research article quasi-ads-b based uav conflict...

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Research Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned Aircraft Chin E. Lin and Ya-Hsien Lai Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan 701, Taiwan Correspondence should be addressed to Chin E. Lin; [email protected] Received 12 October 2014; Revised 12 February 2015; Accepted 24 February 2015 Academic Editor: Christian Wietfeld Copyright © 2015 C. E. Lin and Y.-H. Lai. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A Conflict Detection and Resolution (CD&R) system for manned/unmanned aerial vehicle (UAV) based on Automatic Dependent Surveillance-Broadcast (ADS-B) concept is designed and verified in this paper. e 900 MHz XBee-Pro is selected as data transponder to broadcast flight information among participating aircraſt in omnirange. Standard Compact Position Report (CPR) format packet data are automatically broadcasted by ID sequencing under Quasi-ADS-B mechanism. Time Division Multiple Access (TDMA) monitoring checks the designated time slot and reallocates the conflict ID. is mechanism allows the transponder to effectively share data with multiple aircraſt in near airspace. e STM32f103 microprocessor is designed to handle RF, GPS, and flight data with Windows application on manned aircraſt and ground control station simultaneously. Different conflict detection and collision avoidance algorithms can be implemented into the system to ensure flight safety. e proposed UAV/CD&R using Quasi- ADS-B transceiver is tested using ultralight aircraſt flying at 100–120km/hr speed in small airspace for mission simulation. e proposed hardware is also useful to additional applications to mountain hikers for emergency search and rescue. e fundamental function by the proposed UAV/CD&R using Quasi-ADS-B is verified with effective signal broadcasting for surveillance and efficient collision alert and avoidance performance to low altitude flights. 1. Introduction Airborne support has been a critical part to disaster rescue missions. In the past, the airborne support teams were usually composed of fixed wing and rotary wing manned aircraſt. While the unmanned aerial vehicles (UAVs) have been developed into mature technology, they are deployed into airborne missions for surveillance and data acquisition in civilian applications. As the airborne vehicles are increasingly evolved into the disaster area for joint operations, the irreg- ular UAV performance threats the manned aircraſt in low altitude flights. e function capability of conflict detection and collision avoidance for unmanned aircraſt to manned aircraſt should be paid more attention. A Conflict Detection and Resolution (CD&R) system should be developed and implemented on both unmanned and manned aircraſt in a cooperative airspace. At present, Traffic Alert and Collision Avoidance System (TCAS) is an important and independent system in commer- cial air transportation system for aircraſt separation detection and avoidance resolution under autonomous operation. e Federal Aviation Administration (FAA) and International Civil Aviation Organization (ICAO) have enforced all com- mercial airliners with wider deployments and implementa- tions with TCAS [1]. TCAS II is designed to reduce the incidence of midair collisions between aircraſt by monitoring nearby aircraſt which is equipped with a corresponding active transceiver. Due to more varieties of aircraſt operating in the controlled airspace, different categories of aircraſt also need to settle their TCAS specifications. Business jet or general aviation (GA) is the major consideration in this decade [2, 3]. Despite TCAS requirement of airborne radar, in the CNS/ATM deployment, the Automatic Dependent Surveil- lance-Broadcast (ADS-B) can be used not only to transmit airborne data for air traffic control (ATC) surveillance; new researches have also proposed ADS-B into CD&R mecha- nism for various applications [4, 5]. ADS-B consists of two different services, ADS-B OUT and ADS-B IN. ADS-B OUT periodically broadcasts information of aircraſt identification (ID), current position, Hindawi Publishing Corporation Journal of Electrical and Computer Engineering Volume 2015, Article ID 297859, 12 pages http://dx.doi.org/10.1155/2015/297859

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Page 1: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

Research ArticleQuasi-ADS-B Based UAV Conflict Detection andResolution to Manned Aircraft

Chin E Lin and Ya-Hsien Lai

Department of Aeronautics and Astronautics National Cheng Kung University Tainan 701 Taiwan

Correspondence should be addressed to Chin E Lin chinelinmailnckuedutw

Received 12 October 2014 Revised 12 February 2015 Accepted 24 February 2015

Academic Editor Christian Wietfeld

Copyright copy 2015 C E Lin and Y-H Lai This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

A Conflict Detection and Resolution (CDampR) system for mannedunmanned aerial vehicle (UAV) based on Automatic DependentSurveillance-Broadcast (ADS-B) concept is designed and verified in this paper The 900MHz XBee-Pro is selected as datatransponder to broadcast flight information among participating aircraft in omnirange Standard Compact Position Report (CPR)format packet data are automatically broadcasted by ID sequencing underQuasi-ADS-BmechanismTimeDivisionMultipleAccess(TDMA) monitoring checks the designated time slot and reallocates the conflict ID This mechanism allows the transponder toeffectively share data with multiple aircraft in near airspace The STM32f103 microprocessor is designed to handle RF GPS andflight datawithWindows application onmanned aircraft and ground control station simultaneouslyDifferent conflict detection andcollision avoidance algorithms can be implemented into the system to ensure flight safetyThe proposed UAVCDampR using Quasi-ADS-B transceiver is tested using ultralight aircraft flying at 100ndash120 kmhr speed in small airspace for mission simulation Theproposed hardware is also useful to additional applications to mountain hikers for emergency search and rescue The fundamentalfunction by the proposedUAVCDampRusingQuasi-ADS-B is verifiedwith effective signal broadcasting for surveillance and efficientcollision alert and avoidance performance to low altitude flights

1 Introduction

Airborne support has been a critical part to disaster rescuemissions In the past the airborne support teams wereusually composed of fixed wing and rotary wing mannedaircraft While the unmanned aerial vehicles (UAVs) havebeen developed into mature technology they are deployedinto airbornemissions for surveillance anddata acquisition incivilian applications As the airborne vehicles are increasinglyevolved into the disaster area for joint operations the irreg-ular UAV performance threats the manned aircraft in lowaltitude flights The function capability of conflict detectionand collision avoidance for unmanned aircraft to mannedaircraft should be paid more attention A Conflict Detectionand Resolution (CDampR) system should be developed andimplemented on both unmanned and manned aircraft in acooperative airspace

At present Traffic Alert and Collision Avoidance System(TCAS) is an important and independent system in commer-cial air transportation system for aircraft separation detection

and avoidance resolution under autonomous operation TheFederal Aviation Administration (FAA) and InternationalCivil Aviation Organization (ICAO) have enforced all com-mercial airliners with wider deployments and implementa-tions with TCAS [1] TCAS II is designed to reduce theincidence of midair collisions between aircraft bymonitoringnearby aircraftwhich is equippedwith a corresponding activetransceiver Due to more varieties of aircraft operating in thecontrolled airspace different categories of aircraft also needto settle their TCAS specifications Business jet or generalaviation (GA) is the major consideration in this decade [2 3]

Despite TCAS requirement of airborne radar in theCNSATM deployment the Automatic Dependent Surveil-lance-Broadcast (ADS-B) can be used not only to transmitairborne data for air traffic control (ATC) surveillance newresearches have also proposed ADS-B into CDampR mecha-nism for various applications [4 5]

ADS-B consists of two different services ADS-B OUTand ADS-B IN ADS-B OUT periodically broadcastsinformation of aircraft identification (ID) current position

Hindawi Publishing CorporationJournal of Electrical and Computer EngineeringVolume 2015 Article ID 297859 12 pageshttpdxdoiorg1011552015297859

2 Journal of Electrical and Computer Engineering

altitude and velocity It provides all vicinity aircraft withcoordination information within reasonable range ADS-BIN is the reception of flight data from nearby aircraft Thissystem relies on two avionics components of a high-integrityGPS and a reliable data link transceiver The FAA certifiesADS-B data link of 1090978MHz communication as wellas GPS receiver ADS-B messages are encoded and decodedwith the Compact Position Reporting (CPR) equationsThe use of CPR is to reduce the number of bits requiredto transmit latitude and longitude data [6] For terminalinformation service (TIS) ADS-Rebroadcast is activated touplink the ADS-B data for vicinity aircraft in the terminalairspace [7] ADS-R is an emerging technology for CDampRfor general categories of air transportation [5]

The certified systems for general categories of aircraftare usually complicated heavy and expensive The TCASregulations do not cover below general aviation (GA) aircraftsuch as private aircraft helicopters ultralights and UAVs[5 8] It is not practical to directly implement the matureTCAS into GAs and UAVs Since UAVs have been widelyused in many respects a suitable CDampR for UAVs to mannedaircraft should be constructed to provide aviation safety inlower altitude especially to GA in disaster rescue missions

The proposed CDampR for UAV and GA in collisionavoidance adopts the similar system concept fromTCAS II todeliver traffic information in efficient airspace coverage [3 48 9] using ADS-B data exchangemechanismThe developingsystem should be aimed at performing the similar specifica-tions in both maneuverable function and data formats Thedevelopment can also be appliedwidely into all different typesof GA aircraft including UAVs ultralights and helicoptersin low altitude operation For low altitude airspace operationhorizontal separation will be more appropriate than verticalseparation in flight performance [3 10 11]

This paper focuses on a Quasi-ADS-B transceiver devel-opment in CDampR study for UAVs to GA aircraft Theproposed Quasi-ADS-B uses 900MHz XBee-Pro 900HPfor data broadcasting instead of 1090978MHz in TCASII for air transportation systems in the developing phaseThe system design will suit different CDampR algorithms inTCAS for traffic advisory (TA) and resolution advisory (RA)[3 10 12] The UAVCDampR Quasi-ADS-B transceiver isdesigned and implemented for flight tests using ultralightaircraft in a small confined airspace Some simple avoidanceresolution algorithms are adopted to identify its system per-formance The demonstration of UAVCDampR using Quasi-ADS-B transceiver is successfully verifiedwith real flight testsFurther developments of useful algorithms can be followedfor wider applicationsThe proposed UAVCDampR can gener-ate alert signals to pilots when TA and RA are successfullyidentified by the CDampR algorithms It offers a completesolution for manned aircraft with safety information to avoidintrusion and conflict threat from UAVs

The proposed CDampR system creates a byproduct effect tohiker safety During the flight tests to search for the crashedUAV an additional function is to search for the CDampRtransponder on the carriers for their emergency search andrescue The rescue team and helicopter can find the CDampR

Helicopter

UAV Helicopter

Ground station

Figure 1 Architecture of UAVCDampR using Quasi-ADS-B

transponder signal from the missing mountain hikers Thebasic functions can effectively be verified in flight tests

2 UAVCDampR Quasi ADS-B Transceiver

The main function of the proposed UAVCDampR is focusedon manned aircraft to have the capability to detect and avoidall manned and unmanned aircraft within the surveillanceairspace The UAVCDampR using Quasi-ADS-B transceiverarchitecture is shown in Figure 1 Manned aircraft are shownby helicopters in this figure In the development all themanned aircraft and UAVs are equipped with UAVCDampRQuasi-ADS-B transceivers In this study helicopter is partic-ularly specified in this application as Figure 1 in jointmissionsfor disaster rescueThemanned aircraft is also equipped withmicroprocessor to handle avoidance algorithm calculationand pilot display monitor in communication setup of Quasi-ADS-B OUTIN [7 13] It broadcasts and receives datapackets from the vicinity aircraft in standard ADS-B CPRformat including UAVs and manned aircraft The CDampR fullfunction of TA and RA in audio outputs keeps the pilotsaware of intrusion from the nearby airspace and to performavoidance resolution

The UAVs are equipped with UAVCDampR using Quasi-ADS-B transceivers to broadcast its own (UAV) CDampR datapacket (Quasi-ADS-BOUT) to the vicinity aircraft shown bydashed lines in Figure 1 10 km coverage is restricted by XBee-Pro 900HP performance The scheme in this research treatsUAV as a moving object so the transceiver does not couplewith the flight control system for UAV maneuvering Thismeans the UAVCDampR will not give or receive commandsto change UAV flight control Due to the autopilot natureof civilian UAVs waypoint navigation is the only commandfor flight performance Under such circumstances the UAVsare regarding higher priority than the manned aircraft Allthe manned aircraft should perform appropriate avoidanceto UAVs Therefore the proposed UAVCDampR is universalto any flight control system

Since waypoint navigation is typical in the UAV autopilotflight control in addition the intention of UAVs should bepronounced by themselves with next waypoints It is themost

Journal of Electrical and Computer Engineering 3

feasible way to figure out UAV flight trajectory from thedesignated waypoints for avoidance resolution

The broadcasting data packet is designed following thestandard CPR format in ADS-B plus the following data withnext waypoint in flight [6 7 14 15] The standard CPR(Compact Position Reporting) will be useful to be capable ofmerging and integrating the UAVCDampR system with othersystems using Quasi-ADS-B

Ground control station is deployed for operation surveil-lance and performs ADS-Rebroadcast (ADS-R) [5] in quasi-performance Likewise Quasi-ADS-R repeats Quasi-ADS-Bmessages from one link to the other links for aircraft withQuasi-ADS-B IN relaying data to nearby aircraft to ensureall data being successfully sharedThe communication bridgeis established among these airborne vehicles and groundcontrol station to use a hybrid system between the CPR andadditional part

3 Transceiver Transmission Architecture

The FAA certified communication frequency for ADS-B datalink is 1090978MHz Since this frequency is currently notavailable in this development and to avoid frequency inter-ference to commercial aircraft this research uses 900MHzradio system for preliminary design implementation andtests Although the frequency of the transmissions is differentthe information still follows the CPR formats allowing futuresystem fusion into ADS-B system easier

31 Transceiver Architecture The transceiver architecture isbased on the Time Division Multiple Access (TDMA) mech-anism All participating aircraft will be carrying a transceiverfor Quasi-ADS-BOUT includingUAVs andmanned aircraftThe manned aircraft will have the capability of Quasi-ADS-BIN plus a situation awareness display

Both Quasi-ADS-B OUT and IN are designed into onehardware system This system should be booted up beforeevery flight to run system initialization and GPS lockingAfter the system initialization is finished it starts to sendQuasi-ADS-B OUT once every second and listens for anyQuasi-ADS-B IN data

The transceiver Quasi-ADS-B OUT data output cycle isone secondThis cycle can be split up into twomajor sections(1) the slot sorting section and (2) the transmission cycle [613]

The slot sorting sectionrsquos main purpose is to arrange eachaircraftrsquos transmission slot number The TDMA mechanismin this system allows as many as 10 slots (or 10 IDs) but forsafety precaution a maximum of 8 IDs will be used into theairspace at one timeThe slot sorting section will be split intothree subsections Each subsection is composed of 10 slotsEach aircraft will send a slot message at random time in eachof the 3 subsections It performs overall of sending three slotmessages in the slot sorting section The purpose of sendingthree messages at once every subsection is to ensure that eachtransceiver receives the messages without irregular data jamor loss The slot message includes the aircraft ID and slotnumber ID priority is assigned by the ground control station

UAV always receives higher priority than manned aircraftOtherwise earlier log-in aircraft will receive higher priority

The slot number contained in each message declares theorder of this aircraft and when it will send its transmissionmessage If any transceiver receives conflict data with thesame slot number an automatic slot change mechanism withID priority check will be activated All the participatingtransceiverswill be reassigned by their IDswith priority AfterID priority check the transceiver with lower priority ID willbe reassigned to an unused slot to broadcast its data After theslot sorting sequence ends at 300ms mark all aircraftrsquos slotnumber has been sorted out the next stage of Quasi-ADS-BOUTdata output cycle will startThe transceiver pseudo codeis shown in Algorithm 1

The transmission cycle exchanges data between every oneof the aircraft in the area This section contains 10 slots Eachaircraft will execute its data OUT procedure at its assignedslot time to ensure no data jamming

In this paper considering disaster rescue missions areasonable number of aircraft in the surveillance airspace areassumed It might be several rescue helicopters cooperatingwith a few UAVs Figure 2 shows an example of a commu-nication time chart for 8 different aircraft operating in thesame small airspace The slot sorting section time chart is0sim300ms while the latter part of 300sim800ms carries out theUAVCDampRdata as Quasi-ADS-BOUT 800mssim1000ms arebackup slots for emergency slots or future spare for systemexpansion

The transmissions are synchronized with GPS clock inevery second The slot sorting sequence transmission is 11-byte data composed of start bit (2 bytes) UAV ID (4 bytes)slot number (1 byte) checksum (2 bytes) and end bit (2bytes) Since the slot sorting data of Quasi-ADS-B OUTtransmission takes less than 10ms the time slot in this sectionis assigned by 10ms To ensure data reception by Quasi-ADS-B IN each aircraft sends three sets of sorting sequencedata over 300ms The capacity of the proposed system isbottlenecked by 10 aircraft

The data transmission is carried out from 300ms to800ms Because the UBLOX decrypts GPS data in 280msdata transmission delays 300ms for synchronization Thedata transmitted for UAV in this section includes coordinatesof current position and next waypoint For the helicopterthe transmitted data will be current position and destinationThese data are both encoded by the CPR Each aircraftbroadcasts its two data packets in a 50ms slot by the sequenceof ID number from the sorting section that is slot one at300mssim350ms until slot eight at 650mssim700ms

CPR converts the data into 35 bits instead of the 45 bitssaving 10 bits per position message It does not transmithigher-order bits in the whole period of the flight Both even-format and odd-format are transmitted firstly to unambigu-ously determine the location of the aircraft Once this processhas been carried out and the higher-order bits are knownonly one kind of format can be selected to determine theposition of the aircraft

With this concept all airborne aircraftwill know the posi-tion of others in this airspace to achieve cooperativemissionsAfter the position sharing is established the proposed conflict

4 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

OUTPUT ID + Slot numberIF ownership slot number = intruder slot number

IF ownership ID priority gt intruder ID priorityOwnership slot number remains

ELSEOwnership slot number shifts to an unused slot

ENDIFENDIF

OUTPUT GPS dataINPUT GPS data of all aircraft

UNTIL shutdown

Algorithm 1 Transceiver architecture

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

Transmit ID only for transmit sequence

0xfa

UAV 040x4b

0x01 0x0f 0x15 0x29 0x3a 0xaa 0xfa

0x3a

0x4b 0xaa

UAV 030x29

0x01 0x0f 0x15 0x3a 0x4b 0xaa

0xfa

0x4b 0xaa 0xfa

UAV 020xfa

0x01 0x0f 0x15 0x29 0x3a

UAV 010x15

0x01 0x0f 0x29

Heli 040xaa

0x01 0x0f 0x15 0x29 0x3a 0x4b

0xaa 0xfa

Heli 030x3a

0x01 0x0f 0x15 0x29 0x4b 0xaa 0xfa

0x4b 0xaa 0xfa

Heli 020x0f

0x01 0x15 0x29 0x3a 0x4b

Heli 010x01

0x0f 0x15 0x29 0x3a

Sorting start Transmission start

Transmit data ID + GPS data (each sector = 50ms)

1000ms0ms 100ms 200ms 300ms 400ms 500ms 600ms 700ms 800ms 900ms

Figure 2 An example of 8-aircraft transmission time chart

detection and collision avoidance algorithm helps to ensurethe safety separation and avoidance of the manned aircraftfrom the intruders

32 Hardware The proposed UAVCDampR transceiverenables cross communications among aircraft in a smallairspace to exchange flight data The proposed transceiversystem is shown in Figure 3 consisting of a MCU GPS mod-ule and a wireless module The adopted MCU STM32f103is a 32-bit flash microcontroller based on the ARM Cortexprocessor MCU handles GPS data input from GPS moduleUBLOX Lea 6 h and communicates to other MCU throughthe wireless module XBee-Pro 900HP The GPS has anerror bubble of 5m GPS accuracy is acceptable for CDampR

performance GPS data reliability and stability on UAV canbe maintained by using high performance antenna

Communication platform varies for different applica-tions The commercial ADS-B uses 1090978MHz [1 6]Because it is a regulated frequency it is difficult to findavailable 1090978MHz radio module in the preliminarydevelopment An available wireless module of XBee-Pro900HP is elected to integrate into the proposed UAVCDampRtransceiver for function capabilityTheXBee-Pro 900HP uses900MHz frequency for data transfer rate up to 200 kbps Itis similar to 1090978MHz system using the same CPR datacoding

Figure 4 shows the proposed hardware for test in acomplete set for the manned aircraft in UAVCDampR per-formance The left part is a transmitter-only (Quasi-ADS-B

Journal of Electrical and Computer Engineering 5

Manned aircraft

MCU MCU

U-bloxGPS

U-bloxGPS

XBee900MHz

XBee900MHz

Unmanned aircraft

Figure 3 UAVCDampR in ADS-B hardware

MCU

XBee

GPS

(a) UAVCDampR ADS-B

Power XBee signal

GPS signal

(b) UAVCDampR display

Figure 4 UAVCDampR transceiver for UAV (left only) and for manned aircraft (all)

OUT) hardware for installing onUAVs while the right part istransceiver (Quasi-ADS-B OUTIN) and display for mannedaircraft For the manned aircraft a microcomputer withLCD display is added with conflict detection and collisionavoidance algorithm The proposed UAVCDampR is designedto suit different software from which proximity advisory(PA) traffic advisory (TA) and resolution advisory (RA) willbe issued

33 Conflict Advisories The UAVCDampR algorithm isinstalled in the microprocessor on the manned aircraftCDampR display is shown in Figure 5 by a COM port setup

Commsetup

TCAS display

ac data

Figure 5 UAVCDampR interface display

6 Journal of Electrical and Computer Engineering

Manned aircraft

Dummy unmanned aircraft

Ground base

Figure 6 Two ultralight aircraft for flight test

to show all received data on the top and traffic informationof TA and RA on the screen Both TA and RA are markedby hemisphere sector with a sense of time to conflict Thereceived data include vicinity aircraft GPS coordinates UTCtime next waypoint of UAV (or destination of mannedaircraft) slot ID and the wireless transmission health of eachaircraft

The CDampR display will have three different advisorieswith visual and audio warnings In PA the screen will remaingray with audio alarm ldquoIntrusion XXX at Y (XXX = az Y =dis)rdquo In TA the screen will change into bright yellow withaudio alert ldquoTraffic Trafficrdquo InRA the displaywill be changedinto bright red with audio warning ldquoTurn rightrdquo All alert andwarning will still show every aircraft on the CDampR display

4 Flight Experiment

To verify the operation functions of the proposed UAVCDampR transceiver system a series of flight tests is carriedout to examine the capability of the flight data transmissionTwo ultralight aircraft are used to carry the UAVCDampRtransceiver in cooperation with a ground control stationas shown in Figure 6 One of the ultralight aircraft acts asa manned aircraft (or as manned helicopter) to performconflict detection and collision avoidance while the otherplays as an UAV to fly from waypoint to waypoint

In the preliminary flight experiments the XBee omnidi-rectional transceiver collects around 97 of the data from theUAVand 100 from its ownGPSAlthough there is a 3dropof data these data spread throughout the whole experimentand all happenedwhen they are separated over 1 km away outof PAdistance In theXBee the possible data loss happens lessthan 2 seconds in continuous flight testThe time delay in theQuasi-ADS-B OUTIN and CDampR computation is examinedwith less than 2 seconds in overall tests When all the testaircraft speeds are less than 120 kmhr the possible separationshrinkage falls within 360 meters before an alert is generatedto the pilotsThis separation is important to TARA design intheCDampR algorithmThe collected data in flight experimentsare used in the CDampR algorithms for further simulation andfunction verification

5 CDampR Algorithm and Validation

This paper is mainly focused on UAVCDampR transceiverhardware design and implementation using Quasi-ADS-BThe following CDampR algorithms are only adopted for flightvalidation in the transponding performance The CDampRmethodologies are not presented in detail

The proposed UAVCDampR system is designed to allowdifferent CDampR algorithms to be validated in real flight testAssume that each algorithm requires different sensors theproposed UAVCDampR transceiver hardware is also capableof integrating sensor information into dynamic resolution [213 15] In CDampR operation when the aircraft detects vicinityflight activities in the near airspace intruder will be identifiedby proximity advisory (PA) where the minor possibility ofconflict is raised When the intrusion approaches into anear range traffic advisory (TA) is pronounced with analert Afterward the intrusion enters close range resolutionadvisory (RA) is generated to give pilot a warning In ICAOPA TA and RA are defined in time to conflict (TTC)markedby 120591 in secondsThe sensitive level (SL) and alarm thresholdsare defined by TTC according to the flight altitude In thisstudy the operating altitude is around 1000 meters aboveground level (AGL) The values are defined as TA = 30 secRA = 20 sec [1]

From CDampR algorithm the manned aircraft (ownership)detects any aircraft within 3 km radius from itself Onceany intrusions are detected the trajectory estimation andprobabilistic grids detection (PGD) are generated If all thetime sectors probability is under the threshold the wholeprocess restarts If any sector probability continues to increaseinto dangerous threshold the time and sector recognition(TSR)will further generate TA alert andRAwarning to pilotsPGD and TSR are explained in brief The CDampR algorithmpseudo code is shown in Algorithm 2

51 Probabilistic Grid Detection (PGD) The PGD algorithmis chosen to implant by the flight path detection for multipleaircraft in the operating airspaceThe PGD is a weighted gridon the probability of the aircraft reaching the same sectorat the same time Each aircraft will generate numerous gridsper second The grids in each second describe the positionprediction of the aircraft in advance The probability gridvalue is based on the predicted coordinate in certain timeinterval Then each grid value is calculated by applying theGaussian Function for 120583 represents the mean of expectationof the distribution (and also its median and mode) and 120590 and1205902 are its standard deviation and variance

119891 (119909) =1

120590radic2120587119890minus(119909minus120583)

221205902

(1)

With the combination of the parameters different prob-abilities can be established based on different conditions andpositions of the aircraft As the estimation progresses intime (meaning the farther ahead the prediction is) the errorincreases with time By adjusting the standard deviation andvariance the correct assumptions can be met

When the aircraftrsquos probability grid is generated each gridwith the same time stamp will be calculated together to get

Journal of Electrical and Computer Engineering 7

Initialization lowast System initialized and GPS lock lowastREPEAT every secondOUTPUT GPS data

INPUT Intruders GPS dataIF Intruder distance to ownership lt3 km

Trajectory estimation constructionEstablish PGDCalculate confliction probabilitiesIF conflict probability gt threshold

TSR CDampR generationTA alertRA warning

ENDIFENDIF

UNTIL shutdown

Algorithm 2 CDampR architecture

5 5 10 20 10 5 5

5 5 15 5 5

5 5 5

(b)

5

5 5

10 5 5

20 10 5

10 5 5

(a)

Figure 7 Probability of conflict in time119873

theweighted probability of collision at the certain time stampFor simplicity only time stamp 119873 is shown in Figure 7 ThePGD algorithm detects the possible intrusion to the mannedaircraft and PA will be pronounced

Afterwards when PA is issued a near field sector recogni-tion algorithm is executed to calculate a safe path to avoidconflict TSR CDampR will continue to check the separationamont intrusion aircraft after PA has been issued The PGDalgorithm pseudo code is shown in Algorithm 3

Figure 8 shows a section of the flight test Solid curvedlines are the real trajectory in record The dotted straightline with asterisk symbol is a straight line estimation of the

trajectory connecting the current point to the waypoint Thedotted line with circle symbol is the estimated trajectoryusing the algorithm discussed in this paper From the figuresthe doted circle trajectory is estimated with closer approachthan the straight asterisk line Although one section of thetrajectories in Figure 8 is deviated from the recorded pointsby 20m their conflict point is still closer to the real conflictpoint than the straight trajectory method

The probability grid is generated and each second proba-bility of conflict is shown as a figure in Figure 9 In the test themaximum single point percentage and the integer percentageare both at the 26th second Although the absolute percentage

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

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International Journal of

Page 2: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

2 Journal of Electrical and Computer Engineering

altitude and velocity It provides all vicinity aircraft withcoordination information within reasonable range ADS-BIN is the reception of flight data from nearby aircraft Thissystem relies on two avionics components of a high-integrityGPS and a reliable data link transceiver The FAA certifiesADS-B data link of 1090978MHz communication as wellas GPS receiver ADS-B messages are encoded and decodedwith the Compact Position Reporting (CPR) equationsThe use of CPR is to reduce the number of bits requiredto transmit latitude and longitude data [6] For terminalinformation service (TIS) ADS-Rebroadcast is activated touplink the ADS-B data for vicinity aircraft in the terminalairspace [7] ADS-R is an emerging technology for CDampRfor general categories of air transportation [5]

The certified systems for general categories of aircraftare usually complicated heavy and expensive The TCASregulations do not cover below general aviation (GA) aircraftsuch as private aircraft helicopters ultralights and UAVs[5 8] It is not practical to directly implement the matureTCAS into GAs and UAVs Since UAVs have been widelyused in many respects a suitable CDampR for UAVs to mannedaircraft should be constructed to provide aviation safety inlower altitude especially to GA in disaster rescue missions

The proposed CDampR for UAV and GA in collisionavoidance adopts the similar system concept fromTCAS II todeliver traffic information in efficient airspace coverage [3 48 9] using ADS-B data exchangemechanismThe developingsystem should be aimed at performing the similar specifica-tions in both maneuverable function and data formats Thedevelopment can also be appliedwidely into all different typesof GA aircraft including UAVs ultralights and helicoptersin low altitude operation For low altitude airspace operationhorizontal separation will be more appropriate than verticalseparation in flight performance [3 10 11]

This paper focuses on a Quasi-ADS-B transceiver devel-opment in CDampR study for UAVs to GA aircraft Theproposed Quasi-ADS-B uses 900MHz XBee-Pro 900HPfor data broadcasting instead of 1090978MHz in TCASII for air transportation systems in the developing phaseThe system design will suit different CDampR algorithms inTCAS for traffic advisory (TA) and resolution advisory (RA)[3 10 12] The UAVCDampR Quasi-ADS-B transceiver isdesigned and implemented for flight tests using ultralightaircraft in a small confined airspace Some simple avoidanceresolution algorithms are adopted to identify its system per-formance The demonstration of UAVCDampR using Quasi-ADS-B transceiver is successfully verifiedwith real flight testsFurther developments of useful algorithms can be followedfor wider applicationsThe proposed UAVCDampR can gener-ate alert signals to pilots when TA and RA are successfullyidentified by the CDampR algorithms It offers a completesolution for manned aircraft with safety information to avoidintrusion and conflict threat from UAVs

The proposed CDampR system creates a byproduct effect tohiker safety During the flight tests to search for the crashedUAV an additional function is to search for the CDampRtransponder on the carriers for their emergency search andrescue The rescue team and helicopter can find the CDampR

Helicopter

UAV Helicopter

Ground station

Figure 1 Architecture of UAVCDampR using Quasi-ADS-B

transponder signal from the missing mountain hikers Thebasic functions can effectively be verified in flight tests

2 UAVCDampR Quasi ADS-B Transceiver

The main function of the proposed UAVCDampR is focusedon manned aircraft to have the capability to detect and avoidall manned and unmanned aircraft within the surveillanceairspace The UAVCDampR using Quasi-ADS-B transceiverarchitecture is shown in Figure 1 Manned aircraft are shownby helicopters in this figure In the development all themanned aircraft and UAVs are equipped with UAVCDampRQuasi-ADS-B transceivers In this study helicopter is partic-ularly specified in this application as Figure 1 in jointmissionsfor disaster rescueThemanned aircraft is also equipped withmicroprocessor to handle avoidance algorithm calculationand pilot display monitor in communication setup of Quasi-ADS-B OUTIN [7 13] It broadcasts and receives datapackets from the vicinity aircraft in standard ADS-B CPRformat including UAVs and manned aircraft The CDampR fullfunction of TA and RA in audio outputs keeps the pilotsaware of intrusion from the nearby airspace and to performavoidance resolution

The UAVs are equipped with UAVCDampR using Quasi-ADS-B transceivers to broadcast its own (UAV) CDampR datapacket (Quasi-ADS-BOUT) to the vicinity aircraft shown bydashed lines in Figure 1 10 km coverage is restricted by XBee-Pro 900HP performance The scheme in this research treatsUAV as a moving object so the transceiver does not couplewith the flight control system for UAV maneuvering Thismeans the UAVCDampR will not give or receive commandsto change UAV flight control Due to the autopilot natureof civilian UAVs waypoint navigation is the only commandfor flight performance Under such circumstances the UAVsare regarding higher priority than the manned aircraft Allthe manned aircraft should perform appropriate avoidanceto UAVs Therefore the proposed UAVCDampR is universalto any flight control system

Since waypoint navigation is typical in the UAV autopilotflight control in addition the intention of UAVs should bepronounced by themselves with next waypoints It is themost

Journal of Electrical and Computer Engineering 3

feasible way to figure out UAV flight trajectory from thedesignated waypoints for avoidance resolution

The broadcasting data packet is designed following thestandard CPR format in ADS-B plus the following data withnext waypoint in flight [6 7 14 15] The standard CPR(Compact Position Reporting) will be useful to be capable ofmerging and integrating the UAVCDampR system with othersystems using Quasi-ADS-B

Ground control station is deployed for operation surveil-lance and performs ADS-Rebroadcast (ADS-R) [5] in quasi-performance Likewise Quasi-ADS-R repeats Quasi-ADS-Bmessages from one link to the other links for aircraft withQuasi-ADS-B IN relaying data to nearby aircraft to ensureall data being successfully sharedThe communication bridgeis established among these airborne vehicles and groundcontrol station to use a hybrid system between the CPR andadditional part

3 Transceiver Transmission Architecture

The FAA certified communication frequency for ADS-B datalink is 1090978MHz Since this frequency is currently notavailable in this development and to avoid frequency inter-ference to commercial aircraft this research uses 900MHzradio system for preliminary design implementation andtests Although the frequency of the transmissions is differentthe information still follows the CPR formats allowing futuresystem fusion into ADS-B system easier

31 Transceiver Architecture The transceiver architecture isbased on the Time Division Multiple Access (TDMA) mech-anism All participating aircraft will be carrying a transceiverfor Quasi-ADS-BOUT includingUAVs andmanned aircraftThe manned aircraft will have the capability of Quasi-ADS-BIN plus a situation awareness display

Both Quasi-ADS-B OUT and IN are designed into onehardware system This system should be booted up beforeevery flight to run system initialization and GPS lockingAfter the system initialization is finished it starts to sendQuasi-ADS-B OUT once every second and listens for anyQuasi-ADS-B IN data

The transceiver Quasi-ADS-B OUT data output cycle isone secondThis cycle can be split up into twomajor sections(1) the slot sorting section and (2) the transmission cycle [613]

The slot sorting sectionrsquos main purpose is to arrange eachaircraftrsquos transmission slot number The TDMA mechanismin this system allows as many as 10 slots (or 10 IDs) but forsafety precaution a maximum of 8 IDs will be used into theairspace at one timeThe slot sorting section will be split intothree subsections Each subsection is composed of 10 slotsEach aircraft will send a slot message at random time in eachof the 3 subsections It performs overall of sending three slotmessages in the slot sorting section The purpose of sendingthree messages at once every subsection is to ensure that eachtransceiver receives the messages without irregular data jamor loss The slot message includes the aircraft ID and slotnumber ID priority is assigned by the ground control station

UAV always receives higher priority than manned aircraftOtherwise earlier log-in aircraft will receive higher priority

The slot number contained in each message declares theorder of this aircraft and when it will send its transmissionmessage If any transceiver receives conflict data with thesame slot number an automatic slot change mechanism withID priority check will be activated All the participatingtransceiverswill be reassigned by their IDswith priority AfterID priority check the transceiver with lower priority ID willbe reassigned to an unused slot to broadcast its data After theslot sorting sequence ends at 300ms mark all aircraftrsquos slotnumber has been sorted out the next stage of Quasi-ADS-BOUTdata output cycle will startThe transceiver pseudo codeis shown in Algorithm 1

The transmission cycle exchanges data between every oneof the aircraft in the area This section contains 10 slots Eachaircraft will execute its data OUT procedure at its assignedslot time to ensure no data jamming

In this paper considering disaster rescue missions areasonable number of aircraft in the surveillance airspace areassumed It might be several rescue helicopters cooperatingwith a few UAVs Figure 2 shows an example of a commu-nication time chart for 8 different aircraft operating in thesame small airspace The slot sorting section time chart is0sim300ms while the latter part of 300sim800ms carries out theUAVCDampRdata as Quasi-ADS-BOUT 800mssim1000ms arebackup slots for emergency slots or future spare for systemexpansion

The transmissions are synchronized with GPS clock inevery second The slot sorting sequence transmission is 11-byte data composed of start bit (2 bytes) UAV ID (4 bytes)slot number (1 byte) checksum (2 bytes) and end bit (2bytes) Since the slot sorting data of Quasi-ADS-B OUTtransmission takes less than 10ms the time slot in this sectionis assigned by 10ms To ensure data reception by Quasi-ADS-B IN each aircraft sends three sets of sorting sequencedata over 300ms The capacity of the proposed system isbottlenecked by 10 aircraft

The data transmission is carried out from 300ms to800ms Because the UBLOX decrypts GPS data in 280msdata transmission delays 300ms for synchronization Thedata transmitted for UAV in this section includes coordinatesof current position and next waypoint For the helicopterthe transmitted data will be current position and destinationThese data are both encoded by the CPR Each aircraftbroadcasts its two data packets in a 50ms slot by the sequenceof ID number from the sorting section that is slot one at300mssim350ms until slot eight at 650mssim700ms

CPR converts the data into 35 bits instead of the 45 bitssaving 10 bits per position message It does not transmithigher-order bits in the whole period of the flight Both even-format and odd-format are transmitted firstly to unambigu-ously determine the location of the aircraft Once this processhas been carried out and the higher-order bits are knownonly one kind of format can be selected to determine theposition of the aircraft

With this concept all airborne aircraftwill know the posi-tion of others in this airspace to achieve cooperativemissionsAfter the position sharing is established the proposed conflict

4 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

OUTPUT ID + Slot numberIF ownership slot number = intruder slot number

IF ownership ID priority gt intruder ID priorityOwnership slot number remains

ELSEOwnership slot number shifts to an unused slot

ENDIFENDIF

OUTPUT GPS dataINPUT GPS data of all aircraft

UNTIL shutdown

Algorithm 1 Transceiver architecture

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

Transmit ID only for transmit sequence

0xfa

UAV 040x4b

0x01 0x0f 0x15 0x29 0x3a 0xaa 0xfa

0x3a

0x4b 0xaa

UAV 030x29

0x01 0x0f 0x15 0x3a 0x4b 0xaa

0xfa

0x4b 0xaa 0xfa

UAV 020xfa

0x01 0x0f 0x15 0x29 0x3a

UAV 010x15

0x01 0x0f 0x29

Heli 040xaa

0x01 0x0f 0x15 0x29 0x3a 0x4b

0xaa 0xfa

Heli 030x3a

0x01 0x0f 0x15 0x29 0x4b 0xaa 0xfa

0x4b 0xaa 0xfa

Heli 020x0f

0x01 0x15 0x29 0x3a 0x4b

Heli 010x01

0x0f 0x15 0x29 0x3a

Sorting start Transmission start

Transmit data ID + GPS data (each sector = 50ms)

1000ms0ms 100ms 200ms 300ms 400ms 500ms 600ms 700ms 800ms 900ms

Figure 2 An example of 8-aircraft transmission time chart

detection and collision avoidance algorithm helps to ensurethe safety separation and avoidance of the manned aircraftfrom the intruders

32 Hardware The proposed UAVCDampR transceiverenables cross communications among aircraft in a smallairspace to exchange flight data The proposed transceiversystem is shown in Figure 3 consisting of a MCU GPS mod-ule and a wireless module The adopted MCU STM32f103is a 32-bit flash microcontroller based on the ARM Cortexprocessor MCU handles GPS data input from GPS moduleUBLOX Lea 6 h and communicates to other MCU throughthe wireless module XBee-Pro 900HP The GPS has anerror bubble of 5m GPS accuracy is acceptable for CDampR

performance GPS data reliability and stability on UAV canbe maintained by using high performance antenna

Communication platform varies for different applica-tions The commercial ADS-B uses 1090978MHz [1 6]Because it is a regulated frequency it is difficult to findavailable 1090978MHz radio module in the preliminarydevelopment An available wireless module of XBee-Pro900HP is elected to integrate into the proposed UAVCDampRtransceiver for function capabilityTheXBee-Pro 900HP uses900MHz frequency for data transfer rate up to 200 kbps Itis similar to 1090978MHz system using the same CPR datacoding

Figure 4 shows the proposed hardware for test in acomplete set for the manned aircraft in UAVCDampR per-formance The left part is a transmitter-only (Quasi-ADS-B

Journal of Electrical and Computer Engineering 5

Manned aircraft

MCU MCU

U-bloxGPS

U-bloxGPS

XBee900MHz

XBee900MHz

Unmanned aircraft

Figure 3 UAVCDampR in ADS-B hardware

MCU

XBee

GPS

(a) UAVCDampR ADS-B

Power XBee signal

GPS signal

(b) UAVCDampR display

Figure 4 UAVCDampR transceiver for UAV (left only) and for manned aircraft (all)

OUT) hardware for installing onUAVs while the right part istransceiver (Quasi-ADS-B OUTIN) and display for mannedaircraft For the manned aircraft a microcomputer withLCD display is added with conflict detection and collisionavoidance algorithm The proposed UAVCDampR is designedto suit different software from which proximity advisory(PA) traffic advisory (TA) and resolution advisory (RA) willbe issued

33 Conflict Advisories The UAVCDampR algorithm isinstalled in the microprocessor on the manned aircraftCDampR display is shown in Figure 5 by a COM port setup

Commsetup

TCAS display

ac data

Figure 5 UAVCDampR interface display

6 Journal of Electrical and Computer Engineering

Manned aircraft

Dummy unmanned aircraft

Ground base

Figure 6 Two ultralight aircraft for flight test

to show all received data on the top and traffic informationof TA and RA on the screen Both TA and RA are markedby hemisphere sector with a sense of time to conflict Thereceived data include vicinity aircraft GPS coordinates UTCtime next waypoint of UAV (or destination of mannedaircraft) slot ID and the wireless transmission health of eachaircraft

The CDampR display will have three different advisorieswith visual and audio warnings In PA the screen will remaingray with audio alarm ldquoIntrusion XXX at Y (XXX = az Y =dis)rdquo In TA the screen will change into bright yellow withaudio alert ldquoTraffic Trafficrdquo InRA the displaywill be changedinto bright red with audio warning ldquoTurn rightrdquo All alert andwarning will still show every aircraft on the CDampR display

4 Flight Experiment

To verify the operation functions of the proposed UAVCDampR transceiver system a series of flight tests is carriedout to examine the capability of the flight data transmissionTwo ultralight aircraft are used to carry the UAVCDampRtransceiver in cooperation with a ground control stationas shown in Figure 6 One of the ultralight aircraft acts asa manned aircraft (or as manned helicopter) to performconflict detection and collision avoidance while the otherplays as an UAV to fly from waypoint to waypoint

In the preliminary flight experiments the XBee omnidi-rectional transceiver collects around 97 of the data from theUAVand 100 from its ownGPSAlthough there is a 3dropof data these data spread throughout the whole experimentand all happenedwhen they are separated over 1 km away outof PAdistance In theXBee the possible data loss happens lessthan 2 seconds in continuous flight testThe time delay in theQuasi-ADS-B OUTIN and CDampR computation is examinedwith less than 2 seconds in overall tests When all the testaircraft speeds are less than 120 kmhr the possible separationshrinkage falls within 360 meters before an alert is generatedto the pilotsThis separation is important to TARA design intheCDampR algorithmThe collected data in flight experimentsare used in the CDampR algorithms for further simulation andfunction verification

5 CDampR Algorithm and Validation

This paper is mainly focused on UAVCDampR transceiverhardware design and implementation using Quasi-ADS-BThe following CDampR algorithms are only adopted for flightvalidation in the transponding performance The CDampRmethodologies are not presented in detail

The proposed UAVCDampR system is designed to allowdifferent CDampR algorithms to be validated in real flight testAssume that each algorithm requires different sensors theproposed UAVCDampR transceiver hardware is also capableof integrating sensor information into dynamic resolution [213 15] In CDampR operation when the aircraft detects vicinityflight activities in the near airspace intruder will be identifiedby proximity advisory (PA) where the minor possibility ofconflict is raised When the intrusion approaches into anear range traffic advisory (TA) is pronounced with analert Afterward the intrusion enters close range resolutionadvisory (RA) is generated to give pilot a warning In ICAOPA TA and RA are defined in time to conflict (TTC)markedby 120591 in secondsThe sensitive level (SL) and alarm thresholdsare defined by TTC according to the flight altitude In thisstudy the operating altitude is around 1000 meters aboveground level (AGL) The values are defined as TA = 30 secRA = 20 sec [1]

From CDampR algorithm the manned aircraft (ownership)detects any aircraft within 3 km radius from itself Onceany intrusions are detected the trajectory estimation andprobabilistic grids detection (PGD) are generated If all thetime sectors probability is under the threshold the wholeprocess restarts If any sector probability continues to increaseinto dangerous threshold the time and sector recognition(TSR)will further generate TA alert andRAwarning to pilotsPGD and TSR are explained in brief The CDampR algorithmpseudo code is shown in Algorithm 2

51 Probabilistic Grid Detection (PGD) The PGD algorithmis chosen to implant by the flight path detection for multipleaircraft in the operating airspaceThe PGD is a weighted gridon the probability of the aircraft reaching the same sectorat the same time Each aircraft will generate numerous gridsper second The grids in each second describe the positionprediction of the aircraft in advance The probability gridvalue is based on the predicted coordinate in certain timeinterval Then each grid value is calculated by applying theGaussian Function for 120583 represents the mean of expectationof the distribution (and also its median and mode) and 120590 and1205902 are its standard deviation and variance

119891 (119909) =1

120590radic2120587119890minus(119909minus120583)

221205902

(1)

With the combination of the parameters different prob-abilities can be established based on different conditions andpositions of the aircraft As the estimation progresses intime (meaning the farther ahead the prediction is) the errorincreases with time By adjusting the standard deviation andvariance the correct assumptions can be met

When the aircraftrsquos probability grid is generated each gridwith the same time stamp will be calculated together to get

Journal of Electrical and Computer Engineering 7

Initialization lowast System initialized and GPS lock lowastREPEAT every secondOUTPUT GPS data

INPUT Intruders GPS dataIF Intruder distance to ownership lt3 km

Trajectory estimation constructionEstablish PGDCalculate confliction probabilitiesIF conflict probability gt threshold

TSR CDampR generationTA alertRA warning

ENDIFENDIF

UNTIL shutdown

Algorithm 2 CDampR architecture

5 5 10 20 10 5 5

5 5 15 5 5

5 5 5

(b)

5

5 5

10 5 5

20 10 5

10 5 5

(a)

Figure 7 Probability of conflict in time119873

theweighted probability of collision at the certain time stampFor simplicity only time stamp 119873 is shown in Figure 7 ThePGD algorithm detects the possible intrusion to the mannedaircraft and PA will be pronounced

Afterwards when PA is issued a near field sector recogni-tion algorithm is executed to calculate a safe path to avoidconflict TSR CDampR will continue to check the separationamont intrusion aircraft after PA has been issued The PGDalgorithm pseudo code is shown in Algorithm 3

Figure 8 shows a section of the flight test Solid curvedlines are the real trajectory in record The dotted straightline with asterisk symbol is a straight line estimation of the

trajectory connecting the current point to the waypoint Thedotted line with circle symbol is the estimated trajectoryusing the algorithm discussed in this paper From the figuresthe doted circle trajectory is estimated with closer approachthan the straight asterisk line Although one section of thetrajectories in Figure 8 is deviated from the recorded pointsby 20m their conflict point is still closer to the real conflictpoint than the straight trajectory method

The probability grid is generated and each second proba-bility of conflict is shown as a figure in Figure 9 In the test themaximum single point percentage and the integer percentageare both at the 26th second Although the absolute percentage

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

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Page 3: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

Journal of Electrical and Computer Engineering 3

feasible way to figure out UAV flight trajectory from thedesignated waypoints for avoidance resolution

The broadcasting data packet is designed following thestandard CPR format in ADS-B plus the following data withnext waypoint in flight [6 7 14 15] The standard CPR(Compact Position Reporting) will be useful to be capable ofmerging and integrating the UAVCDampR system with othersystems using Quasi-ADS-B

Ground control station is deployed for operation surveil-lance and performs ADS-Rebroadcast (ADS-R) [5] in quasi-performance Likewise Quasi-ADS-R repeats Quasi-ADS-Bmessages from one link to the other links for aircraft withQuasi-ADS-B IN relaying data to nearby aircraft to ensureall data being successfully sharedThe communication bridgeis established among these airborne vehicles and groundcontrol station to use a hybrid system between the CPR andadditional part

3 Transceiver Transmission Architecture

The FAA certified communication frequency for ADS-B datalink is 1090978MHz Since this frequency is currently notavailable in this development and to avoid frequency inter-ference to commercial aircraft this research uses 900MHzradio system for preliminary design implementation andtests Although the frequency of the transmissions is differentthe information still follows the CPR formats allowing futuresystem fusion into ADS-B system easier

31 Transceiver Architecture The transceiver architecture isbased on the Time Division Multiple Access (TDMA) mech-anism All participating aircraft will be carrying a transceiverfor Quasi-ADS-BOUT includingUAVs andmanned aircraftThe manned aircraft will have the capability of Quasi-ADS-BIN plus a situation awareness display

Both Quasi-ADS-B OUT and IN are designed into onehardware system This system should be booted up beforeevery flight to run system initialization and GPS lockingAfter the system initialization is finished it starts to sendQuasi-ADS-B OUT once every second and listens for anyQuasi-ADS-B IN data

The transceiver Quasi-ADS-B OUT data output cycle isone secondThis cycle can be split up into twomajor sections(1) the slot sorting section and (2) the transmission cycle [613]

The slot sorting sectionrsquos main purpose is to arrange eachaircraftrsquos transmission slot number The TDMA mechanismin this system allows as many as 10 slots (or 10 IDs) but forsafety precaution a maximum of 8 IDs will be used into theairspace at one timeThe slot sorting section will be split intothree subsections Each subsection is composed of 10 slotsEach aircraft will send a slot message at random time in eachof the 3 subsections It performs overall of sending three slotmessages in the slot sorting section The purpose of sendingthree messages at once every subsection is to ensure that eachtransceiver receives the messages without irregular data jamor loss The slot message includes the aircraft ID and slotnumber ID priority is assigned by the ground control station

UAV always receives higher priority than manned aircraftOtherwise earlier log-in aircraft will receive higher priority

The slot number contained in each message declares theorder of this aircraft and when it will send its transmissionmessage If any transceiver receives conflict data with thesame slot number an automatic slot change mechanism withID priority check will be activated All the participatingtransceiverswill be reassigned by their IDswith priority AfterID priority check the transceiver with lower priority ID willbe reassigned to an unused slot to broadcast its data After theslot sorting sequence ends at 300ms mark all aircraftrsquos slotnumber has been sorted out the next stage of Quasi-ADS-BOUTdata output cycle will startThe transceiver pseudo codeis shown in Algorithm 1

The transmission cycle exchanges data between every oneof the aircraft in the area This section contains 10 slots Eachaircraft will execute its data OUT procedure at its assignedslot time to ensure no data jamming

In this paper considering disaster rescue missions areasonable number of aircraft in the surveillance airspace areassumed It might be several rescue helicopters cooperatingwith a few UAVs Figure 2 shows an example of a commu-nication time chart for 8 different aircraft operating in thesame small airspace The slot sorting section time chart is0sim300ms while the latter part of 300sim800ms carries out theUAVCDampRdata as Quasi-ADS-BOUT 800mssim1000ms arebackup slots for emergency slots or future spare for systemexpansion

The transmissions are synchronized with GPS clock inevery second The slot sorting sequence transmission is 11-byte data composed of start bit (2 bytes) UAV ID (4 bytes)slot number (1 byte) checksum (2 bytes) and end bit (2bytes) Since the slot sorting data of Quasi-ADS-B OUTtransmission takes less than 10ms the time slot in this sectionis assigned by 10ms To ensure data reception by Quasi-ADS-B IN each aircraft sends three sets of sorting sequencedata over 300ms The capacity of the proposed system isbottlenecked by 10 aircraft

The data transmission is carried out from 300ms to800ms Because the UBLOX decrypts GPS data in 280msdata transmission delays 300ms for synchronization Thedata transmitted for UAV in this section includes coordinatesof current position and next waypoint For the helicopterthe transmitted data will be current position and destinationThese data are both encoded by the CPR Each aircraftbroadcasts its two data packets in a 50ms slot by the sequenceof ID number from the sorting section that is slot one at300mssim350ms until slot eight at 650mssim700ms

CPR converts the data into 35 bits instead of the 45 bitssaving 10 bits per position message It does not transmithigher-order bits in the whole period of the flight Both even-format and odd-format are transmitted firstly to unambigu-ously determine the location of the aircraft Once this processhas been carried out and the higher-order bits are knownonly one kind of format can be selected to determine theposition of the aircraft

With this concept all airborne aircraftwill know the posi-tion of others in this airspace to achieve cooperativemissionsAfter the position sharing is established the proposed conflict

4 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

OUTPUT ID + Slot numberIF ownership slot number = intruder slot number

IF ownership ID priority gt intruder ID priorityOwnership slot number remains

ELSEOwnership slot number shifts to an unused slot

ENDIFENDIF

OUTPUT GPS dataINPUT GPS data of all aircraft

UNTIL shutdown

Algorithm 1 Transceiver architecture

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

Transmit ID only for transmit sequence

0xfa

UAV 040x4b

0x01 0x0f 0x15 0x29 0x3a 0xaa 0xfa

0x3a

0x4b 0xaa

UAV 030x29

0x01 0x0f 0x15 0x3a 0x4b 0xaa

0xfa

0x4b 0xaa 0xfa

UAV 020xfa

0x01 0x0f 0x15 0x29 0x3a

UAV 010x15

0x01 0x0f 0x29

Heli 040xaa

0x01 0x0f 0x15 0x29 0x3a 0x4b

0xaa 0xfa

Heli 030x3a

0x01 0x0f 0x15 0x29 0x4b 0xaa 0xfa

0x4b 0xaa 0xfa

Heli 020x0f

0x01 0x15 0x29 0x3a 0x4b

Heli 010x01

0x0f 0x15 0x29 0x3a

Sorting start Transmission start

Transmit data ID + GPS data (each sector = 50ms)

1000ms0ms 100ms 200ms 300ms 400ms 500ms 600ms 700ms 800ms 900ms

Figure 2 An example of 8-aircraft transmission time chart

detection and collision avoidance algorithm helps to ensurethe safety separation and avoidance of the manned aircraftfrom the intruders

32 Hardware The proposed UAVCDampR transceiverenables cross communications among aircraft in a smallairspace to exchange flight data The proposed transceiversystem is shown in Figure 3 consisting of a MCU GPS mod-ule and a wireless module The adopted MCU STM32f103is a 32-bit flash microcontroller based on the ARM Cortexprocessor MCU handles GPS data input from GPS moduleUBLOX Lea 6 h and communicates to other MCU throughthe wireless module XBee-Pro 900HP The GPS has anerror bubble of 5m GPS accuracy is acceptable for CDampR

performance GPS data reliability and stability on UAV canbe maintained by using high performance antenna

Communication platform varies for different applica-tions The commercial ADS-B uses 1090978MHz [1 6]Because it is a regulated frequency it is difficult to findavailable 1090978MHz radio module in the preliminarydevelopment An available wireless module of XBee-Pro900HP is elected to integrate into the proposed UAVCDampRtransceiver for function capabilityTheXBee-Pro 900HP uses900MHz frequency for data transfer rate up to 200 kbps Itis similar to 1090978MHz system using the same CPR datacoding

Figure 4 shows the proposed hardware for test in acomplete set for the manned aircraft in UAVCDampR per-formance The left part is a transmitter-only (Quasi-ADS-B

Journal of Electrical and Computer Engineering 5

Manned aircraft

MCU MCU

U-bloxGPS

U-bloxGPS

XBee900MHz

XBee900MHz

Unmanned aircraft

Figure 3 UAVCDampR in ADS-B hardware

MCU

XBee

GPS

(a) UAVCDampR ADS-B

Power XBee signal

GPS signal

(b) UAVCDampR display

Figure 4 UAVCDampR transceiver for UAV (left only) and for manned aircraft (all)

OUT) hardware for installing onUAVs while the right part istransceiver (Quasi-ADS-B OUTIN) and display for mannedaircraft For the manned aircraft a microcomputer withLCD display is added with conflict detection and collisionavoidance algorithm The proposed UAVCDampR is designedto suit different software from which proximity advisory(PA) traffic advisory (TA) and resolution advisory (RA) willbe issued

33 Conflict Advisories The UAVCDampR algorithm isinstalled in the microprocessor on the manned aircraftCDampR display is shown in Figure 5 by a COM port setup

Commsetup

TCAS display

ac data

Figure 5 UAVCDampR interface display

6 Journal of Electrical and Computer Engineering

Manned aircraft

Dummy unmanned aircraft

Ground base

Figure 6 Two ultralight aircraft for flight test

to show all received data on the top and traffic informationof TA and RA on the screen Both TA and RA are markedby hemisphere sector with a sense of time to conflict Thereceived data include vicinity aircraft GPS coordinates UTCtime next waypoint of UAV (or destination of mannedaircraft) slot ID and the wireless transmission health of eachaircraft

The CDampR display will have three different advisorieswith visual and audio warnings In PA the screen will remaingray with audio alarm ldquoIntrusion XXX at Y (XXX = az Y =dis)rdquo In TA the screen will change into bright yellow withaudio alert ldquoTraffic Trafficrdquo InRA the displaywill be changedinto bright red with audio warning ldquoTurn rightrdquo All alert andwarning will still show every aircraft on the CDampR display

4 Flight Experiment

To verify the operation functions of the proposed UAVCDampR transceiver system a series of flight tests is carriedout to examine the capability of the flight data transmissionTwo ultralight aircraft are used to carry the UAVCDampRtransceiver in cooperation with a ground control stationas shown in Figure 6 One of the ultralight aircraft acts asa manned aircraft (or as manned helicopter) to performconflict detection and collision avoidance while the otherplays as an UAV to fly from waypoint to waypoint

In the preliminary flight experiments the XBee omnidi-rectional transceiver collects around 97 of the data from theUAVand 100 from its ownGPSAlthough there is a 3dropof data these data spread throughout the whole experimentand all happenedwhen they are separated over 1 km away outof PAdistance In theXBee the possible data loss happens lessthan 2 seconds in continuous flight testThe time delay in theQuasi-ADS-B OUTIN and CDampR computation is examinedwith less than 2 seconds in overall tests When all the testaircraft speeds are less than 120 kmhr the possible separationshrinkage falls within 360 meters before an alert is generatedto the pilotsThis separation is important to TARA design intheCDampR algorithmThe collected data in flight experimentsare used in the CDampR algorithms for further simulation andfunction verification

5 CDampR Algorithm and Validation

This paper is mainly focused on UAVCDampR transceiverhardware design and implementation using Quasi-ADS-BThe following CDampR algorithms are only adopted for flightvalidation in the transponding performance The CDampRmethodologies are not presented in detail

The proposed UAVCDampR system is designed to allowdifferent CDampR algorithms to be validated in real flight testAssume that each algorithm requires different sensors theproposed UAVCDampR transceiver hardware is also capableof integrating sensor information into dynamic resolution [213 15] In CDampR operation when the aircraft detects vicinityflight activities in the near airspace intruder will be identifiedby proximity advisory (PA) where the minor possibility ofconflict is raised When the intrusion approaches into anear range traffic advisory (TA) is pronounced with analert Afterward the intrusion enters close range resolutionadvisory (RA) is generated to give pilot a warning In ICAOPA TA and RA are defined in time to conflict (TTC)markedby 120591 in secondsThe sensitive level (SL) and alarm thresholdsare defined by TTC according to the flight altitude In thisstudy the operating altitude is around 1000 meters aboveground level (AGL) The values are defined as TA = 30 secRA = 20 sec [1]

From CDampR algorithm the manned aircraft (ownership)detects any aircraft within 3 km radius from itself Onceany intrusions are detected the trajectory estimation andprobabilistic grids detection (PGD) are generated If all thetime sectors probability is under the threshold the wholeprocess restarts If any sector probability continues to increaseinto dangerous threshold the time and sector recognition(TSR)will further generate TA alert andRAwarning to pilotsPGD and TSR are explained in brief The CDampR algorithmpseudo code is shown in Algorithm 2

51 Probabilistic Grid Detection (PGD) The PGD algorithmis chosen to implant by the flight path detection for multipleaircraft in the operating airspaceThe PGD is a weighted gridon the probability of the aircraft reaching the same sectorat the same time Each aircraft will generate numerous gridsper second The grids in each second describe the positionprediction of the aircraft in advance The probability gridvalue is based on the predicted coordinate in certain timeinterval Then each grid value is calculated by applying theGaussian Function for 120583 represents the mean of expectationof the distribution (and also its median and mode) and 120590 and1205902 are its standard deviation and variance

119891 (119909) =1

120590radic2120587119890minus(119909minus120583)

221205902

(1)

With the combination of the parameters different prob-abilities can be established based on different conditions andpositions of the aircraft As the estimation progresses intime (meaning the farther ahead the prediction is) the errorincreases with time By adjusting the standard deviation andvariance the correct assumptions can be met

When the aircraftrsquos probability grid is generated each gridwith the same time stamp will be calculated together to get

Journal of Electrical and Computer Engineering 7

Initialization lowast System initialized and GPS lock lowastREPEAT every secondOUTPUT GPS data

INPUT Intruders GPS dataIF Intruder distance to ownership lt3 km

Trajectory estimation constructionEstablish PGDCalculate confliction probabilitiesIF conflict probability gt threshold

TSR CDampR generationTA alertRA warning

ENDIFENDIF

UNTIL shutdown

Algorithm 2 CDampR architecture

5 5 10 20 10 5 5

5 5 15 5 5

5 5 5

(b)

5

5 5

10 5 5

20 10 5

10 5 5

(a)

Figure 7 Probability of conflict in time119873

theweighted probability of collision at the certain time stampFor simplicity only time stamp 119873 is shown in Figure 7 ThePGD algorithm detects the possible intrusion to the mannedaircraft and PA will be pronounced

Afterwards when PA is issued a near field sector recogni-tion algorithm is executed to calculate a safe path to avoidconflict TSR CDampR will continue to check the separationamont intrusion aircraft after PA has been issued The PGDalgorithm pseudo code is shown in Algorithm 3

Figure 8 shows a section of the flight test Solid curvedlines are the real trajectory in record The dotted straightline with asterisk symbol is a straight line estimation of the

trajectory connecting the current point to the waypoint Thedotted line with circle symbol is the estimated trajectoryusing the algorithm discussed in this paper From the figuresthe doted circle trajectory is estimated with closer approachthan the straight asterisk line Although one section of thetrajectories in Figure 8 is deviated from the recorded pointsby 20m their conflict point is still closer to the real conflictpoint than the straight trajectory method

The probability grid is generated and each second proba-bility of conflict is shown as a figure in Figure 9 In the test themaximum single point percentage and the integer percentageare both at the 26th second Although the absolute percentage

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

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International Journal of

Page 4: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

4 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

OUTPUT ID + Slot numberIF ownership slot number = intruder slot number

IF ownership ID priority gt intruder ID priorityOwnership slot number remains

ELSEOwnership slot number shifts to an unused slot

ENDIFENDIF

OUTPUT GPS dataINPUT GPS data of all aircraft

UNTIL shutdown

Algorithm 1 Transceiver architecture

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

TransmitReceive

Transmit ID only for transmit sequence

0xfa

UAV 040x4b

0x01 0x0f 0x15 0x29 0x3a 0xaa 0xfa

0x3a

0x4b 0xaa

UAV 030x29

0x01 0x0f 0x15 0x3a 0x4b 0xaa

0xfa

0x4b 0xaa 0xfa

UAV 020xfa

0x01 0x0f 0x15 0x29 0x3a

UAV 010x15

0x01 0x0f 0x29

Heli 040xaa

0x01 0x0f 0x15 0x29 0x3a 0x4b

0xaa 0xfa

Heli 030x3a

0x01 0x0f 0x15 0x29 0x4b 0xaa 0xfa

0x4b 0xaa 0xfa

Heli 020x0f

0x01 0x15 0x29 0x3a 0x4b

Heli 010x01

0x0f 0x15 0x29 0x3a

Sorting start Transmission start

Transmit data ID + GPS data (each sector = 50ms)

1000ms0ms 100ms 200ms 300ms 400ms 500ms 600ms 700ms 800ms 900ms

Figure 2 An example of 8-aircraft transmission time chart

detection and collision avoidance algorithm helps to ensurethe safety separation and avoidance of the manned aircraftfrom the intruders

32 Hardware The proposed UAVCDampR transceiverenables cross communications among aircraft in a smallairspace to exchange flight data The proposed transceiversystem is shown in Figure 3 consisting of a MCU GPS mod-ule and a wireless module The adopted MCU STM32f103is a 32-bit flash microcontroller based on the ARM Cortexprocessor MCU handles GPS data input from GPS moduleUBLOX Lea 6 h and communicates to other MCU throughthe wireless module XBee-Pro 900HP The GPS has anerror bubble of 5m GPS accuracy is acceptable for CDampR

performance GPS data reliability and stability on UAV canbe maintained by using high performance antenna

Communication platform varies for different applica-tions The commercial ADS-B uses 1090978MHz [1 6]Because it is a regulated frequency it is difficult to findavailable 1090978MHz radio module in the preliminarydevelopment An available wireless module of XBee-Pro900HP is elected to integrate into the proposed UAVCDampRtransceiver for function capabilityTheXBee-Pro 900HP uses900MHz frequency for data transfer rate up to 200 kbps Itis similar to 1090978MHz system using the same CPR datacoding

Figure 4 shows the proposed hardware for test in acomplete set for the manned aircraft in UAVCDampR per-formance The left part is a transmitter-only (Quasi-ADS-B

Journal of Electrical and Computer Engineering 5

Manned aircraft

MCU MCU

U-bloxGPS

U-bloxGPS

XBee900MHz

XBee900MHz

Unmanned aircraft

Figure 3 UAVCDampR in ADS-B hardware

MCU

XBee

GPS

(a) UAVCDampR ADS-B

Power XBee signal

GPS signal

(b) UAVCDampR display

Figure 4 UAVCDampR transceiver for UAV (left only) and for manned aircraft (all)

OUT) hardware for installing onUAVs while the right part istransceiver (Quasi-ADS-B OUTIN) and display for mannedaircraft For the manned aircraft a microcomputer withLCD display is added with conflict detection and collisionavoidance algorithm The proposed UAVCDampR is designedto suit different software from which proximity advisory(PA) traffic advisory (TA) and resolution advisory (RA) willbe issued

33 Conflict Advisories The UAVCDampR algorithm isinstalled in the microprocessor on the manned aircraftCDampR display is shown in Figure 5 by a COM port setup

Commsetup

TCAS display

ac data

Figure 5 UAVCDampR interface display

6 Journal of Electrical and Computer Engineering

Manned aircraft

Dummy unmanned aircraft

Ground base

Figure 6 Two ultralight aircraft for flight test

to show all received data on the top and traffic informationof TA and RA on the screen Both TA and RA are markedby hemisphere sector with a sense of time to conflict Thereceived data include vicinity aircraft GPS coordinates UTCtime next waypoint of UAV (or destination of mannedaircraft) slot ID and the wireless transmission health of eachaircraft

The CDampR display will have three different advisorieswith visual and audio warnings In PA the screen will remaingray with audio alarm ldquoIntrusion XXX at Y (XXX = az Y =dis)rdquo In TA the screen will change into bright yellow withaudio alert ldquoTraffic Trafficrdquo InRA the displaywill be changedinto bright red with audio warning ldquoTurn rightrdquo All alert andwarning will still show every aircraft on the CDampR display

4 Flight Experiment

To verify the operation functions of the proposed UAVCDampR transceiver system a series of flight tests is carriedout to examine the capability of the flight data transmissionTwo ultralight aircraft are used to carry the UAVCDampRtransceiver in cooperation with a ground control stationas shown in Figure 6 One of the ultralight aircraft acts asa manned aircraft (or as manned helicopter) to performconflict detection and collision avoidance while the otherplays as an UAV to fly from waypoint to waypoint

In the preliminary flight experiments the XBee omnidi-rectional transceiver collects around 97 of the data from theUAVand 100 from its ownGPSAlthough there is a 3dropof data these data spread throughout the whole experimentand all happenedwhen they are separated over 1 km away outof PAdistance In theXBee the possible data loss happens lessthan 2 seconds in continuous flight testThe time delay in theQuasi-ADS-B OUTIN and CDampR computation is examinedwith less than 2 seconds in overall tests When all the testaircraft speeds are less than 120 kmhr the possible separationshrinkage falls within 360 meters before an alert is generatedto the pilotsThis separation is important to TARA design intheCDampR algorithmThe collected data in flight experimentsare used in the CDampR algorithms for further simulation andfunction verification

5 CDampR Algorithm and Validation

This paper is mainly focused on UAVCDampR transceiverhardware design and implementation using Quasi-ADS-BThe following CDampR algorithms are only adopted for flightvalidation in the transponding performance The CDampRmethodologies are not presented in detail

The proposed UAVCDampR system is designed to allowdifferent CDampR algorithms to be validated in real flight testAssume that each algorithm requires different sensors theproposed UAVCDampR transceiver hardware is also capableof integrating sensor information into dynamic resolution [213 15] In CDampR operation when the aircraft detects vicinityflight activities in the near airspace intruder will be identifiedby proximity advisory (PA) where the minor possibility ofconflict is raised When the intrusion approaches into anear range traffic advisory (TA) is pronounced with analert Afterward the intrusion enters close range resolutionadvisory (RA) is generated to give pilot a warning In ICAOPA TA and RA are defined in time to conflict (TTC)markedby 120591 in secondsThe sensitive level (SL) and alarm thresholdsare defined by TTC according to the flight altitude In thisstudy the operating altitude is around 1000 meters aboveground level (AGL) The values are defined as TA = 30 secRA = 20 sec [1]

From CDampR algorithm the manned aircraft (ownership)detects any aircraft within 3 km radius from itself Onceany intrusions are detected the trajectory estimation andprobabilistic grids detection (PGD) are generated If all thetime sectors probability is under the threshold the wholeprocess restarts If any sector probability continues to increaseinto dangerous threshold the time and sector recognition(TSR)will further generate TA alert andRAwarning to pilotsPGD and TSR are explained in brief The CDampR algorithmpseudo code is shown in Algorithm 2

51 Probabilistic Grid Detection (PGD) The PGD algorithmis chosen to implant by the flight path detection for multipleaircraft in the operating airspaceThe PGD is a weighted gridon the probability of the aircraft reaching the same sectorat the same time Each aircraft will generate numerous gridsper second The grids in each second describe the positionprediction of the aircraft in advance The probability gridvalue is based on the predicted coordinate in certain timeinterval Then each grid value is calculated by applying theGaussian Function for 120583 represents the mean of expectationof the distribution (and also its median and mode) and 120590 and1205902 are its standard deviation and variance

119891 (119909) =1

120590radic2120587119890minus(119909minus120583)

221205902

(1)

With the combination of the parameters different prob-abilities can be established based on different conditions andpositions of the aircraft As the estimation progresses intime (meaning the farther ahead the prediction is) the errorincreases with time By adjusting the standard deviation andvariance the correct assumptions can be met

When the aircraftrsquos probability grid is generated each gridwith the same time stamp will be calculated together to get

Journal of Electrical and Computer Engineering 7

Initialization lowast System initialized and GPS lock lowastREPEAT every secondOUTPUT GPS data

INPUT Intruders GPS dataIF Intruder distance to ownership lt3 km

Trajectory estimation constructionEstablish PGDCalculate confliction probabilitiesIF conflict probability gt threshold

TSR CDampR generationTA alertRA warning

ENDIFENDIF

UNTIL shutdown

Algorithm 2 CDampR architecture

5 5 10 20 10 5 5

5 5 15 5 5

5 5 5

(b)

5

5 5

10 5 5

20 10 5

10 5 5

(a)

Figure 7 Probability of conflict in time119873

theweighted probability of collision at the certain time stampFor simplicity only time stamp 119873 is shown in Figure 7 ThePGD algorithm detects the possible intrusion to the mannedaircraft and PA will be pronounced

Afterwards when PA is issued a near field sector recogni-tion algorithm is executed to calculate a safe path to avoidconflict TSR CDampR will continue to check the separationamont intrusion aircraft after PA has been issued The PGDalgorithm pseudo code is shown in Algorithm 3

Figure 8 shows a section of the flight test Solid curvedlines are the real trajectory in record The dotted straightline with asterisk symbol is a straight line estimation of the

trajectory connecting the current point to the waypoint Thedotted line with circle symbol is the estimated trajectoryusing the algorithm discussed in this paper From the figuresthe doted circle trajectory is estimated with closer approachthan the straight asterisk line Although one section of thetrajectories in Figure 8 is deviated from the recorded pointsby 20m their conflict point is still closer to the real conflictpoint than the straight trajectory method

The probability grid is generated and each second proba-bility of conflict is shown as a figure in Figure 9 In the test themaximum single point percentage and the integer percentageare both at the 26th second Although the absolute percentage

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 5: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

Journal of Electrical and Computer Engineering 5

Manned aircraft

MCU MCU

U-bloxGPS

U-bloxGPS

XBee900MHz

XBee900MHz

Unmanned aircraft

Figure 3 UAVCDampR in ADS-B hardware

MCU

XBee

GPS

(a) UAVCDampR ADS-B

Power XBee signal

GPS signal

(b) UAVCDampR display

Figure 4 UAVCDampR transceiver for UAV (left only) and for manned aircraft (all)

OUT) hardware for installing onUAVs while the right part istransceiver (Quasi-ADS-B OUTIN) and display for mannedaircraft For the manned aircraft a microcomputer withLCD display is added with conflict detection and collisionavoidance algorithm The proposed UAVCDampR is designedto suit different software from which proximity advisory(PA) traffic advisory (TA) and resolution advisory (RA) willbe issued

33 Conflict Advisories The UAVCDampR algorithm isinstalled in the microprocessor on the manned aircraftCDampR display is shown in Figure 5 by a COM port setup

Commsetup

TCAS display

ac data

Figure 5 UAVCDampR interface display

6 Journal of Electrical and Computer Engineering

Manned aircraft

Dummy unmanned aircraft

Ground base

Figure 6 Two ultralight aircraft for flight test

to show all received data on the top and traffic informationof TA and RA on the screen Both TA and RA are markedby hemisphere sector with a sense of time to conflict Thereceived data include vicinity aircraft GPS coordinates UTCtime next waypoint of UAV (or destination of mannedaircraft) slot ID and the wireless transmission health of eachaircraft

The CDampR display will have three different advisorieswith visual and audio warnings In PA the screen will remaingray with audio alarm ldquoIntrusion XXX at Y (XXX = az Y =dis)rdquo In TA the screen will change into bright yellow withaudio alert ldquoTraffic Trafficrdquo InRA the displaywill be changedinto bright red with audio warning ldquoTurn rightrdquo All alert andwarning will still show every aircraft on the CDampR display

4 Flight Experiment

To verify the operation functions of the proposed UAVCDampR transceiver system a series of flight tests is carriedout to examine the capability of the flight data transmissionTwo ultralight aircraft are used to carry the UAVCDampRtransceiver in cooperation with a ground control stationas shown in Figure 6 One of the ultralight aircraft acts asa manned aircraft (or as manned helicopter) to performconflict detection and collision avoidance while the otherplays as an UAV to fly from waypoint to waypoint

In the preliminary flight experiments the XBee omnidi-rectional transceiver collects around 97 of the data from theUAVand 100 from its ownGPSAlthough there is a 3dropof data these data spread throughout the whole experimentand all happenedwhen they are separated over 1 km away outof PAdistance In theXBee the possible data loss happens lessthan 2 seconds in continuous flight testThe time delay in theQuasi-ADS-B OUTIN and CDampR computation is examinedwith less than 2 seconds in overall tests When all the testaircraft speeds are less than 120 kmhr the possible separationshrinkage falls within 360 meters before an alert is generatedto the pilotsThis separation is important to TARA design intheCDampR algorithmThe collected data in flight experimentsare used in the CDampR algorithms for further simulation andfunction verification

5 CDampR Algorithm and Validation

This paper is mainly focused on UAVCDampR transceiverhardware design and implementation using Quasi-ADS-BThe following CDampR algorithms are only adopted for flightvalidation in the transponding performance The CDampRmethodologies are not presented in detail

The proposed UAVCDampR system is designed to allowdifferent CDampR algorithms to be validated in real flight testAssume that each algorithm requires different sensors theproposed UAVCDampR transceiver hardware is also capableof integrating sensor information into dynamic resolution [213 15] In CDampR operation when the aircraft detects vicinityflight activities in the near airspace intruder will be identifiedby proximity advisory (PA) where the minor possibility ofconflict is raised When the intrusion approaches into anear range traffic advisory (TA) is pronounced with analert Afterward the intrusion enters close range resolutionadvisory (RA) is generated to give pilot a warning In ICAOPA TA and RA are defined in time to conflict (TTC)markedby 120591 in secondsThe sensitive level (SL) and alarm thresholdsare defined by TTC according to the flight altitude In thisstudy the operating altitude is around 1000 meters aboveground level (AGL) The values are defined as TA = 30 secRA = 20 sec [1]

From CDampR algorithm the manned aircraft (ownership)detects any aircraft within 3 km radius from itself Onceany intrusions are detected the trajectory estimation andprobabilistic grids detection (PGD) are generated If all thetime sectors probability is under the threshold the wholeprocess restarts If any sector probability continues to increaseinto dangerous threshold the time and sector recognition(TSR)will further generate TA alert andRAwarning to pilotsPGD and TSR are explained in brief The CDampR algorithmpseudo code is shown in Algorithm 2

51 Probabilistic Grid Detection (PGD) The PGD algorithmis chosen to implant by the flight path detection for multipleaircraft in the operating airspaceThe PGD is a weighted gridon the probability of the aircraft reaching the same sectorat the same time Each aircraft will generate numerous gridsper second The grids in each second describe the positionprediction of the aircraft in advance The probability gridvalue is based on the predicted coordinate in certain timeinterval Then each grid value is calculated by applying theGaussian Function for 120583 represents the mean of expectationof the distribution (and also its median and mode) and 120590 and1205902 are its standard deviation and variance

119891 (119909) =1

120590radic2120587119890minus(119909minus120583)

221205902

(1)

With the combination of the parameters different prob-abilities can be established based on different conditions andpositions of the aircraft As the estimation progresses intime (meaning the farther ahead the prediction is) the errorincreases with time By adjusting the standard deviation andvariance the correct assumptions can be met

When the aircraftrsquos probability grid is generated each gridwith the same time stamp will be calculated together to get

Journal of Electrical and Computer Engineering 7

Initialization lowast System initialized and GPS lock lowastREPEAT every secondOUTPUT GPS data

INPUT Intruders GPS dataIF Intruder distance to ownership lt3 km

Trajectory estimation constructionEstablish PGDCalculate confliction probabilitiesIF conflict probability gt threshold

TSR CDampR generationTA alertRA warning

ENDIFENDIF

UNTIL shutdown

Algorithm 2 CDampR architecture

5 5 10 20 10 5 5

5 5 15 5 5

5 5 5

(b)

5

5 5

10 5 5

20 10 5

10 5 5

(a)

Figure 7 Probability of conflict in time119873

theweighted probability of collision at the certain time stampFor simplicity only time stamp 119873 is shown in Figure 7 ThePGD algorithm detects the possible intrusion to the mannedaircraft and PA will be pronounced

Afterwards when PA is issued a near field sector recogni-tion algorithm is executed to calculate a safe path to avoidconflict TSR CDampR will continue to check the separationamont intrusion aircraft after PA has been issued The PGDalgorithm pseudo code is shown in Algorithm 3

Figure 8 shows a section of the flight test Solid curvedlines are the real trajectory in record The dotted straightline with asterisk symbol is a straight line estimation of the

trajectory connecting the current point to the waypoint Thedotted line with circle symbol is the estimated trajectoryusing the algorithm discussed in this paper From the figuresthe doted circle trajectory is estimated with closer approachthan the straight asterisk line Although one section of thetrajectories in Figure 8 is deviated from the recorded pointsby 20m their conflict point is still closer to the real conflictpoint than the straight trajectory method

The probability grid is generated and each second proba-bility of conflict is shown as a figure in Figure 9 In the test themaximum single point percentage and the integer percentageare both at the 26th second Although the absolute percentage

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 6: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

6 Journal of Electrical and Computer Engineering

Manned aircraft

Dummy unmanned aircraft

Ground base

Figure 6 Two ultralight aircraft for flight test

to show all received data on the top and traffic informationof TA and RA on the screen Both TA and RA are markedby hemisphere sector with a sense of time to conflict Thereceived data include vicinity aircraft GPS coordinates UTCtime next waypoint of UAV (or destination of mannedaircraft) slot ID and the wireless transmission health of eachaircraft

The CDampR display will have three different advisorieswith visual and audio warnings In PA the screen will remaingray with audio alarm ldquoIntrusion XXX at Y (XXX = az Y =dis)rdquo In TA the screen will change into bright yellow withaudio alert ldquoTraffic Trafficrdquo InRA the displaywill be changedinto bright red with audio warning ldquoTurn rightrdquo All alert andwarning will still show every aircraft on the CDampR display

4 Flight Experiment

To verify the operation functions of the proposed UAVCDampR transceiver system a series of flight tests is carriedout to examine the capability of the flight data transmissionTwo ultralight aircraft are used to carry the UAVCDampRtransceiver in cooperation with a ground control stationas shown in Figure 6 One of the ultralight aircraft acts asa manned aircraft (or as manned helicopter) to performconflict detection and collision avoidance while the otherplays as an UAV to fly from waypoint to waypoint

In the preliminary flight experiments the XBee omnidi-rectional transceiver collects around 97 of the data from theUAVand 100 from its ownGPSAlthough there is a 3dropof data these data spread throughout the whole experimentand all happenedwhen they are separated over 1 km away outof PAdistance In theXBee the possible data loss happens lessthan 2 seconds in continuous flight testThe time delay in theQuasi-ADS-B OUTIN and CDampR computation is examinedwith less than 2 seconds in overall tests When all the testaircraft speeds are less than 120 kmhr the possible separationshrinkage falls within 360 meters before an alert is generatedto the pilotsThis separation is important to TARA design intheCDampR algorithmThe collected data in flight experimentsare used in the CDampR algorithms for further simulation andfunction verification

5 CDampR Algorithm and Validation

This paper is mainly focused on UAVCDampR transceiverhardware design and implementation using Quasi-ADS-BThe following CDampR algorithms are only adopted for flightvalidation in the transponding performance The CDampRmethodologies are not presented in detail

The proposed UAVCDampR system is designed to allowdifferent CDampR algorithms to be validated in real flight testAssume that each algorithm requires different sensors theproposed UAVCDampR transceiver hardware is also capableof integrating sensor information into dynamic resolution [213 15] In CDampR operation when the aircraft detects vicinityflight activities in the near airspace intruder will be identifiedby proximity advisory (PA) where the minor possibility ofconflict is raised When the intrusion approaches into anear range traffic advisory (TA) is pronounced with analert Afterward the intrusion enters close range resolutionadvisory (RA) is generated to give pilot a warning In ICAOPA TA and RA are defined in time to conflict (TTC)markedby 120591 in secondsThe sensitive level (SL) and alarm thresholdsare defined by TTC according to the flight altitude In thisstudy the operating altitude is around 1000 meters aboveground level (AGL) The values are defined as TA = 30 secRA = 20 sec [1]

From CDampR algorithm the manned aircraft (ownership)detects any aircraft within 3 km radius from itself Onceany intrusions are detected the trajectory estimation andprobabilistic grids detection (PGD) are generated If all thetime sectors probability is under the threshold the wholeprocess restarts If any sector probability continues to increaseinto dangerous threshold the time and sector recognition(TSR)will further generate TA alert andRAwarning to pilotsPGD and TSR are explained in brief The CDampR algorithmpseudo code is shown in Algorithm 2

51 Probabilistic Grid Detection (PGD) The PGD algorithmis chosen to implant by the flight path detection for multipleaircraft in the operating airspaceThe PGD is a weighted gridon the probability of the aircraft reaching the same sectorat the same time Each aircraft will generate numerous gridsper second The grids in each second describe the positionprediction of the aircraft in advance The probability gridvalue is based on the predicted coordinate in certain timeinterval Then each grid value is calculated by applying theGaussian Function for 120583 represents the mean of expectationof the distribution (and also its median and mode) and 120590 and1205902 are its standard deviation and variance

119891 (119909) =1

120590radic2120587119890minus(119909minus120583)

221205902

(1)

With the combination of the parameters different prob-abilities can be established based on different conditions andpositions of the aircraft As the estimation progresses intime (meaning the farther ahead the prediction is) the errorincreases with time By adjusting the standard deviation andvariance the correct assumptions can be met

When the aircraftrsquos probability grid is generated each gridwith the same time stamp will be calculated together to get

Journal of Electrical and Computer Engineering 7

Initialization lowast System initialized and GPS lock lowastREPEAT every secondOUTPUT GPS data

INPUT Intruders GPS dataIF Intruder distance to ownership lt3 km

Trajectory estimation constructionEstablish PGDCalculate confliction probabilitiesIF conflict probability gt threshold

TSR CDampR generationTA alertRA warning

ENDIFENDIF

UNTIL shutdown

Algorithm 2 CDampR architecture

5 5 10 20 10 5 5

5 5 15 5 5

5 5 5

(b)

5

5 5

10 5 5

20 10 5

10 5 5

(a)

Figure 7 Probability of conflict in time119873

theweighted probability of collision at the certain time stampFor simplicity only time stamp 119873 is shown in Figure 7 ThePGD algorithm detects the possible intrusion to the mannedaircraft and PA will be pronounced

Afterwards when PA is issued a near field sector recogni-tion algorithm is executed to calculate a safe path to avoidconflict TSR CDampR will continue to check the separationamont intrusion aircraft after PA has been issued The PGDalgorithm pseudo code is shown in Algorithm 3

Figure 8 shows a section of the flight test Solid curvedlines are the real trajectory in record The dotted straightline with asterisk symbol is a straight line estimation of the

trajectory connecting the current point to the waypoint Thedotted line with circle symbol is the estimated trajectoryusing the algorithm discussed in this paper From the figuresthe doted circle trajectory is estimated with closer approachthan the straight asterisk line Although one section of thetrajectories in Figure 8 is deviated from the recorded pointsby 20m their conflict point is still closer to the real conflictpoint than the straight trajectory method

The probability grid is generated and each second proba-bility of conflict is shown as a figure in Figure 9 In the test themaximum single point percentage and the integer percentageare both at the 26th second Although the absolute percentage

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 7: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

Journal of Electrical and Computer Engineering 7

Initialization lowast System initialized and GPS lock lowastREPEAT every secondOUTPUT GPS data

INPUT Intruders GPS dataIF Intruder distance to ownership lt3 km

Trajectory estimation constructionEstablish PGDCalculate confliction probabilitiesIF conflict probability gt threshold

TSR CDampR generationTA alertRA warning

ENDIFENDIF

UNTIL shutdown

Algorithm 2 CDampR architecture

5 5 10 20 10 5 5

5 5 15 5 5

5 5 5

(b)

5

5 5

10 5 5

20 10 5

10 5 5

(a)

Figure 7 Probability of conflict in time119873

theweighted probability of collision at the certain time stampFor simplicity only time stamp 119873 is shown in Figure 7 ThePGD algorithm detects the possible intrusion to the mannedaircraft and PA will be pronounced

Afterwards when PA is issued a near field sector recogni-tion algorithm is executed to calculate a safe path to avoidconflict TSR CDampR will continue to check the separationamont intrusion aircraft after PA has been issued The PGDalgorithm pseudo code is shown in Algorithm 3

Figure 8 shows a section of the flight test Solid curvedlines are the real trajectory in record The dotted straightline with asterisk symbol is a straight line estimation of the

trajectory connecting the current point to the waypoint Thedotted line with circle symbol is the estimated trajectoryusing the algorithm discussed in this paper From the figuresthe doted circle trajectory is estimated with closer approachthan the straight asterisk line Although one section of thetrajectories in Figure 8 is deviated from the recorded pointsby 20m their conflict point is still closer to the real conflictpoint than the straight trajectory method

The probability grid is generated and each second proba-bility of conflict is shown as a figure in Figure 9 In the test themaximum single point percentage and the integer percentageare both at the 26th second Although the absolute percentage

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 8: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

8 Journal of Electrical and Computer Engineering

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataPredict future trajectory and position (next 25 seconds = 25 grids)Overlap of each aircraft same time stamp gridsIF A grid block value gt threshold value

Mark block as dangerous zoneIssue PATSR CDampR execute

ENDIFUNTIL Shutdown

Algorithm 3 PGD CDampR architecture

minus600 minus400 minus200 0 200 400 600 800minus200

0

200

400

600

800

1000

1200

X direction (m)

Y d

irect

ion

(m)

Real path heliPGD estimated heliReal path UAV

PGD estimated UAVStraight estimated heliStraight estimated UAV

Current (helicopter)

WaypointCurrent (UAV)

Check point

Figure 8 Test trajectory

0 5 10 15 20 25 30 35 400

05

1

15

2

25

3

35

4

45

(s)

()

times10minus5

(a) Test max percentage

0 5 10 15 20 25 30 35 400

05

1

15

(s)

()

times10minus3

(b) Test percentage integer

Figure 9 Graph of probability of conflict

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 9: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

Journal of Electrical and Computer Engineering 9

Initialization lowast System initialized and GPS lock lowastREPEAT every second

INPUT Intruders GPS dataIF PGD block value gt threshold or intruder distance from ownership lt1 km

Generate sector of each aircraftCalculate overlap area of each sectorIF Overlap area gt TSR threshold

Calculate right turn rateRA issue

ENDIFENDIF

UNTIL Shutdown

Algorithm 4 TSR CDampR architecture

in Figure 9 is very small the relative percentage increment isenough to exceed the threshold of the system and trigger andissue PA From Figure 8 the recorded conflict point is alsoat the 26thsim27st secondThe simulation using real flight datashows that with the combination of the trajectory estimationand probability grid an accurate conflict prediction can bepredicted

52 Time and Sector Recognition (TSR) The time and sectorrecognition (TSR) algorithm [16] generates a sector shapedarea in the tangent direction of the flight path If any intruderrsquossector area overlaps the ownership sector area to a certainratio TA and RA will be pronounced following its resolutioncalculation The avoidance path is calculated by the possibleturning angle 120593 to decrease of overlapping ratio at mostWithsome restrict parameters by turning radius in constant speeda safe right turn trajectory can be plotted to assist the pilot forconducting conflict avoidance [14 15]

TSR is triggered in two conditions (1) PGD exceedsthreshold and (2) intruder aircraft is less than 1 km fromownership When TSR is executed the CDampR message willgenerate time and sector recognition pattern with intrudersrsquolocation and heading as shown in Figure 10 The proposedTSR algorithm will identify the intruder UAVs or mannedaircraft and apply appropriate separation Conflict detectionand collision avoidance from manned aircraft to other air-craft especially the UAVs will be shown in Figure 11

The adopted TSR algorithm defines maneuvering anglechange for UAV with 30 degrees and for the manned heli-copter in 45 degrees as shown in Figure 11 Based on this 2Dspatial relation conflict detection TA and collision avoidanceRA will be published on the proposed UAVCDampR display asshown in Figure 5

Using the actual flight test data by ultralight aircraftFigure 12 shows the flight path data collected from the ultra-light aircraft flight testsThe red dots represent the waypointsfor the UAVThe green and blue lines are the trajectory of themanned helicopter and UAV correspondingly The red star(995333) marks the position to pronounce TAThe TSR algorithmpseudo code is shown in Algorithm 4

When RA is issued in Figure 13 the display turns tored with audio warning Sector recognition algorithm will

Turn angle = 120593

120593

Figure 10 The time and sector recognition algorithm

then calculate the best right turn trajectory to escape inFigure 14(a) The conflict resolution suggests the mannedhelicopter to increase the distance from the intruder andavoid conflict by making right turn The separation of twoaircraft is calculated in Figure 14(b)

The flight tests demonstrate the effectiveness of theproposedUAVCDampR transceiverworkingwith two differentalgorithms for conflict detection and collision avoidanceamong UAVs to GA

53 UAV Crash Search and Mountain Hiker Search Theproposed UAVCDampR hardware can also be applied tomissing UAS search once crashed Since the 900MHz XBee-Pro 900HP is independent fromautopilot system it continuesto broadcast position data once crashed

Likewise the proposed UAVCDampR hardware carriedan additional test from mountain hikers It can be used tosend their SOS by the proposed CDampR transponder Sincethe mountain hikers are staying at a fixed position theCDampR ADS-IN in the rescue helicopter can easily locatethe transponder signals and call for rescue Two CDampRtransponders are used at the same time during flight tests Itsapplication to mountain hiker can be verified in byproduct

The hiker SOS transponder will be broadcastingrandomly at the emergency slot of the whole second

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 10: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

10 Journal of Electrical and Computer Engineering

25 s

25 s

15 s

45∘

45∘

30∘

30∘

(a)

25 s

25 s

15 s

45∘

45∘

30∘30∘

(b)

Figure 11 Advisories (a) TA and (b) RA by TSR algorithm

120

618

120

619

120

62

120

621

120

622

120

623

120

624

120

625

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

Waypoint

Waypoint

UAV

Figure 12 Flight test path of two conflicting aircraft

(800mssim1000ms)These slots are unused message slots usedfor emergency and future expansion usage Because theseslots are originally free with no message flow no slot sortingis required

6 Conclusion

In this paper a UAVCDampR transceiver hardware usingQuasi-ADS-B is designed and fabricated for tests Based onthe FAA CDampR specifications 1090978MHz frequency isdefined [1] In the proposed system 900MHz XBee wirelessmodule is adopted for implementation and preliminaryverification The transceiver carries ADS-B format in CDampRoperation into 10 km coverage range By careful arrangementthe selected TDMA performance can avoid time conflict and

Figure 13 Display of intrusion on the manned helicopter when RAis issued

resolve automatic time slot adjustment to split out data over-lappingThe designed transceiver hardware of 500 g of weightwith 6-hour battery lasting in Figure 4(a) is quite suitablefor any kind of UAVs The same design for manned aircraftincluding a man-machine interface to display the TARAsituation awareness is adequate for practical applications

The proposed wireless transceiver for UAVCDampR hasbeen successfully verified by a series of flight tests usingmultiple ultralight aircraft Actual airborne flight data are col-lected from the participating ultralight aircraft as well as theground control stationThemanned aircraft receives effectiveintrusion message to activate its embedded algorithm forconflict detection and collision avoidance Several flight testdata have successfully supported the proposed mechanismfor UAVCDampR using Quasi-ADS-B communication

The proposed UAVCDampR transceiver is an open hard-ware system suitable for different CDampR algorithms Inthe tests two CDampR algorithms are adopted into CDampRperformance verification The results strongly validate theeffectiveness of the proposedUAVCDampR transceiver designThe XBee transceiver within reasonable data loss plays anefficient media for ADS-B performance in high efficiencyhigh reliability and low cost in real world implementation

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 11: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

Journal of Electrical and Computer Engineering 11

120617 120618 120619 12062 120621 120622 120623

22752

22753

22754

22755

22756

22757

Longitude

Latit

ude

UAVHelicopter

Helicopter

UAV enters the RA region

Helicopter changes path

UAV

RA

(a) Trajectory of UAV and manned aircraft

0 5 10 15250

300

350

400

450

500

550

600

650

700

750

Time

Dist

ance

(m)

ResolutionNo resolution

(b) Separation between two aircraft

Figure 14 Avoidance trajectory of manned aircraft to UAV

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

Thiswork is supported by theNational ScienceCouncil underContracts NSC101-2218-E-006-002 and NSC102-2221-E-006-81-MY3

References

[1] Federal Aviation Administration Introduction to CDampR IIVersion 71 U S Department of Transportation 2011

[2] J E Olszta andW A Olson ldquoA comparative study of air carrierand business jet TCAS RA experiencesrdquo in Proceedings of the29th Digital Avionics Systems Conference (DASC rsquo10) pp 4A1-1ndash4A1-10 IEEE Salt Lake City Utah USA October 2010

[3] C E Lin and Y-Y Wu ldquoCollision avoidance solution for low-altitude flightsrdquo Proceedings of the Institution of MechanicalEngineers Part G Journal of Aerospace Engineering vol 225 no7 pp 779ndash790 2011

[4] G Xiao Y Xu C Dai Z Jing and J Wu ldquoA selectionalgorithm for conflict aircrafts and performance analysis basedon ADS-Brdquo in Proceedings of the 30th Digital Avionics SystemsConference pp D31ndashD36 October 2011

[5] C-E Lin C-C Li S-F Tai C-F Tsai S-C Chiang and T-C Chen ldquoCollision avoidance system for low altitude flightsrdquoJournal of Aeronautics Astronautics and Aviation Series A vol41 no 3 pp 143ndash156 2009

[6] A Marshall ldquoAn expanded description of the CPR algorithmrdquoTech Rep ADS-B 1090 MOPS Rev B 1090-WP29-07 RTCASpecial Committee 186 Working Group 3 2009

[7] DMcCallie J Butts andRMills ldquoSecurity analysis of theADS-B implementation in the next generation air transportation sys-temrdquo International Journal of Critical Infrastructure Protectionvol 4 no 2 pp 78ndash87 2011

[8] H Choi Y Kim and I Hwang ldquoVision-based reactive collisionavoidance algorithm for unmanned aerial vehiclerdquo in Proceed-ings of the AIAA Guidance Navigation and Control ConferencePortland Ore USA August 2011

[9] B M Albaker and N A Rahim ldquoUnmanned aircraft collisiondetection and resolution concept and surveyrdquo in Proceedings ofthe 5th IEEE Conference on Industrial Electronics and Applica-tions (ICIEA rsquo10) pp 248ndash253 June 2010

[10] M Melega S Lazarus and A Savvaris ldquoAutonomous colli-sion avoidance based on aircraft performances estimationrdquo inProceedings of the IEEEAIAA 30th Digital Avionics SystemsConference (DASC rsquo11) pp 5B4-1ndash5B4-15 Seattle Wash USAOctober 2011

[11] J Kuchar and L Yang ldquoSurvey of conflict detection andresolution modeling methodsrdquo in Proceedings of the AIAAGuidance Navigation Control Conference pp 1388ndash1397 NewOrleans La USA August 1997

[12] M S Huang and R M Narayanan ldquoNon-cooperative collisionavoidance concept for unmanned aircraft system using satellite-based radar and radio communicationrdquo in Proceedings of the30th Digital Avionics System Conference Seattle Wash USAOctober 2011

[13] C-P Lai Y-J Ren and C Lin ldquoADS-B based collision avoid-ance radar for unmanned aerial vehiclesrdquo in Proceedings of theIEEE MTT-S International Microwave Symposium Digest (MTTrsquo09) pp 85ndash88 Boston Mass USA June 2009

[14] R Chamlou ldquoDesign principles and algorithm development fortwo types of nextgen airborne conflict detection and collisionavoidancerdquo in Proceedings of the Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo10) May 2010

[15] S Ueno T Higuchi andK Iwama ldquoCollision avoidance controllaw of a helicopter using information amount feedbackrdquo in

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 12: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

12 Journal of Electrical and Computer Engineering

Proceedings of the SICE Annual Conference pp 2118ndash2121Tokyo Japan August 2008

[16] C E Lin Y H Lai and F J Lee ldquoUAV collision avoidanceusing sector recognition in cooperative mission to helicoptersrdquoin Proceedings of the IEEEAIAA Integrated CommunicationsNavigation and Surveillance Conference (ICNS rsquo14) pp F1-1ndashF1-9 Herndon Va USA April 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Page 13: Research Article Quasi-ADS-B Based UAV Conflict ...downloads.hindawi.com/journals/jece/2015/297859.pdfResearch Article Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of