a multistatic microwave radar sensor for short range anticollision warning

2270IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 49, NO. 6, NOVEMBER 2000

A Multistatic Microwave Radar Sensor for Short Range Anticollision Warning

Luigi Giubbolini

Abstract An adequate radar technology for the detection and localization of obstacles before, behind and on the sides of a moving car is of primary importance to realize on-board devices able to perform different tasks such as parking, stop and go, and pre alarm of the frontal air-bags. In these situations, the radar must acquire the position of the obstacles located at short distances from the car. This acquisition must be carried out with high radial and angular resolution; the former needs large radio frequency bandwidth, the latter requires large antennas and this means that the investigation area of the radar is certainly in the near field of the antenna. It is for this reason that traditional anti-collision systems based on phase array antennas prove to be unsuited to perform these tasks in the short range [7]. The solution that we are proposing is based on sev-eral independent microwave radar sensors with wide angle of view connected to a central processing unit able to define the position and the relative velocity of the nearest obstacles. This prototype works in the 13.414 GHz frequency range at low power (16 dBm eirp) in accordance with the most recent ETSI and CEPT/ERC Recommendations and it has been realized with microstrip tech-nology so that thanks to its reduced size each device can be em-bedded easily in a bumper.

Index Terms Image reconstruction, microwave circuits, radar imaging.

at a time and, through a triangulation algorithm, the system finds the () position of the nearest obstacles in each area.

Fig. 2 shows the prototype of a radar sensor and where the sensors are placed in the vehicle: four sensors are mounted in the Front () and four in the Back (). The larger the number of sensors, the higher the degree of accuracy in the localization of the obstacles and by separating the sensors with a step of 0.3 meter the specifications defined in Fig. 1 are met.

The proposed system is based on microwave FMCW radar sensors and a PC-DSP system. The working frequency range is between 13.4 and 14 GHz, 40 mW of maximum radiated peak power according to the CEPT Recommendation T/R 60-01 and the ETSI 300 440 for low power radio-localization equipment for detecting movement and radio-determination.

Low cost and reduced size of the whole system are of para-mount importance, for this reason we have used hybrid mi-crostrip technology and large scale components to realize the FMCW transceiver (size of mm), and a central digital signal processor (DSP) which performs, round robin for each side of the vehicle, the necessary computation.

I. INTRODUCTIONII. SYSTEM ARCHITECTURE

SAFETY in driving could be increased significantly with the assistance of a device able to provide the distance and the relative velocity of the nearest obstacles and it could be useful also in other situations such as parking, stop-and-go and pre-

alarm of the frontal air-bags [1], [2].

To acquire the data necessary to perform these tasks in every weather condition a reliable localization of the obstacles before and behind the vehicle must be carried out. In Fig. 1 are shown the investigated space and the specifications of the range of the antenna and the resolution required.

The peculiarity of this application in the short range is the wide basis of the investigated areas: a characteristic that, to-gether with the high angular resolution required, cant be man-aged successfully by the usual phase array techniques. In fact high accuracy of the angular position is obtained using large antennas so that the investigation area falls in their near field.

To measure the position () of the nearest obstacles located in each one of the four areas, we propose a distributed solution based on several independent microwave radar sensors placed round the vehicle. These sensors are turned on in sequence one

Manuscript received January 27, 1997; revised December 4, 1998 and November 3, 1999.

The author is with CNR-CESPA, Dipartimento di Elettronica, Politecnico di Torino, 10129 Torino, Italy (e-mail: [email protected]).Publisher Item Identifier S 0018-9545(00)11224-1. The architecture of the whole system is reported in Fig. 3; the sensors and the computer are connected by RS-232 and supplied by 12 V, in this way a thin and easy interconnection is realized. Through serial interconnection the DSP performs the following cycle in sequence on each radar sensor: starting of the measure-ment cycle, reception of the sampled intermediate frequency signal and processing of the spectrum analysis to evaluate the distance of the nearest objects from the selected sensor. At the end of a complete round robin cycle the DSP calculates the position () of the nearest obstacles on each side of the vehicle and sends these data to the display or to the cruise control.

III. MICROWAVE RADAR SENSOR

Each radar sensor is realized on four different layers (see Fig. 4): the FMCW transceiver (on layer 1), the Intermediate Frequency subsystem (IF on layer 2), the automatic gain con-trolled amplifier (AGC on layer 3) and a microcontroller (layer 4). On layer 2 the dc bias network of the HEMPTs are also implemented. The front end is realized with hybrid technology (Diclad 527, mils; ) using 8 low-cost HEMPT (Nec NE32484A); the VCO is able to sweep on the range GHz with 0 dBm output power. The swept signal supplies, by means of a power divider, the HEMPT T3 (mixer) and the couple T6T7 (transmitter power amplifier). A two-stage (T1

00189545/00$10.00 2000 IEEEGIUBBOLINI: MULTISTATIC MICROWAVE RADAR SENSOR2271

Fig. 1. View from the top of the vehicle and specifications for the localization process.

Fig. 2. Prototype of a radar sensor (88235 250 mm); view of the two aperture antennas; scheme for the embedding of the sensors inside the bumper (view from the top).

T2) low noise amplifier ( dB) amplifies the re-ceived signal from the Rx antenna and supplies the radio fre-quency (RF) port of the mixer. Fig. 5 shows the picture of the layers #1 and #2.

The two-stage amplifier (T6 T7) supplies the transmitting antenna with 10 dBm and isolates by 45 dB the mixer T3 fromthe transmitting antenna.

The two antennas are microstrip-fed aperture ( mm)

in order to obtain a gain of 5.7 dB with half-power angles in the horizontal and vertical planes of and required by the application. Fig. 2 shows the two aperture antennas and Fig. 6 their radiation diagrams.

The intermediate frequency signal, output of the mixer, is am-plified at first by a two-stage amplifier (2 Minicircuit MAR 6 on layer 2) and then by a digitally controlled amplifier; after that the IF signal is sampled (ADC Maxim MAX153, 8 bit at 1 Ms/s, on layer 3) and acquired by the microcontroller (Motorola HC11 on layer 4) and finally transferred to the remote DSP system. The local microcontroller controls the gain of the AGC IF am-plifier (using the multiplier Analog Device AD834 on layer 3), generates the predistorted modulation waveform (using the Na-tional DAC0832, 8 bit 1 Msps, on layer 4) to have a linear chirp transmitted signal, manages the communication with the remote system and switches on and off the transceiver.

The front-end overall performances allow a 35-dB S/N of the IF signal in the worst case, that is with an obstacle of 1 m radar cross section located at 5 m in front of the antenna. In this way the degree of accuracy in the measurement of the radial distance is of about one centimeter thanks to the large bandwidth used (bandwidth 600 MHz, resolution 0.25 m) and to the processing.

IV. DIGITAL PROCESSING

The processing system enables and queries, in round robin, all the radar sensors and acquires the sampled intermediate fre-quency signals (each IF sampled signal is packed in an 80-byte array). Fig. 7 shows the block diagram and the picture of the fast Fourier transform (FFT) board; the system is realized by means of two cooperating processors, the first one (Intel 80 486) man-ages the communication with the radar sensors and passes the IF streams to the second (TRW TMC2310), which is specialized in very fast windowing and FFT processing (windowing zero padding on 1024 byte in 612 s).

The result of the spectral analysis is the reflectivity diagram RD() of the scenario seen by the radar sensor [3], [5]:

(1)

where

convolution product;

Fourier operator;

and radial distance and radial velocity between the

antenna and the scattering objects;

carrier wavelength (2.2 centimeter);

system resolution (25 centimeter);


Fig. 3. System architecture.

Fig. 4. Block diagram of the microwave (13 4 4 14 GHz) FMCW Radar Sensor.

transmitted signal power (10 dBm);

radiation loss;

total gain of the system;

IF intermediate signal in time;

modulation period (80 s);

windowing function;

radial reflectivity of the observed scenery;

point spread function of the whole system (4)

(2)

The i80486 processes the reflectivity diagram RD() in order to verify the presence of any obstacles and to extract their ra-dial distance together with their echo intensity; in this way each sensor compiles its own list of the obstacles which are detected in the locations of the peaks in the reflectivity diagram RD [6].

At the end of the round robin cycle a list of the obstacles for each radar sensor is available and the localization process can start to evaluate, for each side of the vehicle, the presence of at least one obstacle and, in this case, to perform a triangulation

process to calculate the () of its position and show it on thedisplay; a complete cycle is performed any 20 ms.The localization processfinds the () positions of the

obstacles present on each side of the vehicle by triangulation on their radial distances between the first and the last sensor of theside considered (using the first list of obstaclesand the lastone, whereis the number of sensors on the vehicle

side). To do this in a proper way one needs to know the correct association between the two sets of radial distances: if on one side of the vehicle there are present obstacles, the system has to find the right association among possible ones. This task is carried out using the obstacle lists of the other sensors (intermediate sensors ) to build an association matrix (AM) of merit figures of the possible associations (AM of elements). For any association () (obstacle of the

and obstacleof the) the position of the hypotheticalobstacle () is evaluated by intersecting the two circleshaving as radius the two radial distances considered [and] and centers located on the first and last sensor.

After that, the expected radial distances from each intermediate sensor ( ) are evaluated and used to calculate the merit figure of the actual association as the sum of the squared relative errors between the expected radial distances and the actual closest ones [ with such as

GIUBBOLINI: MULTISTATIC MICROWAVE RADAR SENSOR2273

(a)

(a)

(b)

Fig. 6. Protoype radiation diagrams (vertical and horizontal planes at 13.4, 13.7, and 14.0 GHz).

(b)

Fig. 5. Photos of the prototype radar sensor: microwave and dc layers.

is minimum]:

(3)

By analyzing the association matrix the obstacle () po-sitions are obtained. This process searches for the minimum values in every th row of AM: the two radial distances asso-ciated with this AM element permit to obtain, by triangulation, the () position of the th obstacle.

obstacle configurations with discrete and distributed objects (in relation to the spatial resolution of the radar of 25 cm). These configurations have been chosen to test the robustness of the tri-angulation process in solving operative ambiguities and to esti-mate the precision while localizing the obstacles.

In Fig. 8 a test set-up with the associated screen output is shown. It is possible to see the correspondence between the spa-tial position of the obstacles () and the displayed output.

The characterization of the accuracy of the whole system has been obtained with one microwave rear reflector located in dif-ferent positions in the frontal operative range (see Fig. 1) on a grid of 0.5 m step on both and axis. Fig. 9 shows the lo-calization error as the mean value on 100 acquisitions of the error between the measured position () and the actual one ():

(4)

V. SYSTEM CHARACTERIZATION

The whole system has been characterized in laboratory by

using four radar sensors and analyzing their IF signals in several is always less than 1 cm.


Fig. 8. Test setup example and associated display output.

(a)

Fig. 9. System accuracy with one obstacle in the investigated area.

(b)

Fig. 7. Block diagram of the DSP system and photo of the FFT board.

A set of characterizations with a second disturbing target has shown that until the distance between two obstacles is greater than the resolution of the radar (25 cm) the accuracy in local-izing the obstacles is kept under 1 centimeter on both of them. Similar considerations are possible for more discrete targets.

The system has been tested also for the robustness of the lo-calization process. All the tests with discrete obstacles separated by a distance greater than the radar resolution have been passed without ambiguity by the triangulation process. Special cases have been found when the first and the last sensor did not see the same number of obstacles; this is possible for one of the fol-lowing reasons:

the areas investigated by the two sensors did not overlap exactly,

the obstacles are so close to each other that one or both the sensors are unable to resolve them,

one distributed obstacle (larger than the spatial resolu-tion) is present in the scenario.

In all these cases, the association matrix is rectangular rather than square, and fewer obstacles than the real number of scat-tering centers have been detected.

The first situation occurs in the lateral sides of the investigated area and can be controlled by accurate positioning of the sensor orientations.

In the second situation the system gives the location of two or more merged scattering centers with a lower accuracy. Finally, in case of a distributed obstacle, the system can give only its radial minimum distance from the vehicle.

VI. CONCLUSION

A distributed microwave radar sensor for the short-range an-ticollision warning has been presented. The proposed system is realized by several FMCW microwave transceivers located all around the vehicle and a central DSP system. The system shows on a display, every 20 ms, the () position of all the obstacles present around the vehicle in the short range (until 3 meter).

The operative frequency range and the radiated power follow the most recent International Recommendations and it is pos-sible to classify the system as a low power device for radio-de-termination. The system has been realized using consumer hy-brid technology.

The characterization of the system has shown a degree of accuracy higher than 1 cm on the whole operative range. The process implemented by the system works properly without any ambiguities on the nearest obstacle, on the whole oper-ative range when only discrete obstacles are present. In case the nearest obstacle is a distributed obstacle (for example a guardrail on the right-hand side of the car), the system can give only its minimum distance.

This feature will permit the implementation of many func-tions such as the parking aids, the stop-and-go and the pre-alarm of the air bags.

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https://www.academia.edu/7634142/A_multistatic_microwave_radar_sensor_for_short_range_anticollision_warning

Luigi Giubbolini was born in Imperia, Italy, in 1963. He received the Dr. Eng. degree in electronics from the Polytechnic of Turin, Turin, Italy, in 1989.

Since 1989, he has done research in the Depart-ment of Electronics of the Polytechnic of Turin on radar imaging for automotive applications in the EEC PROMETHEUS project. His research interests con-cern the microwave imaging techniques, microstrip circuits and digital signal processing. He has worked as a Research Consultant for Magneti Marelli Com-pany, where he was involved in the developing of a

Lidar anticollision system for vehicles. Presently, he is with the official staff of the Antennas and Propagation Study Center of the Italian Research National Council, Turin, Italy, as Researcher, where he takes part in several EC and Italian research projects.