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GIS and GPS for Railroad Environment
Presented by:
Jim Rome
May 15, 2007
Rome Navigation Innovations Inc27 Old County Rd.
Gloucester, MA [email protected]
H. James Rome, President978-281-5623
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Why is Track Navigation different from most any other Navigation
• It is mostly ONE DIMENSIONAL, Linear referencing!
• Curves are mild , linear accelerations are mild.
• A Map (if we have one) tells us everything except where along the track we are. We simply have to pin down that ONE quantity.
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Its Sooo.. Easy!
• Compare the Issue an aircraft pilot in flying and landing virtually blind.
• Track Navigation is like shooting fish in a Barrel
• Don’t Shoot yourself in the Foot!
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What Follows
• Preliminaries
• Principles of GPS ( very very short course)
• Issues of Rail Navigation
• Data Integration and Handling– For Navigation– Navigation with Measured Data
• The Railroad Receiver
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Definitions
• Purpose of GIS and Navigation: Locate something so you can find it again
• Accuracy Required : Good enough to complete your “Mission”
• Methods of Navigation on the Rails :– Dark Ages.. Locate by visual clues– Until Recently Locate by ft from Milepost
(Requirements are often driven by capability)– NOW GPS…Adds a whole new Dimension of the One
Dimensional Problem
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Comparing Apples to Prunes
• Never Try to Land a plane where a train navigates• A Plane for the most part can go any direction at
any time and hardly ever stops. A Train for the most part goes forward and backward and stops all the time.
• GPS on a plane is generally available. On a train, only if we are lucky.
• On a train we Independently can find distance along the ground traveled to great precision. Not so on a plane.
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Accuracy Integrity Reliability
• Accuracy: RMS error 95 % limit of error, etc.
• Integrity: know when to trust! Know when readings are false! ( Can cost lots of money when you don’t)
• Reliability what fraction of the time ( space) is it working?
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Why Know the Principles of Operations of GPS
• So you know where it won’t work and where it might Shoot you In the foot!
• Know what complements GPS.
• Know what you might do with GPS.. And What you can’t . That is, understand issues.
• Next is a very brief summary.
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sat. time
Observed Time
sat. time
Observed Time
Observed Time Observed
Time
sat. time
sat. time
Antenna /Receiver Compute Position
Sat Positions
Other Parameters
Vehicle Position
Principles of GPS Operation
DifferentialCorrections R1
R2
R3 R4
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NAVIGATION SOLUTION IF WE HAD 4 TIME MEASUREMENTS T1, T2,T3,T4
AND FOUR UNKNOWNS: X,Y,Z, Can Find position, X,Y,Z RANGE TO VEHICLE
T1= [(Xs1-X)2+(Ys1-Y)2+(ZS1-Z)2] 1/2 /c + n1
T2= [(Xs2-X)2+(Ys2-Y)2+(ZS2-Z)2] 1/2 /c + n2
T3= [(Xs3-X)2+(Ys3-Y)2+(ZS3-Z)2] 1/2 /c + n3
T4= [(Xs4-X)2+(Ys4-Y)2+(ZS4-Z)2] 1/2 /c + n4
Speed of Light
Synch Error
Noise
X orbit Pos. sat #2
Transmission Delay Time
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ADDITIONAL FEATURES IN NAVIGATION SOLUTION
THERE ARE USUALLY MORE MEASUREMENTS: T5= [(Xs5-X)2+(Ys5-Y)2+(ZS5-Z)2] 1/2 /c + n5
T6= [(Xs6-X)2+(Ys6-Y)2+(ZS6-Z)2] 1/2 /c + n6
USED FOR SELF CHECK AND IMPROVING ACCURACY• Least Squares Estimation•Integrity and Exclusion
1,2,3,4
1,2,3,5
1,2,4,5
1,3,4,5
2,3,4,5
1,3,4,6
Least Squares Estimate: HDOP*RMS Range=Nav. Error
Integrity Region
Outlier, Sat6 Bad?
One SolutionUsing 4 Sats.
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ADDITIONAL FEATURES IN NAVIGATION SOLUTION
T3= [(Xs3-Csx3 -X)2+(Ys3 -Csy3 -Y)2+(ZS3 -Csz3 -Z)2] 1/2 /c – EP3+ n3
Differential Corrections:
Orbit Corrections Propagation Corrections
Types of Differential Corrections:VBS satellite (OmniStar) ~3 ft (they say 1ft) (800/yr)NDGPS (Free.. If available) 3-6 ftWASS (Satellite, Free) 10 ft.(Omnistar) 1500 HP Satellite 5 INCHES! ( 1500/yr)
But They only work when there is GPS!
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Types of Receivers• Hand Held ( WASS enabled) accuracy ~ 30 ft (10 ft)
<$300• Computer Cards .. Right in your laptop Accuracy 30 ft-~
2 ft .. With cycle matching and Good differential• Receivers with cycle matching… 2 ft with good
differential… better for “local corrections”• Dual Frequency ( gets rid of Ionospheric errors) Receivers
have cycle matching, with base station positioning to cm or mm. ( Overkill?)
• Inertial Aiding… probably won’t benefit railroad users, but fast recovery from outage will.
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Track Beds Are Not Designed for GPS Visibility -Issues
HeadingOdometer
Blockage of Sats./DifferentialMulti-pathTotal WipeoutError in Differential
Dead Reckoning is Important
Issues of GPS and Train Navigaton
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So What does One Dimension Buy US?
• Linear Referenced track Map .. It will fit on a memory stick
• If only we had a perfect Odometer, we would only need GPS occasionally
• If only we didn’t have to use Figure skates to play Hockey….?– Example Next that could probably reduce the
unavailability of GPS by a factor of 3
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Line of Track
Solution: Two Satellites and a Track Map
This is a great Concept,Easily Implemented.But Don’t expect a GPSManufacturer to offer oneSoon
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Why is this so special?
• If any satellites in view, they will be fore and aft, and above .. Where they would be most effective!
• No Receiver Does this because nobody with clout asked!( That is it is a feature that could be burned into a receiver chip)
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Data IntegrationKalman Filter Software
• Kalman Filter software usually uses GPS and aiding data . Example:odometer , heading reference, and/ or inertial system
– Provides smooth outputs between fresh GPS samples
– Can Provide Position Solutions ( albeit with growing errors) during GPS outages.
– Can slightly improve accuracy over just Raw GPS
– Can Provide good heading information
– Can Reject bad data (A Key Feature )
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Kaman Filter Should Also Provide:
• Distance Along track• Heading• Quality of Solution ( Combination of Quality of
Raw data, Expected error, Number of rejections) – Used to Tie Down Distance , assess precision of
solution
• If not, they are selling you a Figure skate for Hockey!
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Comments on Integration Components in Kalman Filtering
• Aircraft Grade GPS Inertial System would provide >100 ft along track accuracy extrapolating 1 mile at 60 Mph with no GPS.
• GPS/Odometer/ heading reference (Could be curvature from Geometry) filter would provide <12 ft along track accuracy extrapolating 1 mile at 60 Mph with no GPS.– Cheap and simple implemented in post time
• Guess which is a lot cheaper?
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But then You have the GPS/INERTIAL /ODOMETER• Should be as good as the Odometer and
HR…If it is integrated properly… at 5X to 10X the cost.
• Your Geometry measurement System may need Inertial Data for Stabilization of measurements.. So get it , but not Just for position improvement!
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How to get the Most out of Your GPS
• Make Sure Your Receiver is Navigating !!!!!!!• Know where the GPS antenna is with respect to
sensors (then you can compensate)!• Have a Track Map at least as accurate as your GPS (Do
you have to? No more than you have to have air conditioning in you car in Texas)
• A Chain is only as strong as its weakest link
– When you plan think of Location and Re-Location!
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About Synchronization • SYNCHRONIZE Your Sensors to Odometer
– Odometer is your interpolator
• SYNCHRONIZE Your GPS to Odometer– Odometer Distance between GPS outputs should be
consistent with GPS distance Difference
• SYNCHRONIZE GPS to Sensors ( Redundant? Maybe)– If you travel at 50 ft/sec, and there is a synch error of .2
sec between GPS output and Sensor,You are off by 10 ft! – Timing or Synch Jitter is the worst.. Because you can’t
compensate!• GPS Latency: GPS solution is before time of output. Good
receivers will extrapolate to to output time.
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Using Odometer as Strobe
• Most Geometry Car data is strobed to the (ft) count of the odometer. Its is logical
• GPS Data should be ( and is in many systems) Strobed in the same way. – Fresh GPS is detected at change.
– Sampling error can be no more that a ft.
– When it is done right, everything is time synched( even though we might not exactly what time it is)
– And yes, you can have a Kalman filter “without time”
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GPS Sampling Rates
• When there is an odometer providing data every ft or less, there is no need for GPS outputs faster that 1/sec… Software can do any necessary interpolation.
• Faster GPS sampling means less sophisticated Interpolation software.
• BUT it won’t significantly improve accuracies.
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What should be on a Track Map?• Dependent Variables :LAT/Long (Elevation), AZIMUTH
every ~15 –50 ft
• Independent Variable: Distance Along track Si: Preferably Derived from a GPS input based Algorithm
• LAT/Long derived from survey,fly maps, or GPS derived maps.
• Beware of Datum shifts (Does Positioning During Mapping use same earth model as Navigating GPS?)!
L1,
L2, L3,
S1 S2 S3
Format?
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Can Make A Track Map With Geometry Car GPS , Ancillary data and Optimal Smoothing
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Some Uses Of Track Map• Convert Lat/Long to distance along Track and
vise/versa. Lets High tech meet low tech
• Provide heading for Lever arm correction, and Estimation.
• Provide common Base for Communication, data collection
XDefect file/map
CrackedTie
312 ft X
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What data to Record on the Big Guys
• Latitude , Longitude, {Elevation} Time • Distance along track ( odometer) • Heading change( if Curvature is not on Geometry) • Integrity Related:
– Differential Quality , – Hdop ( measure of accuracy),– number of satellites in solution (good for in finding
integrity)…– Better: Sat numbers in solution ( can be used In post
processing for correction)
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If Kalman Filter Output is Available on Geometry Car
• Kalman filter output of LAT/Long/Heading {Distance along Track or correction to Odometer}
• {Filter Integrity Measure}• Measure of Raw heading change• + All data on previous slide
– To Recover from “Computer and software crashes”
– To Apply Optimal smoothing for more accurate positioning , and making semblance of map
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Data To Collect on “Low Tech Little Brothers” Having GPS
• At fault, lat/long , milepost and ft. If available
• Distance from fault to next good GPS reading. Could be “0”– Lat/long at this point– With track map this is now a redundant
measurement
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Odometer Error Sources and Suggested Accuracies
• Scale factor stability(.002 in say 200000 ft)• Random ( show example) • Low or no (Reasonable) speed sensitivity• Event related:
– Wheel skips ( best to have odometer on “free wheel”)
– Low speed effects( with magnetic odometers…test it at very low speeds)
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6000004000002000000E0
160
140
120
100
80
60
40
20
0
-20
-40
-60
Distance along track, ft
Odo
met
er E
rror
, ft.
Scale Factor, slope =.00018
Random Error
This odometer Error Would be O.K.
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Odometer Sampling Rates
• For Geometry car collection
• One pulse/ft MINIMUM
• 10 pulses or better/ft better
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Resultant Capabilities of Railroad Specific Receiver
• Fast or seamless acquisition or reacquisition of signal after short length outages.
• Differential Corrections wherever there is a GPS signal ( alternate modes of receiving differential corrections)
• Capability 1-D navigation when as few as two satellites are in view and a track map available. (Extension of 2-D navigation when only three satellites in view) (Don’t Hold Your Breath)
• Output only when there is High integrity or warning when Integrity cannot be validated
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Rome’s Version of A Railroad Specific Receiver
• For signal acquisition,reacquisition and tracking in weak signal environments
– Maximum Bandwidths of Receiver tracking loops consistent with the Railroad Operation accelerations ( Should be Adjustable at least by Manufacturer )
– Tracking loop aiding consistent with Odometer /heading reference inputs ( should be better and cheaper than MEMS aiding, but is not currently available)
• Antenna with rate Gyro (Certainly not Standard)
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Rome’s Version of A Railroad Specific Receiver (Cont.)
• RAIM (Internal Integrity Monitoring) tuned to accuracies of Differential Systems
• Software consistent with (1-D) navigation … factoring in track map into solutions (may be a long time coming)
– Built in integrity based on track maps
• Receptors of Differential Corrections coming from “Broadband ( like internet, cell phone, even perhaps TV, track based communications… It will come!)