availability improvement of rtk‐gps with imu
TRANSCRIPT
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Availability Improvement of RTK GPS with IMUAvailability Improvement of RTK‐GPS with IMU and Vehicle Sensors in Urban Environment
ION GPS/GNSS 2012
T k U i it f M i S i d T h lTokyo University of Marine Science and Technology
Nobuaki Kubo, Chen Dihan
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ContentsContents
• Background
• Objective and Commercial Product• Objective and Commercial Product
• Loosely coupled Integration of RTK with other sensors
• Proposed Technique
• Test Results
• Summary
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BackgroundBackground
• The number of traffic accident deaths is decreasing i J f t d d
Transition of the number of deaths for 20 yearsin Japan (within 24 hours)
in Japan for two decades.• Future ITS still requires more
efficient transport system.efficient transport system.‐Safety‐Energy savinggy g‐Standardization
• What is a roll of GNSS ?
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ITS and GNSSITS and GNSS• Automatic collision avoidance system have been installed• Automatic collision avoidance system have been installed
recently. They are not related to GNSS.
• However most of present and future services for ITS will stillHowever, most of present and future services for ITS will still rely on GNSS to some extent.
Auto pilot (expressway)
Warning system(tight curve, fallen object)VICS
(FM, Beacon)Prove system
(avoid traffic jam, significant database)
( , )
ETC
Auto pilot (general road)
ITS spot
Where is your position ? (10 1 10 )4
Where is your position ? (10m or 1m or 10cm)
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Two Commercial ProductsTwo Commercial Products
#1 Survey‐grade GNSS + DMI + military‐grade IMU‐Expensive but fully‐integrated turnkey position
‐10 cm accuracy even with one minute outage
‐it is often used as a reference system for automobile
#2 Car‐navigation‐grade GNSS + Speed sensor + IMU#2 Car navigation grade GNSS + Speed sensor + IMU‐A few hundred dollars but several meters accuracy
‐100% coverage, continuous positioningg , p g
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Performance of #2 ProductPerformance of #2 Product• Open‐sky: Horizontal Errors were within 3m• Urban: Horizontal Errors were within 5m• Dense‐urban: following figures• Underground: 10m‐ / minute
West Shinjuku in Tokyo M i d i i b 10
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West Shinjuku in Tokyo(many skyscrapers)
Maximum deviation: about 10m
Provided by HONDA R&D
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Our ObjectiveOur Objective
• Survey‐grade GNSS + Speed sensor + IMUReliable RTK still requires dual‐frequency Low cost
• Prospective accuracy in safety use for ITS like lane recognition is said under 1m with continuous positionsrecognition is said under 1m with continuous positions
1cm10cm1m5m10m
AccuracyTarget#1 Product#2 Product
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1m horizontal error and 100% availability
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Algorithm of Loosely Coupled IntegrationAlgorithm of Loosely Coupled Integration
A l t
Vehicle Sensor Speed
Accelerometer
Gyroscope Yaw RateHeading
Velocity Filter
Movement Detection
GNSS Raw Data (+SQT) Velocity Heading
Heading Filter
#3
Float Position
RTK W Fi
Position Filter#2
RTK Position
Wrong Fix Detection
Navigation*SQT: Signal Quality Test
#1
f8
NavigationSQ : S g a Qua ty est# : Order of Priority
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RTKRTK
• Double differenced observations• Double‐differenced observations
• LAMBDA method
• Ratio Test (>3) + ADOP
Good Quality Observation
Bad Quality Observation is includedObservation
LAMBDA + Ratio Test (ADOP)
Observation is included
LAMBDA + Ratio Test(ADOP)(ADOP)
Reliability OK
(ADOP)
Reliability decreases
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Signal Quality TestSignal Quality Test(Detecting dominant multipath signal)
(Kubo et al 2005)
• Detection method is very simple
(Kubo et al, 2005)
(L1+L2, 2011)
C/N0(dB‐Hz)PRN 15 (elevation 60‐70‐60)
Only reflection
50 estimated
7‐10dB
30
40
i i l l
thresholdactual data
Diffraction and reflection
30 minimum level
Diffraction and reflection(dominant multipath)timeTemporal variation of C/N0
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Ambiguity Resolution with Velocity‐Information
• RTK requires initial positions (=float solutions).I d f l fl l i d i i i d
(Kubo et al, 2008)
• Instead of normal float solution, expected position is used.• Search space can be reduced dramatically.
t t‐1t+1 t‐2
Expected Position(t) = Previous Fix Position(t‐1) + (Velocity(t)+Velocity(t‐1))/2
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Algorithm of Loosely Coupled IntegrationAlgorithm of Loosely Coupled Integration
A l t
Vehicle Sensor Speed
Accelerometer
Gyroscope Yaw RateHeading
Velocity Filter
Movement Detection
GNSS Raw Data (+SQT) Velocity Heading
Heading Filter
#3
Float Position
RTK W Fi
Position Filter#2
RTK Position
Wrong Fix Detection
Navigation*SQT: Signal Quality Test
#1
f12
NavigationSQ : S g a Qua ty est# : Order of Priority
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Heading from GPS VelocityHeading from GPS Velocity– We can not get the right heading when ( , )k G gx
the vehicle is stationary or in a low speed
• GPS velocity measurement has a few cm/s noise 1k k k k
k k k
x F x Gwy Hx v
10 1
tF
( , )k kk G g
k k k
| | 1 | 1ˆ ˆ ˆ( )k k k k k k k k kx x K y H x
ˆ ˆF1| |ˆ ˆk k k k kx F x
1| 1 | 1( )T T
k k k k k k k k kK P H H P H R
– The heading error will increase when the vehicle
is moving in a high yaw rate
GPS li i i l t
| | 1 | 1k k k k k k k kP P K H P
1| |T T
k k k k k k k k kP F P F G Q G
• GPS sampling is in a low rate
Heading from GPSTrue heading
2
2
0
0G
g
R
g
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A new heading estimation algorithmA new heading estimation algorithm• Moving situations
Low speed (from vehicle speed sensor)– Low speed (from vehicle speed sensor)
– Normal speed with low yaw rate and HDOP<5
– with low yaw rate and HDOP>5
ith hi h t d HDOP<5– with high yaw rate and HDOP<5
– with high yaw rate and HDOP>5
Speed threshold : 1 m/s
• The measurement covariance will be updated
p /Yaw rate threshold : 4 deg/s
in each state.
No smoothed / std=0.64 Smoothed by IMU / std=0.29
g)g)
Error (deg
Error (deg
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Not include stop and low speed
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Algorithm of Loosely Coupled IntegrationAlgorithm of Loosely Coupled Integration
A l t
Vehicle Sensor Speed
Accelerometer
Gyroscope Yaw RateHeading
Velocity Filter
Movement Detection
GNSS Raw Data (+SQT) Velocity Heading
Heading Filter
#3
Float Position
RTK W Fi
Position Filter#2
RTK Position
Wrong Fix Detection
Navigation*SQT: Signal Quality Test
#1
f15
NavigationSQ : S g a Qua ty est# : Order of Priority
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Wrong fix DetectionWrong fix Detection• Calculate the change of the altitudeCalculate the change of the altitude
2
1sin( )
t
th v dt
• is the pitch angle change deduced from a pitch rate gyro
• Velocity in vertical direction from GPS is also used
h f d d h h l bl
• Epochs of t1 and t2 are used when the RTK‐GPS is available.
• Bad quality carrier‐phase can be often received in t2 (re‐tracking).
Maximum threshold
Mi i th h ld
An example of the threshold of height
Outage of RTK‐GPSMinimum threshold
p g
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Automobile Experimental TestsAutomobile Experimental Tests
• Test1 (only RTK): Tokyo(2011)
• Test2 (RTK+IMU+Speed): Nagoya(2010)
GPS Receiver NovAtel OEM5 or JAVAD Delta (CS=100s)
A N A l GPS702 JAVAD R AAntenna NovAtel GPS702 or JAVAD RegAnt
IMU Crossbow IMU 440 (MEMS)
Speed sensor Standard vehicle loaded wheel speed sensorsSpeed sensor Standard vehicle loaded wheel speed sensors
True position POS/LV (Applanix) (positional accuracy ‐ within 10cm/1min outage )
Baseline within 10 km
Mask angle 15 degrees
HDOP h h ld 10
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HDOP threshold 10
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Tokyo (Test1)(O 10% U b 50% D 40%)(Open 10% Urban 50% Dense 40%)
T t l i d 1h• Total period: 1hour
• Data rate: 5Hz
• JAVAD Delta+RegAntJAVAD Delta RegAnt
• Relatively wide road
18Around Tokyo Station
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RTK Performance (Test1)RTK Performance (Test1)Availability and percentage within 50 cm in horizontal error
GPS GPS+QZS
DGPS 69.6% 84.7%
Normal RTK 17.6% (99.2%) 31.7% (99.7%)
+signal quality test 15.7% (99.8%) 36.0% (100%)g q y ( ) ( )
+velocity information 21.2% (99.8%) 43.5% (100%)
Total: 17800 epochs (5Hz)Total: 17800 epochs (5Hz)(): percentage within 50 cm
4.5
QZSGPS
19Satellite Constellation
QZS
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Temporal Horizontal Errors (Test1)p ( )(GPS+QZS, Best case in RTK)
2(m
)
1
1.5
zontal Error
0.5
bsolute Horiz
0176500 177000 177500 178000 178500 179000 179500 180000 180500 181000
Ab
GPSTIME (s)GPSTIME (s)
7737 / 17800 epochs
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Nagoya (Test2) g y ( )(Open 0% Urban 40% Dense 50% No‐Sky 10%)
• QZS was not evaluated
T t l i d 27 i• Total period: 27min
• NovAtel OEM5+ GPS702
• Data rate: 10HzData rate: 10Hz
• POS/LV was used to evaluate the precise temporal errors.
• Relatively wide road
• Good GPS Constellation
• Average speed was 3 5m/s• Average speed was 3.5m/s
N Sk
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Test Route No‐Sky
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Number of Used Satellites (Test2)Number of Used Satellites (Test2)
A NUS i f > 7 1• Average NUS in reference ‐> 7.1
• Average NUS in rover ‐> 3.2
L1 + L2 carrier phase are validP t ith 4 t llit 42%
Over 50 are not displayed
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Percentage with 4 or more satellites: 42%
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RTK Performance (Test2)RTK Performance (Test2)Availability and percentage within 1 m in horizontal error
GPS
DGPS 51 0% (55 3%)DGPS 51.0% (55.3%)
Normal RTK 12.4% (88.9%)
+signal quality test 13 0% (98 4%)+signal quality test 13.0% (98.4%)
+velocity information 32.0% (94.8%)
ADOP 0 25 20 0% (99 8%)
for integration
+ADOP < 0.25 20.0% (99.8%)Total: 16270 epochs (10Hz)(): percentage within 1 m() p g
The rest of 68 % positions have to be generated from filtered DGPS or INS using our proposed integration method.
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Wrong Fix Detection Summary (Test2)g y ( )
5
Temporal Horizontal Errors in RTK (32% of all)
3
4
5
tal Errors (m
)
Actual Wrong Fix Detection Example
1
2
3
olute Horizon
t
40
42
44
RTK (m
)
0351000 351500 352000 352500 353000
Abso
GPSTIME (s)32
34
36
38
Altitud
e in R
HorizontalErrors (m)
StatisticsWrong fix Detection
1m-2m 13 9
30
32
351438 351439 351440 351441
A
GPSTIME (s)
2m-3m 3 3>3m 259 259
M t f fi d t t d !24
Most of wrong fixes were detected !
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Total Performance (Test2)Total Performance (Test2)
Horizontal Errors (m)Statistics
N Percentage
<=1m 13379 82.2
25
< 1m 13379 82.2>1m 2891 17.8
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Total Horizontal Positions (Test2)( )
RTK-GPS fixed positionsp
32% of all(5219 of 16270epochs)
Positions given by our proposed integration systemp p g y
68% of all(11051 of 16270epochs)=
100 %26
100 %
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Summaryy• Our proposed signal quality test and velocity use for the reliability
and availability in RTK were quite effective in urban environment. y qHowever, there are still wrong fixes.
L l l d i i (GPS IMU S d) h d• Loosely coupled integration (GPS+IMU+Speed) method was proposed and availability was improved from 32% to 100%. Accuracy deterioration was small using IMU and Speed.
M lti GNSS d M lti F i l i f t A QZS• Multi‐GNSS and Multi‐Frequency is clear in future. As QZS was effective in RTK, the performance of RTK in urban environment must be improved.
• What is an appropriate application in the level of 1m accuracy ?
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Thank you for your attention [email protected]
• I would like to thank the Toyota central R&D for their valuable experimental data
Acknowledgements
• I would like to thank the Toyota central R&D for their valuable experimental data.
• Financial support was partly provided by Space Use Promotion Grant from Ministry of Education, Culture, Sports, Science and Technology.
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