Cooperative localization (part I) Jouni Rantakokko

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1 Cooperative localization (part I) Jouni Rantakokko

2 Cooperative applications / approaches Wireless sensor networks Robotics Pedestrian localization First responders Localization sensors - Small, low-cost nodes only use wireless ranging Centralized and distributed algorithms Use of anchor nodes - Larger nodes may also incorporate additional sensors GNSS-receivers, inertial, magnetometers,

3 Cooperative localization examples GPS-receivers - Two receivers can exchange pseudorange measurements - Range between receivers desired, and directions - Could improve performance if receivers due to signal blockage tracks different satellites F. Berefelt, B. Boberg, J. Nygårds, P. Strömbäck, S.-L. Wirkander, Collaborative GPS/INS Navigation in Urban Environments, Proceedings of ION NTM, 2004.

4 Cooperative localization examples GPS-receivers - Two receivers can exchange pseudo-range measurements - Range between receivers desired, and directions - Could improve performance if receivers due to signal blockage tracks different satellites

5 Cooperative localization - examples Mobile-phones cooperating for improved accuracy indoors - Bluetooth used as proximity sensors - Internal mobile phone sensors are used to estimate how person is moving indoors - Phones exchange position estimates (and uncertainties) - Some nodes are assumed to have more accurate position estimates Walked indoors recently, and had GPS-positions outdoors - Could be implemented as a smartphone app I.Krämer, B. Eissfeller: A peer-to-peer Kalman Filter for Pedestrian Navigation, Proceedings of ION-GNSS 2009, September 2009, Savannah, GA, USA

6 Cooperative approaches for FR s Connectivity can not be guaranteed(?) - Opportunistic approaches use range measurements when available - Distributed algorithms What sensor data should be exchanged? - Communications consumes resources (battery) so any data exchange should provide a clear benefit

7 Cooperative approaches for FR s GPS? - As long as there are no reliable performance metrics for accuracy of individual pseudo-range measurements then tight-coupling or cooperative use of pseudo-range measurements is not of particular interest? Magnetometer? - First persons moving through the area can perform magnetic fingerprinting, characterizing large & static local magnetic field disturbances - Later arriving units can compare magnetic field measurements with earlier units fingerprinting

8 Cooperative approaches for FR s Barometric data? - Barometric pressure measurements could be exchanged within the group to provide more robust estimates of floor-level? Generated maps? - Units with mapping capability could exchange maps and thereby improve map quality - Generated maps could be used by all units entering previously mapped areas in order to improve their positioning accuracy

9 Cooperative approaches for FR s Simple approach - Perform ranging between two persons and exchange position and uncertainty estimates

10 Cooperative navigation (part II) An example using foot-mounted INS and UWB-transceivers Jouni Rantakokko

11 References J. Rantakokko et al, Accurate and reliable soldier and first responder indoor positioning: Multi-sensor systems and cooperative localization, IEEE Wireless Communications Magazine, April P. Strömbäck, J. Rantakokko, S.-L. Wirkander, M. Alexandersson, K. Fors, I. Skog, and P. Händel Footmounted Inertial Navigation and Cooperative Sensor Fusion for Indoor Positioning, Proc. ION International Technical Meeting (ITM), San Diego, USA, January 2010.

12 Aim Increased accuracy during long-term operations in GNSS-challenged environments for - First responders - Dismounted soldiers - Personal navigation

13 Outline Short recapitulation Foot-mounted INS IR-UWB Cooperative navigation Summary

14 Outline Short recapitulation Foot-mounted INS IR-UWB Cooperative navigation Summary

15 First responder requirements What is desired of an indoor positioning system? - Robust, light-weight, small, power efficient, low-cost - Reliable estimation of room/floor (or equivalent) - Error estimates (integrity monitoring) - No dependence on pre-installed infrastructure - Seamless outdoor-indoor coverage, with consistent performance in all relevant scenarios

16 First responder requirements Requirement estimates ~ 1-3 m accuracy ~ near 100% availability in all environments << 1 kg, incl. processing unit and visualization ~ 8-24 h battery ~ 1k >> 30 min s indoors but they also depend heavily on user group, type of operation, and usage (e.g. avoid friendly fire or efficient C2),

17 Summary enabling technologies Today s technology insufficient crucial user requirements cannot be fulfilled (simultaneously) with a single positioning sensor/sub-system - 3D accuracy and availability indoors - Integrity monitoring, estimate of position errors - Price, size, weight, battery - Tactical behavior Sensor fusion approach needed - What sensors should be used? - How should the sensor data be combined?

18 Summary enabling technologies Multi-sensor system is required - GNSS-receivers GPS + Galileo + GLONASS(?) Different services and signals from all SatNav systems are available - Inertial sensors, magnetometers and barometer Foot-mounted, back-mounted and/or co-located with camera - Ranging devices (RF, acoustic, ) - Imaging sensors -Doppler radar - Cooperative navigation HW - Focus on inexpensive and lightweight sensors SW - Quality of multi-sensor fusion and integrity monitoring of positioning sub-systems dictates performance

19 Vision for the future Consumer market - Smartphone as multi-sensor platform accelerometers, gyros, magnetometers, barometer, camera Radio-based ranging Acoustic Map WLAN Cooperation - Positioning app s available

20 Vision for the future First responder market - Individual sensors accelerometers, gyros, magnetometer, barometer camera, acoustic, Doppler-radar - Radio-based ranging and cooperative navigation Impulse radio (UWB) Ranging waveform in future FR radios (SDR) FR-to-FR and/or FR-to-vehicle -Maps LiDAR (3D) and cooperative mapping

21 Possible future concept for robust first responder positioning systems in urban operations IR-Camera IR-Camera IMU IMU Cooperative navigation for high accuracy during long-term operations GNSS GNSS - Impulse radio (UWB) for ranging and exchange of information? - What sensor data should be exchanged to enhance efficiency of cooperation? Accelerometers Accelerometers Gyro Gyro Magnetometers Magnetometers Barometric Barometric altimeter altimeter First responder equipped with individual sensors for position estimation J. Rantakokko et al, Accurate and reliable soldier and first responder indoor positioning: Multi-sensor systems and cooperative localization, IEEE Wireless Communications Magazine, April 2011

22 Possible future concept for robust soldier positioning systems in urban operations Camera Camera IMU IMU Cooperative navigation for high accuracy during long-term operations GNSS GNSS GUI GUI Processor Processor Accelerometrar Accelerometrar Gyro Gyro Magnetometrar Magnetometrar Barometer Barometer - Impulse radio (UWB) for ranging and exchange of information? - What sensor data should be exchanged to enhance efficiency of cooperation? Soldier equipped with individual sensors for position estimation - What sensors should be used? - How should they be combined (sensor fusion)? J. Rantakokko et al, Accurate and reliable soldier and first responder indoor positioning: Multi-sensor systems and cooperative localization, IEEE Wireless Communications Magazine, April 2011

23 Backpack contains laptop, battery, converter and UWB - UWB-ranging measurements and analysis - Foot-mounted inertial navigation experiments - Collaborative sensor fusion experiments Work consists mainly of three parts Scope of work

24 Outline Short recapitulation IR-UWB Foot-mounted INS Cooperative navigation Summary

25 UWB-ranging TimeDomain PulsOn 220 EVK GHz 10-dB BW (approx GHz) - Round-trip time estimation - Sample waveforms for ranging, comm s and radar Error models - Differentiate between LOS NLOS with direct path NLOS w/o direct path

26 UWB-ranging (LOS) LOS experiments - Distance 2-50 meter, multipath environment - Small ranging errors and low standard deviation - Scale-factor increase in ranging error with decreasing distance (calibration issue)

27 UWB-ranging (NLOS) Plaster-board walls, whiteboards, safety-cabinets -a=6 m -b=9 m - c=12 m - d=15 m

28 UWB-ranging (NLOS) ~dm accuracy Approx. ranging distance < 15 m (<4 walls) Fairly static multipath Probability of undetected direct path ~6% at 12m Not corrected for distance scaling factor (calibration)

29 UWB-ranging (NLOS) Concrete walls, different thickness, whiteboards

30 UWB-ranging (NLOS) Approximate ranging distance <9 m (<3 walls) Fairly static multipath Probability of undetected direct path ~7% at 6m Not corrected for distance scaling factor

31 UWB-ranging through whiteboard Whiteboard has low signal penetration, generates multipath

32 UWB-ranging between floors

33 Outline Short recapitulation IR-UWB Foot-mounted INS Cooperative navigation Summary

34 Foot-mounted INS Navigation algorithm based on a 15-state Extended Kalman Filter - 3D position, velocity & orientation (9 states) - Accelerometer and Gyro bias (6 states) Measurement updates to KF consists of a zero velocity (ZUPT) during the stance phase Detection of ZUPT based on gyro signal amplitude averaged over a few samples - Accurate during regular walking, errors may increase during other movement regimes

35 Outline Short recapitulation Foot-mounted INS IR-UWB Cooperative navigation Summary

36 Cooperative navigation Estimate position, velocity, and orientation (and uncertainties) based on foot-mounted sensors Measure range to cooperative unit Exchange position estimates and uncertainties between cooperative units Update units positions, velocities, and orientations RF-ranging Transfer of position and uncertainty

37 Cooperative navigation -overview Accelerometers Gyros ZUPT detection Corrections Measurement update (ZUPT) INS Mechanization Position Velocity Orientation Velocity EKF

38 Range, Position & Covariance Cooperative navigation -overview UWB Accelerometers Gyros ZUPT detection Measurement update (Range) Corrections Measurement update (ZUPT) INS Position Mechanization Position Velocity Orientation Velocity EKF

39 Experiments one example Scenario 1 - single floor (horizontal plane) Scenario 2 - two floors (horizontal and vertical motion) Multiple laps for each test, at two different occasions Closed loop tests - Start point and stop point are the same within a few centimeters Initial orientation, position and velocities - Known to a few deg & cm & mm/s Initial gyro bias - Chosen as the mean value of gyro signal during a minute of standing still (this is only a rough estimate)

40 Scenarios Scenario 1 Single floor Scenario 2 Two floors

41 Results - Cooperative positioning No cooperation Cooperation Scenario 1 One floor Blue: 9.0 m (3D pos error) Red: 8.2 m (3D pos error) Blue: 1.4 m (3D pos error) Red: 3.5 m (3D pos error)

42 Results - Cooperative positioning No cooperation Cooperation Scenario 2 Two floors Blue: 3.8 m (3D pos error) Red: 2.8 m (3D pos error) Blue: 1.3 m (3D pos error) Red: 2.7 m (3D pos error)

43 Summary Cooperation has the potential to improve performance significantly - The improvement in these two tests is likely larger than what will be achieved in general Smaller errors now with foot-mounted system Heading drift experienced particularly in Scenario 1 ver favorable towards cooperative approaches - Multiple cooperative units will lead to further improvements

44 Q&A

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