Next Generation Personal Navigator: An Enhanced Prototype .

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Next Generation Personal Navigator:An Enhanced Prototype Personal Inertial Navigation SystemYunqian Ma, PhDHoneywell AerospaceWPI workshopAugust 6, 2012

Personal Navigation Overview What is personal navigation ?- Provides localization to humans on foot Includes GPS denied environments Who needs PN?- Situations that require personnelaccountability, situational awareness Soldiers, first responders, industrial workers DHS funded GLANSER program focused at ER/firefightercommunity Product differentiators- Cost, SWaP, accuracy User community has high expectations based on cellphone /GPS experienceGPSAntennaRadioIMU2

Measurement Sources- Visual odometry (Camera, LIDAR, ) – measuresposition change relative to recognized features Requires image processing, accurate attitude Require system calibration Realized accuracy (stereo camera): 4%- Zero Velocity Aiding (ZUPT) Boot mounted IMU can achieve accurate navigation Zupt occurs at every heel strike – limits free navigation time to 1 second Customers resistant to boot mounted hardware3

Evolution of ePINS: Prior projects SUO SAS (DARPA/IR&D 1999)- HG1700 IMU, walking motion model,DGPS, mag, baro, (MFMU)- Manual initialization, gyrocompassalignment- Very large SWaP (full size backpack) iPINS (DARPA 2005)- HG1930 IMU- Manual heading initialization- Extended motion model to running,non-forward walking- Waist pack4

ePINS Objectives Develop a ePINS prototype- Use iPINS design as baseline ECTOS Nav/Kalman software- Update hardware components Block C HG1930 IMU ANGIE navigation processor Commercial GPS receiver- Redesign package – miniaturize as much as possible Belt mount- Incorporate IR&D developments LPI Heading initialization method Wavelet based motion model classification Motion model altitude control Android mobile display besides PC display5

ePINS Components ePINS - enhanced Personal Inertial Navigation SystemPreliminary Prototype SpecificationOperating MotionProduct component, sub-system,and packagePerformance at end point(Closed Path@ 1 Hour)Walking 2% distance traveledCombined (walking, runningcrawling) 4% distance traveledHG1930 IMUMicroprocessor BoardPackageVolume (with battery)613 cm3Weight454 gPower 5 wattsOperating life4 hoursInterfacesRS-422 SerialEthernetUSBPressure SensorHMC6343 CompassStandard NMEA outputs andcustom NMEA inputs and outputsDisplay InterfaceData Logging,Display InterfaceData loggingNovaTel GPSReceiverePINS Package6

ePINS AssemblyLeatheror cloth beltloopPlastic HousingPieces (3 each)Aluminum Housing(1 each)Circuit CardAssembly(Attaches toplastichousing)IMU HG1930GPSreceiverBatterySwitch7

Hardware Architecture8

Approach Heading Initialization- Developed Low Performance IMU (LPI) headingdetermination method User walks a few circles in presence of GPS Capable of determining heading to 0.6 deg Improve distance traveled estimate while allowingindividual to move in a more natural manner- Motion classification using wavelet domain classifier- Step model algorithm was developed to improve distancetraveled estimate Provides an estimate of the length of each foot step based on delta timebetween footfalls Integration of inertial navigation with the distancetraveled estimate to achieve optimal performance9

Motion Classification Algorithm Segment IMU signal based on peak or valley of theIMU dataWes Running [2921-2929]drx 010001500200025003000350040000500100015002000time (s)2500300035004000dry (r/s)0.020-0.02-0.04drz (r/s)0.020.010-0.01dvx (g)0.50-0.5dvy (g)0-0.5-1dvz (g)0.50-0.510

Motion Classification Algorithm 2 persons walking IMU data (red curve for oneperson, blue curve for the other person)drx (r/s).0.02roll0-0.02.dry 00102030405060708090drz (r/s)0-0.02dvx (g)0.50-0.5dvy (g)10-1-21dvz (g).z200.02yaw.y100-0.02.x00.020.50-0.511

Step distance model The step-length modeling formulated as a regressionover the frequency and user’s biometric information12

Sensor Integration: ECTOS Nav/EKFNovaTelOEMStarGPSR13

Benefits of Integration Navigation output is based on strapdown inertialnavigation, not dead reckoning- Provides continuous solution that is not dependent on stepdetection Kalman filter residual test is used to reject poormeasurements from Step Model- Step Model will provide erroneous results when individualmoves in an “unusual” manner, relative to walking Side stepping, walking with torso turned relative to direction of travel- System operates in “free inertial” mode when Step Modelmeasurements are rejected14

Demonstration Startup/Initialization- System heading initializedfrom GPS position andvelocity measurement- Operation in GPS -deniedenvironments- Real time observation ofperformance COTS 900 MHz data radiotransmits user position todisplay @ 1 Hz15

Demonstration Procedure Heading calibrationStep parameterestimation with GPSOutdoor GPS denied(compare performanceto above step)Transition fromoutside to inside(GPS aided)Enter building(GPS denied)Walk up stairsWalk down stairsEnd at conferenceroom7865142316

ePINS Summary Benefits- Obtain accurate positioning in GPS denied environments- Small, light weight unit can be easily carried by firstresponders, rescue workers or soldiers- Rugged design and packaging will withstand the most difficultfirst responder and military environments Features- Incorporates state-of-the-art Micro Electromechanical Systems(MEMS) gyros and accelerometers, 3 axis magnetic compass,barometric altitude sensor and advanced navigation software- Patented motion classification algorithms accurately identifyand measure user activity- System automatically adapts navigation parameters to the user,achieving outstanding accuracy without calibration- High performance MEMS gyros eliminate errors caused bymagnetic disturbances17

Future ePINS concept Future performance andphysical characteristic18

Segment IMU signal based on peak or valley of the IMU data 0 500 1000 1500 2000 2500 3000 3500 4000-0.01 0 0.01 0.02 Wes Running [2921-2929] dr x) 0 500 1000 1500 2000 2500 3000 3500 4000-0.04-0.02 0 0.02 dr y) 0 500 1000 1500 2000 2500 3000 3500 4000-0.01 0 0.01 0.02 dr z) 0 500 1000 1500 2000 2500 3000 3500 4000-0.5 0 0.5 dv x) 0 500 1000 .

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