Precision Personnel Locator System

Matthew LoweElectrical and Computer Engineering

Worcester Polytechnic InstituteWorcester, MA

Inertial Filtering for Improved Position Accuracy in Challenging RF Environments

06/29/2011

JNC 2011

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Overall Project Goal

• Indoor LocalizationTracking

• For first responders• No  Pre‐installed 

Infrastructure• Rapid Deployment

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Inertial RF FusionOverview

• Design an Inertial Tracking solution– Foot Mounted IMU– (Extended) Kalman Filter

• Design an RF algorithm which uses Inertial information at the signal (not range) level– (ISAR) Inverse Synthetic 

Aperture (sART) Singular value Reconciliation Tomography (ISART)

• Close the loop to update the Inertial

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Inertial RF Fusion

IMUData

Fusion Algorithm

RF Data

Inertial System Model

EKF

PhysicalSystem Model

Noise Model

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Physical System Model

• Newtonian Physics • Representing Rotation (Charting)

Charts•Rotation Matrix•Unit Quaternion•Euler Angle

Problems•Closure•Differential Form

ContinuousTime Linearize Discretize

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Inertial RF Fusion

IMUData

Fusion Algorithm

RF Data

Inertial System Model

EKF

PhysicalSystem Model

Noise Model

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Noise Model(Noise Processes)

WGN

Flicker

Bias Walk

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Inertial RF Fusion

IMUData

Fusion Algorithm

RF Data

Inertial System Model

EKF

PhysicalSystem Model

Noise Model

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EKF

Physical SystemModel

IMU Noise Specifications

(From Spec Sheet)

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German Aerospace CenterPublic Data set

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Inertial RF Fusion

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IMUData

Fusion Algorithm

RF Data

Inertial System Model

EKF

PhysicalSystem Model

Noise Model

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sART

• Combines the data at the signal level

• Each point is rephasedas if the signal originated there

• Metric is computed using Singular Value Decomposition

• Each point is compared via its metric value

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Religious Center

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ISART

• Use the benefits of both systems• Inertial is good in the 

short term• RF has no drift

• Use the inertial track to tie together multiple RF measurements

o8

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Slide 14

o8 This looks like your notes, not a slide for the audience.orr, 6/22/2011

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ISART SimulationsART ISART

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ISART Real Data

Inertial  TrackISART  Track

sART Track

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Conclusions

• Designed an Inertial Tracking solution– Contributed a filter creation method which was automated and based on sensor specifications

– Demonstrated validity on a publically available data set

• Design an RF algorithm which uses Inertial information– Contributed an algorithm which mitigates difficult RF environments by using inertial tracks

– Demonstrated preliminary results

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Acknowledgments

• DHS S&T• Analog Devices• Team members (Andrew and Jamie)• German Aerospace Center DLR

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PPL Workshop at WPI sponsored by DHS

• In August WPI will be hosting the 6th annual indoor location workshop

• http://www.wpi.edu/academics/ece/ppl/2011workshop.html or Google “ppl workshop”

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Questions?

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