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Tightly-Coupled Opportunistic Navigation for Deep Urban and Indoor Positioning

Tightly-Coupled Opportunistic Navigation for Deep Urban and Indoor Positioning. Ken Pesyna , Zak Kassas , Jahshan Bhatti , and Todd Humphreys. Presentation at ION 2011|September 23, 2011. Outline. Motivate & define Tightly-Coupled Opportunistic Navigation (TCON)

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Tightly-Coupled Opportunistic Navigation for Deep Urban and Indoor Positioning

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  1. Tightly-Coupled Opportunistic Navigation for Deep Urban and Indoor Positioning Ken Pesyna, Zak Kassas, JahshanBhatti, and Todd Humphreys Presentation at ION 2011|September 23, 2011

  2. Outline • Motivate & define Tightly-Coupled Opportunistic Navigation (TCON) • Explore “signals of opportunity” for TCON • Discuss the central estimator to optimally fuse signals together • Present experimental results

  3. Goal Optimally extract navigation and timing information from ambient radio signals Tightly-Coupled Opportunistic Navigation is a framework to achieve this goal

  4. Tightly-Coupled Opportunistic Navigation • TCON is an optimal generalization of specific hybrid navigation technologies • Generalize • Optimize TCON Cellular [1] GNSS HDTV [2] Iridium [3] [1] R. Rowe, P. Duffett-Smith, et. al., “Enhanced GPS: The tight integration of received cellular timing signals and GNSS receivers for ubiquitous positioning,” in Position, Location, and Navigation Symposium, IEEE/ION, 2008. [2] J. Do, M. Rabinowitz, and P. Enge, “Performance of hybrid positioning system combining GPS and television signals,” in Position, Location, And Navigation Symposium, IEEE/ION, 2006. [3] M. Joerger, et. al., “Iridium/gps carrier phase positioning and fault detection over wide areas,” ION GNSS 2009.

  5. TCON: Breaking it Down Tightly-Coupled • Signals downmixed and sampled with the same clock • Absolute time correspondence at the nanosecond level Opportunistic Navigation • Receiver continuously searches for signals from which to extract navigation and timing information • Receiver employs on-the-fly signal characterization: • Clock stability • Clock offset • Carrier-to-noise ratio • Transmitter location

  6. Tightly-Coupled Opportunistic Navigation

  7. Signals of Opportunity • TCON treats all RF signals as potential signals of opportunity • GNSS signals: GPS, Galileo, Glonass • Cellular signals: CDMA, GSM, 4G LTE, & WiMAX • Other satellite signals: Iridium • Other ground-based signals: HDTV, Wi-Fi

  8. What SOP characteristics are desirable? • High received carrier-to-noise ratio • Good frequency stability • Known location/timing offset Unfortunately, we almost never get all three properties if we are not working with dedicated navigation signals

  9. Freestyle Navigation • CDMA Cellular • Carrier-to-noise is high, penetrates well • Towers do not move • Only roughly synchronized to GPS • Carrier stability varies from provider to provider • Iridium • Carrier-to-noise ratio is higher than GNSS • Global coverage • Not continuous – “Bursty” TDMA structure • Ambiguous in carrier phase from burst to burst

  10. Centralized Estimator

  11. Centralized Estimator • Optimally combines observables from all SOPs • Our preferred implementation is an extended Kalman filter: • Base State: SOP state: • Full State:

  12. Carrier Phase Measurement Models • GPS carrier phase measurement model: • CDMA carrier phase measurement model: • Iridium carrier phase measurement model:

  13. Dynamics Model • Dynamics dependent on current state and process noise: • Process noise covariance formed by models of clock dynamics:

  14. Adaptive Dynamics Model Update SOP Clock Model Output * Run Kalman Filter new old Iterate * Can only be done when is observable (to within a constant offset)

  15. Simple TCON Demo: Experiment Setup GRID Software Receiver National Instruments RFSA MATLAB EKF Storage

  16. Simple TCON Demo: SOP Wardriving

  17. A Simple Demonstration of TCON (2) Characterizing CDMA SOP (3) Demonstrate post-characterization CDMA SOP only estimate of (1) Obtaining Truth 6x 2x Update SOP Clock Model Run Kalman Filter Truth Estimate CDMA-based estimate vs. new old Iterate

  18. So What? • Achieve our estimate error of by differencing the CDMA-only estimate from the truth variations: • The stability of will affect the length of achievable GNSS coherent integration in weak signal conditions • In this experiment, CDMA-only TCON (after-characterization) could supply coherent integration times beyond 100 seconds • 100+ sec. coherent integration allows GNSS acquisition of signals below 0 dB-Hz assuming all else ideal - Mean squared coherence of

  19. Conclusions • TCON is a framework to optimally extract navigation and timing information from ambient radio signals • Tight-coupling at the carrier-phase level and SOP characterization are essential to TCON • A simple TCON demonstration on timing showed a TCON-enabled receiver can coherently integrate beyond 100 seconds using characterized CDMA signals

  20. Questions?

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