Riding out the Rough Spots: Scintillation-Robust GNSS Carrier Tracking

1. Riding out the Rough Spots:Scintillation-Robust GNSS Carrier Tracking Dr. Todd E. Humphreys Radionavigation Laboratory University of Texas at Austin

2. UT Radionavigation Lab Research Agenda • GNSS Spoofing • Characterize spoofing signatures • Develop receiver-autonomous defenses • Develop augmentation-based defenses (GPS + eLORAN + Iridium + …) • GPS Jamming • Develop augmentation-based defenses • Locate jamming sources by combining data from a network of receivers • Indoor Navigation • Pioneer collaborative navigation • Develop augmentation-based indoor nav techniques (GPS + eLORAN + Iridium + …) • Natural GNSS Interference • Improve tracking loop robustness to scintillation

3. Ionospheric Diagnosis via Arrays of GPS Receivers Ionospheric Tomography (dense array) Ionospheric Monitoring (sparse array) Incident plane wave Disturbed ionosphere Nominal magnetic field direction CASES Connected Autonomous Space Environment Sensors Cornell University, UT Austin, ASTRA LLC AFOSR STTR Proposal, 2008 Diffracted wavefront Linear array of GRID receivers

4. CASES Sensor Evolution V0 V1 V2

5. Carrier Tracking Goals Long-term Goals Receiver noise and scintillation-induced phase errors Cycle slips (phase unlock) • Eliminate frequency unlock • Minimize cycle slips and generally reduce phase errors Strategy • Analyze scintillation effects on GPS receivers; isolate cause of phase unlock • Model scintillation well enough to generate realistic synthetic scintillation • Synthesize scintillation to test tracking loop strategies • Design phase tracking loops for operation in scintillation Total loss of carrier lock (frequency unlock)

6. Carrier Tracking Goals Long-term Goals • Eliminate frequency unlock • Minimize cycle slips and generally reduce phase errors Strategy • Analyze scintillation effects on GPS receivers; isolate cause of phase unlock • Model scintillation well enough to generate realistic synthetic scintillation • Synthesize scintillation to test tracking loop strategies • Design phase tracking loops for operation in scintillation

7. Analyze:The Empirical Scintillation Library Canonical fades

8. Fading Interpreted on the Complex Plane

9. Model: Distill Scintillation Down to Essential Characteristics for Carrier Tracking Standard statistical analysis techniques DPSK bit error prediction with Rice and 2nd-order Butterworth models

10. Synthesize:Turnthe Model Around

11. Scintillation Simulator Implementation

12. Hardware-in-the-loop Scintillation Robustness Evaluation GNSS Signal Simulator Scintillation Simulator Simulated time history GNSS Receiver Phase difference time history

13. Straightforward approach: navigation data bit prediction Incorporate the observed second-order dynamics into a Kalman filter whose state includes the complex components of z(t) Combine this with a Bayesian multiple-model filter that spawns a new tracking loop whenever a data bit is uncertain. Prune loops at parity check. Design:Scintillation-hardened Tracking Loops GOAL: Ts > 240 seconds for {S4 = 0.8, 0 = 0.8 sec., C/N0 = 43 dB-Hz} (a factor of 10 longer than current best)

14. Traditional Approach to Carrier Modeling

15. A New Approach to Carrier Modeling

16. A Multiple-Model Approach to Data Bit Estimation

17. The GPS Assimilator A Backward-Compatible Way to Harden Existing UE Against Scintillation The GPS Assimilator modernizes and makes existing GPS equipment resistant to jamming, spoofing, and scintillation without requiring hardware or software changes to the equipment

18. GPS Assimilator Prototype • All digital signal processing implemented in C++ on a high-end DSP • Marginal computational demands: • Tracking: ~1.2% of DSP per channel • Simulation: ~4% of DSP per channel • Full capability: • 12 L1 C/A & 10 L2C tracking channels • 8 L1 C/A simulation channels • 1 Hz navigation solution • Acquisition in background

19. Summary • Models of scintillation effects on phase tracking loops must faithfully capture deep fades • The mean time between differentially-detected navigation bit errors is a good lumped indicator of scintillation severity • The triple accurately predicts • For carrier tracking, scintillation modeling & simulation can be boiled down to two parameters: S4 & τ0 • A hardware-in-the-loop scintillation testbedhas been built and validated • Carrier tracking techniques inspired by the proposed model promises to extend

20. Acknowledgements • CASES sensor development funded by STTR grant through AFOSR via ASTRA LLC • Adaptation of CASES sensor for Antarctic deployment funded by ASTRA LLC

21. Model:Link Cycle Slips to Differentially-Detected Bit Errors

22. Amplitude Distribution: Rice distribution applies p(|z(t)|) can be summarized by the S4 index

23. Autocorrelation Function:Empirical Spectrum vs. Models 2nd-order Butterworth autocorrelation model applies R() can be summarized by 0