Riding out the Rough Spots:

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Presentations text content in Riding out the Rough Spots:

Slide1

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

Dr. Todd E. Humphreys

Radionavigation

Laboratory

University of Texas at Austin

Slide2

UT Radionavigation Lab Research Agenda

GNSS SpoofingCharacterize spoofing signaturesDevelop receiver-autonomous defensesDevelop augmentation-based defenses (GPS + eLORAN + Iridium + …)GPS JammingDevelop augmentation-based defensesLocate jamming sources by combining data from a network of receiversIndoor NavigationPioneer collaborative navigationDevelop augmentation-based indoor nav techniques (GPS + eLORAN + Iridium + …)Natural GNSS InterferenceImprove tracking loop robustness to scintillation

Slide3

Ionospheric Diagnosis via Arrays of GPS Receivers

Ionospheric

Monitoring (sparse array)

Ionospheric

Tomography (dense array)

Incident plane wave

Disturbedionosphere

Diffractedwavefront

Linear array ofGRID receivers

Nominal magneticfield direction

CASES

Connected Autonomous Space Environment Sensors

Cornell University, UT Austin, ASTRA LLC

AFOSR STTR Proposal, 2008

Slide4

CASES Sensor Evolution

V0

V1

V2

Slide5

Carrier Tracking Goals

Receiver noise and

scintillation-induced

phase errors

Cycle slips (phase unlock)

Total loss of carrier lock (frequency unlock)

Analyze

scintillation effects on GPS receivers; isolate cause of phase unlock

Model scintillation well enough to generate realistic synthetic scintillationSynthesize scintillation to test tracking loop strategies Design phase tracking loops for operation in scintillation

Strategy

Long-term Goals

Eliminate frequency unlock

Minimize cycle slips and generally reduce phase errors

Slide6

Carrier Tracking Goals

Analyze

scintillation effects on GPS receivers; isolate cause of phase unlock

Model scintillation well enough to generate realistic synthetic scintillationSynthesize scintillation to test tracking loop strategies Design phase tracking loops for operation in scintillation

Long-term Goals

Eliminate frequency unlock Minimize cycle slips and generally reduce phase errors

Strategy

Slide7

Analyze:

The Empirical Scintillation Library

Canonical fades

Slide8

Fading

Interpreted on the Complex Plane

Slide9

Model: Distill Scintillation Down to Essential Characteristics for Carrier Tracking

Standard statistical

analysis techniques

DPSK bit error prediction with Rice and 2

nd

-order Butterworth models

Slide10

Synthesize: Turn the Model Around

Slide11

Scintillation Simulator Implementation

Slide12

Hardware-in-the-loop

Scintillation Robustness Evaluation

Scintillation Simulator

Simulated time history

GNSS Signal Simulator

GNSS Receiver

Phase difference time history

Slide13

Design:

Scintillation-hardened Tracking Loops

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.

GOAL: Ts > 240 seconds for

{S

4

= 0.8,

0

= 0.8 sec., C/N0 = 43 dB-Hz}

(a factor of 10 longer than current best)

Slide14

Traditional Approach to Carrier Modeling

Slide15

A New Approach to Carrier Modeling

Slide16

A Multiple-Model Approach to Data Bit Estimation

Slide17

The GPS Assimilator

The GPS Assimilator modernizes and makes existing GPS equipment resistant to jamming, spoofing, and scintillation without requiring hardware or software changes to the equipment

A Backward-Compatible Way to Harden Existing UE Against Scintillation

Slide18

All digital signal processing implemented in C++ on a high-end DSPMarginal computational demands:Tracking: ~1.2% of DSP per channelSimulation: ~4% of DSP per channelFull capability: 12 L1 C/A & 10 L2C tracking channels8 L1 C/A simulation channels1 Hz navigation solution Acquisition in background

GPS Assimilator Prototype

Slide19

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 severityThe triple accurately predicts For carrier tracking, scintillation modeling & simulation can be boiled down to two parameters: S4 & τ0A hardware-in-the-loop scintillation testbed has been built and validatedCarrier tracking techniques inspired by the proposed model promises to extend

Slide20

Acknowledgements

CASES sensor development funded by STTR grant through AFOSR via ASTRA LLC

Adaptation of CASES sensor for Antarctic deployment funded by ASTRA LLC

Slide21

Model: Link Cycle Slips to Differentially-Detected Bit Errors

Slide22

Amplitude Distribution:

Rice distribution

applies

p(|z(t)|) can be summarized by the S

4

index

Slide23

Autocorrelation Function:Empirical Spectrum vs. Models

2

nd

-order Butterworth autocorrelation model

applies

R

(

) can be summarized by

0

Slide24

Slide25

Slide26

Slide27

Slide28


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