Navigation Accuracy and Interference Rejection for …...Navigation Accuracy and Interference...

Navigation Accuracy and Interference Rejectionfor an Adaptive GPS Antenna Array

David S. De Lorenzo, Jason Rife, Per EngeStanford University GPS Lab

Dennis AkosUniversity of Colorado

05 June 2006

The authors gratefully acknowledge the support of the JPALS Program Office, andthe Naval Air Warfare Center Aircraft Division through contract N00421-01-C-0022.

6/13/2006 Stanford University JPALS Research 2

Constrained Adaptive Processing

• JPALS has stringent limits on pseudorange & carrier-phase errors– Required to meet carrier-landing accuracy limits.

• GPS antennas introduce distortion on received signals– Apparent as deterministic pseudorange and carrier phase biases– Dependent on the incoming signal line-of-sight.

• JPALS will likely require multi-element STAP algorithms to improve C/No under jamming & RFI conditions.

• STAP algorithms can introduce additionalpseudorange and carrier phase biases.

Goal: Through temporal & spatialconstraints on a STAP algorithm,

move down & left in the trade space,to a point where deterministic

pseudorange & carrier phase correctionsbased on signal LOS can be applied.


Outline

• Software tools for signal simulation & tracking– Signal simulator

• C/A or P-code signal generator that includes antenna distortion effects– Software receiver

• Tracks a wide range of GNSS signals – GPS C/A & P-code, Galileo L1 & E6

• Includes multi-antenna and space-time adaptive signal processing

• Verification of software receiver & multi-signal tracking performance

• Research methodology:– Characterize biases vs. RFI rejection– Evaluate different compensation schemes

• Preliminary results– FRPA vs. CRPA biases and interference rejection


Stanford HW & SW Development

Analog front-end4-channel GP2015 with10 MHz common clock

Data collection computer(2) ICS-650 cards

sampling at 5-65 MHzand 12-bit A/D resolution

Software Receiverall-in view, multi-signal

GNSS receiverwith STAP array

processing

7-element arrayrectangular patch

antennas manufacturedat Stanford University

2m high-gain dish* Possibility of including data from OSU’s

multi-element antenna array.

HP VectorSignal

Analyzer


Software-Based Signal Simulator

Bandlimited WGN& CW interference

C/A & “P” code1.023 & 10.23 Mchip/sec

Front-endA/D

Front-endA/D

…

…

1480 1500 1520 1540 1560 1580 1600 1620 1640 1660 16800

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Gai

n

Antenna Gain Response for PRN #1 [Az = 0 deg, El = 40 deg]

Antenna #1Antenna #2Antenna #3Antenna #4Antenna #5Antenna #6Antenna #7

Front-end BW ~19MHz

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0

50

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250

Frequency (MHz)

Pha

se

Antenna Phase Response for PRN #1 [Az = 0 deg, El = 40 deg]


Front-end BW ~19MHz

• Gain/phase data for each look direction (10 S/V constellation) and antenna (7 rectangular patches)

– Data courtesy Ung-Suok Kim

Gain/phase response for PRN #1[Azimuth = 0°, Elevation = 40°]


Signal Generation at Intermediate Freq.

• Received signal at master element:

• Mixing signal:

• Signal after LPF:

• Received signal at subsidiary element:

• Signal after mixing & LPF:

( ) ( ) ( )[ ]θπττ ++⋅−⋅−⋅ tfftxtDP DLS 12cos2

( ) ( ) ( )( )[ ]θπττ +Δ++⋅−Δ+⋅−Δ+⋅ ttffttxttDP DLS 12cos2

( )[ ]tff IFL −⋅ 12cos2 π

( ) ( ) ( )[ ]θπττ ++⋅−⋅−⋅ tfftxtDP DIFS 2cos

( ) ( ) ( ) ( )[ ]tfftffttxttDP DLDIFS Δ++++⋅−Δ+⋅−Δ+⋅ 122cos πθπττ


Signal Generation w/ Antenna Distortion

s(t) and gain/phase data are antenna & S/V specific

Gain/phase distortion data available from HFSS simulation

– Verified by comparison to anechoic chamber testing


( )ts

( )tsout

fft ( )fS

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Gai

n



Front-end BW ~40MHz

0 5 10 15 20 25 30 35 40Frequency (MHz)

Pow

er/fr

eque

ncy

(dB

/Hz)

Power Spectral Density Estimate via Welch

⊗ 1−fft

-1.5 -1 -0.5 0 0.5 1 1.50

0.5

1

1.5

2

2.5

3

3.5

4 x 104 P-code Correlation Peak Distortion - PRN #1

Code Offset (chips

Cor

rela

tor O

utpu

t

-1.5 -1 -0.5 0 0.5 1 1.50

0.5

1

1.5

2

2.5

3

3.5

4x 104 P-code Correlation Peak w/o Distortion - PRN #1

Code Phase (chips)

Cor

rela

tion

Out

put

Autocorrelation of s(t)

Autocorrelation of sout(t)

1450 1500 1550 1600 1650 1700-50

0

50

100

150

200

250

Frequency (MHz)

Pha

se



Front-end BW ~40MHz


Standard Satellite Constellation

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ain



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n



Front-end BW ~40MHz

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Frequency (MHz)

Gai

n



Front-end BW ~40MHz

PRN #1

PRN #2

PRN #3

PRN #4PRN #5

PRN #6

PRN #7

PRN #8PRN #9 PRN #10


0 5 10 15 20 25 30 35 40Frequency (MHz)

Pow

er/fr

eque

ncy

(dB

/Hz)


Wideband Jammer Signal Generation at IF

( )tj

( )tjout

fft ( )fJ

1480 1500 1520 1540 1560 1580 1600 1620 1640 1660 16800

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Frequency (MHz)

Gai

n



Front-end BW ~40MHz

⊗ 1−fft

( ) ( ) ( )[ ]∑ Δ++Δ+′++⋅i

JLJJIFJ tffttftffPii 1

2 22cos2 ππ

Gain/phase distortion data are currently not available ( ) ( )tjtj out≡

• For each jammer – six swept sinusoids cover frequency band from ~0 Hz to ~fs/2

• Amplitude scaled as needed to achieve desired J/S ratio


Satellite & RFI Constellation

8030010

302709

202408

702107

601506

201205

50904

40603

30302

4001

ElevationAzimuthPRN

102706

02505

02254

01203

0452

001

ElevationAzimuthRFI

Bandlimited WGNand/or

CW interference


Multi-signal Software GNSS Receiver

• Software Receiver tracks a wide range of GNSS signals, runs in MATLAB– GPS C/A and pseudo-P-codes– Galileo L1-B/C and E6-B/C codes

• Includes multi-antenna and space-time adaptive signal processing

• Supports arbitrary sampling frequency, intermediate frequency, data format, etc.– The ideal s/w rcvr is fast, flexible, & uncomplicated

You can have 2 out of 3!!


Software Receiver Block Diagram

WeightControl

Algorithm

Correlatorsintegrate& dump

TrackingLoops

CarrierNCO

CodeNCO

cos

C/No Estimator

Pseudorange & Carrier-phaseBias Estimator

carrierwipeoff

code wipeoff

Early

Prompt

LateFFT-basedCoherent

Acquisition

sin

Weight control processing supportsFRPA & CRPA antennas and

adaptive LMS & Applebaum arrays


Software Receiver Flow Chart

For each tracking channel:1ms sample buffer alignedw/ start of spreading code

Code/carrier phase alignedw/ first sample of 1ms epoch

Discrete operation from stored data sample indexing & alignment

Noncoherent or coherentintegration depends onnav. data bit alignment

This loop runs ona 1ms schedule

The devil isin the details


Epoch-based Tracking of GNSS Codes

Code start tracked ineach ~1ms data epoch

Problems:– If fs is not an exact multiple of

1000Hz, the extra fractional sample causes a code-phase ramp error

– Approaching/receding satellites will cause code wrap (phase skew), leading to dropped sample epochs

PRN1

PRN2

PRN3

Frame-based data epochs

Multi-epoch tracking window

Code start tracked in the~5ms active tracking window

Active window

Active window

PRN1

PRN2

PRN3

Solutions:– Sample index for each

tracked PRN aligns with 0 code phase

– Logic is used to control sample index over-run or under-run


S/W Rcvr Verification:GPS C/A Code Tracking – Real Data

• All-in-view tracking of GPS C/A code signals• Software

receiver is acombination ofin-house codeand structuresfrom Kai Borreof AalborgUniversity

0 500 1000 1500 2000 2500-0.2

0

0.2

0.4

0.6

0.8

1

Navigation Data Message - PRN 3

Time (ms)

Data source: NordNav Rcvr & Dennis Akos

0 500 1000 1500 2000 2500

1700

1750

1800

Doppler Frequency

Time (ms)

Dop

pler

freq

uenc

y (H

z)

0 500 1000 1500 2000 2500211

211.5

212

212.5

213

213.5

214

214.5Position of the C/A Code Start

Time (ms)C

/A c

ode

star

t (ch

ips)

0 500 1000 1500 2000 250030

35

40

45

50

55

60Filtered C/No

Time (ms)

C/N

o (d

B-H

z)Tracking mode transitions


S/W Rcvr Verification:C/A Code Acquisition – High-Gain Data

• Acquisition of GPS C/A code signal collected with SRI Dish– fS = 124.5 MHz– fIF = 43.08 MHz– Data courtesy

Grace Gao ofthe StanfordGPS Lab

Why is thecorrelation

peak rounded? 106.5 107 107.5 108 108.5 109 109.50

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1

C/A Code Correlation - PRN #8 for 1ms

Code Phase (chips)

Cor

rela

tion

Func

tion

(nor

mal

ized

)


106.5 107 107.5 108 108.5 109 109.50

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1


Code Phase (chips)

Cor

rela

tion

Func

tion

(nor

mal

ized

)




A band-passfilter was appliedto the data before

processing.


105.5 106 106.5 107 107.5 108 108.5 109 109.50

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0.8

1


Code Phase (chips)

Cor

rela

tion

Func

tion

(nor

mal

ized

)




This is thecorrelation

to unfiltereddata.


-400 -200 0 200 400 600 800 1000 1200 1400 16000

0.2

0.4

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1

Code Correlation - Galileo L1/B for 1ms

Code Phase (chips)

Cor

rela

tion

Func

tion

(nor

mal

ized

)

Code CorrelationGalileo L1/B for 1msPeak in 1st acq. blockDoppler= 2200 HzCode Ph.= 610.4 chipsCPPR= 11.7CPPM= 332.3

– Galileo L1-B/C and E6-B/C codes determined by Grace Gao of the Stanford GPS Lab

S/W Rcvr Verification:Galileo L1/B Code Acquisition – Real Data

608 608.5 609 609.5 610 610.5 611 611.5 612 612.5 6130

0.2

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1


Code Phase (chips)

Cor

rela

tion

Func

tion

(nor

mal

ized

)


S/W Rcvr Verification:Galileo L1/C Code Tracking – Real Data

• Tracking of Galileo L1/C BOC(1,1) pilot signal• No modification

to s/w rcvrexcept newcode generators

• GalileoL1-B/C andE6-B/C codesdetermined byGrace Gao ofthe StanfordGPS Lab

0 200 400 600 800 1000 1200 1400 1600 1800-0.2

0

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1

Navigation Data Message - Galileo L1/C

Time (ms)

Data source: Galileo L1 w/ SRI Dish & VSA by Grace Gao

0 500 1000 1500

2140

2160

2180

2200

2220

2240

2260

Doppler Frequency

Time (ms)

Dop

pler

freq

uenc

y (H

z)

0 500 1000 1500604

605

606

607

608

609

610

611Position of the Galileo Code Start

Time (ms)

Gal

ileo

code

sta

rt (c

hips

)

200ms secondary code


S/W Rcvr Verification:GPS P-Code Tracking – Simulated Data

• GPS pseudo-P-code signals, 10.23 Mchips/sec• Signals have

sufficient BWto elucidateeffects due todifferentialantenna gainand phaseresponses– fS = 80 MHz– fIF = 20 MHz

0 500 1000 1500 2000-0.2

0

0.2

0.4

0.6

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1

Navigation Data Message - PRN 6

Time (ms)

Data source: Multi-Antenna Signal Simulator

0 500 1000 1500 2000

160

180

200

220

240

260

280

Doppler Frequency

Time (ms)

Dop

pler

freq

uenc

y (H

z)

0 500 1000 1500 20005444.35

5444.4

5444.45

5444.5

5444.55Position of the P-Code Start

Time (ms)

P-c

ode

star

t (ch

ips)

0 500 1000 1500 200030

35

40

45

50

55

60Filtered C/No

Time (ms)

C/N

o (d

B-H

z)


S/W Rcvr Verification:CRPA Processing – Simulated Data

• 7-element CRPA with gradually decreasing C/No• No special

receiverprocessingfor low C/No

• Loss-of-lockbelow C/Noof ~25 dB-Hz

0 2000 4000 6000 8000-90

-45

0

45

90PLL Discriminator

Time (ms)

Pha

se o

ffset

(deg

rees

)

0 2000 4000 6000 8000-500

0

500DLL Discriminator

Time (ms)

Cod

e of

fset

(m)

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

10

20

30

40

50

60Filtered C/No

Time (ms)

C/N

o (d

B-H

z)

FRPACRPA

Increasing noise power

Loss-of-lock


Navigation Errors due to Multi-Antenna Arrays

Common-mode: errors areshared by all signals on aparticular antenna channel

Non-common-mode: errorsare a function of satellite #

az/el-dependent(also present for single-antenna GPS)

Do errors introduce a pseudorange or carrier-phase bias? What RFI or noise

rejection performance is attainable?Algorithm: errors may beintroduced by the weightcontrol algorithm itself

LO

Σ TrackingLoops PVT

code replica

IMUattitude

ephemeris

WeightControl

Algorithm

tracking reference

carrier replica

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

LO


code replica

IMUattitude

ephemeris

WeightControl

Algorithm

tracking reference


code replica

IMUattitude

ephemeris

WeightControl

Algorithm

tracking reference

carrier replica

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&QHatke, 1998Fante & Vaccaro, 2000Gupta & Moore, 2001Moore, 2002Fante, et.al., 2004McGraw, et.al., 2004Hatke & Phuong, 2004Kim, et.al., 2004Kim, 2005

Pseudorange/Carrier-phase errors


Methodology – Biases vs. RFI Rejection

• Develop adaptive algorithms that balance noise/RFI rejection against pseudorange & carrier-phase errors – through constraints on weight adjustment– End-to-end: from signal reception through the receiver

tracking loops to the pseudorange and carrier phase estimates

Goal: Through temporal & spatialconstraints on a STAP algorithm,

move down & left in the trade space,to a point where deterministic

pseudorange & carrier phase correctionsbased on signal LOS can be applied.


-1.5 -1 -0.5 0 0.5 1 1.50

1

2

3

4

5

6

7x 104

Code Offset (chips)

Cor

rela

tion

Out

put

PRN #1PRN #2PRN #3PRN #4PRN #5PRN #6PRN #7PRN #8PRN #9PRN #10

0 200 400 600 800 1000

-6

-4

-2

0

2

4

6

Time (ms)

Car

rier P

hase

Err

or (c

m)

Carrier Phase Estimates vs. Truth Values

PRN 1PRN 2PRN 3PRN 4PRN 5PRN 6PRN 7PRN 8PRN 9PRN 10PRN 11

Preliminary Results:GPS P-Code w/ Antenna Distortion

• Simulated data and complete visibility of tracking output allow comparison between predicted and true pseudorange and carrier phase values

Carrier phase biases Pseudorange bias – distortionof P-code correlation peak

Test satellite – zero bias

6/13/2006 Stanford University JPALS Research 2635 40 45 50 55 60

-6

-4

-2

0

2

4

6

C/No (dB-Hz)

Car

rier P

hase

Erro

r (cm

)C

arrie

r-ph

ase

Erro

rs (c

m)

35 40 45 50 55 60-5

-4

-3

-2

-1

0

1

C/No (dB-Hz)

Cod

e P

hase

Erro

r (m

)Ps

eudo

rang

e Er

rors

(m)

Preliminary Results:FRPA vs. CRPA Processing – no RFI

• Code/carrier errors are not affected by deterministic array processing

• C/No enjoys healthy boost under these conditions

0 200 400 600 800 1000 1200 1400 1600 1800 200035

40

45

50

55

60

Time (ms)

C/N

o (d

B-H

z)

Filtered C/No

PRN 1PRN 2PRN 3PRN 4PRN 5PRN 6PRN 7PRN 8

FRPA CRPA


Future Work – Exploring the Trade Space

1. Simulate signals with desired characteristics (C/No, J/S ratio, antenna distortion, etc.)

2. Track with Software Receiver (FRPA, CRPA, LMS, Applebaum processing)

3. Characterize C/No vs. pseudorange and carrier phase biases for various scenarios

4. Apply compensation schemes

Spatial Constraints

Temporal Constraints

DistortionC/NoJ/S level

ApplebaumLMSCRPAFRPA


Conclusions

• Signal simulator captures parameters of interest– Broadband RFI, antenna gain/phase variation based on

detailed characterization models

• Software receiver supports adaptivealgorithms and estimation ofpseudorange & carrier phase errors

• Methodology is yielding data abouttradeoffs between RFI rejection andcode/carrier estimation errors

• Tools will support implementationand testing of antenna compensation schemes

Backup


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Pow

er/fr

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(dB

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Pha

se



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se



Front-end BW ~40MHz

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Front-end BW ~40MHz

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-40

-20

0

20

40

60

80

100

120

140

Frequency (MHz)

Pha

se



Front-end BW ~40MHz

PRN #1

PRN #8

PRN #10

Antenna Distortion Effects (2)

• Fourier transform of complex signal multiplied by antenna response characteristics

– Gain/phase data re-centered at IF

• Inverse Fourier transform back to time domain

• Real-valued samples stored to disk

• Gain/phase distortion data available from HFSS simulation

– Verified by comparison to anechoic chamber testing



Wideband Jammer Signal Generation at IF

• For each jammer – six swept sinusoids cover frequency band from ~0 Hz to ~fs/2– Pseudo-random

center frequencies– For fs = 80 MHz and

fIF = 20 MHz, eachwave covers 10 MHz

• Amplitude scaled asneeded to achievedesired J/S ratio

( ) ( ) ( )[ ]∑ Δ++Δ+′++⋅i

JLJJIFJ tffttftffPii 1

2 22cos2 ππ

0 5 10 15 20 25 30 35 40Frequency (MHz)

Pow

er/fr

eque

ncy

(dB

/Hz)



Spatial & Temporal D.O.F

• Spatial: geometry of gain pattern, width (selectivity) of beams/nulls

• Temporal: spectral response of array, nulling of wideband signals

LMS WeightAdjust Circuit

Δw11

Δw21

s(t)

r(t) - LMS referenceΣ+

–

Σ

w12

w22

Σ TrackingLoops

replica

ε

Spat

ial

Temporal

from Widrow & Stearns, Adaptive Signal Processing (1985)


slave

master

SamplingClock

SynchronizationCables

PCI Bus

IDEHD

NovAtelSuperStar

Analog line

Host PC

Serial cable

NovAtelSuperStar

power/ground wiresand buffer circuitsleft off for clarity

InterferenceGenerator

4 Antennas4 SuperStars

2 ICS-650 cardsCommon Clock

NovAtelSuperStar

GPS Display

ICS-650

ICS-650

NovAtelSuperStar

10 MHzClock

Analog line

Analog line

Analog line

ICS-65012-bit A/D5-65 MHz2-channel

SuperStar IIZarlink GP20154.309 MHz IF

4-Channel Test Hardware – Schematic


Proposed 1st-gen Hardware Implementation

LO

Σ TrackingLoops

PVT

code replica

AdaptiveWeight

Algorithm

LMS reference

carrier replica

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

S/V-specific signal processing

LMS-based AdaptiveBlind Beamforming

Multi-Element GPS ASIC


Software Receiver Block Diagram

WeightControl

Algorithm

Correlatorsintegrate& dump

TrackingLoops

CarrierNCO

CodeNCO

cos

C/No Estimator

Pseudorange & Carrier-phaseBias Estimator

carrierwipeoff

code wipeoff

Early

Prompt

LateFFT-basedCoherent

Acquisition

sin

Let’s focus on thisblock for a moment.


Generic Adaptive Antenna Array

from Compton, Adaptive Antennas (1988)

Σ

FeedbackControl

PerformanceIndex

ArrayOutput

Gain and PhaseAdjustment

Maximize SINR at the array output(e.g., Applebaum, 1976; Frost, 1972)

Minimize MSE between the actualarray output and the ideal array output

(e.g., Widrow, et. al., 1967)

Optimization Criteria

• Using feedbackto optimize someperformance index



code replica

IMUattitude

ephemeris

WeightControl

Algorithm

replicated signal

carrier replica

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Adaptive Array Processing for GPS

covarianceestimate



code replica

IMUattitude

ephemeris

WeightControl

Algorithm

replicated signal

carrier replica

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q


Deterministic CRPA: signal arrivaland platform/array orientation

Adaptive w/ maximum SINR, e.g. Applebaum: signalarrival, platform/array orientation, and SINR metric

Adaptive w/ minimum MSE, e.g. Widrow LMS:ideal array output reference signal and SINR metric

covarianceestimate

e.g., Hatke, 1998; Nicholson, et al., 1998; Fante & Vaccaro, 2000;Gupta & Moore, 2001;Hatke & Phuong, 2004; Fante, et al., 2004

e.g., Gecan & Zoltowski, 1995



code replica

IMUattitude

ephemeris

WeightControl

Algorithm

replicated signal

carrier replica

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q

Front-end A/D I&Q


But what happens when there are

errors introduced by the hardware

that are not completely mitigated

by software or calibration?

Antennaphase-center

and groupdelay effects

Front-endfilter and

timingeffects

Navigation Accuracy and Interference Rejection for …...Navigation Accuracy and Interference...

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