BYU

Auxiliary Antenna Assisted Interference Cancellation for Radio Astronomy Imaging Arrays

Brian Jeffs and Karl Warnick

August 21, 2002

References

1. J. Raza, A-J Boonstra and A-J van der Veen, “Spatial Filtering of RF Interference in Radio Astronomy,” IEEE SP Letters, vol. 9, no. 2, Feb. 2002.

2. A. Leshem, A-J van der Veen, “Radio-Astronomical Imaging in the Presence of Strong Radio Interference,” IEEE Trans. On Information Theory, vol. 46, no. 5, Aug. 2000.

Summary

Goal is to remove strong interference component from synthesis array covariance estimate, Rs.

Satellite signals: GLONASS, Iridium

Direct path dominant interference, low rank Ri.

Adaptive array beamforming not applicable.

Subspace projection methods preserve structure of Rs.

Use of low gain auxiliary antennas in existing and new algorithms yields improved cancellation.

Augmented Imaging Array Structure

GLONASSsatellite

. . .Auxiliaryantennas

Primary Antennas

x1[n] xMp[n] xM[n]

xp[n] xa[n]

x[n]

][][1ˆ

1

0nn

NH

N

nxxR

Possible Augmented VLA Configuration

Auxiliaries are 3m dishes, inexpensive LNAs and receiver electronics.

Existing dish (approximate location shown) is used for RFI satellite tracking studies – could be used as auxiliary.

Auxiliaries could be connected to unused correlator inputs (e.g. out-of-service antennas).

Array Covariance Matrix is the Basis for Synthesis Imaging

Elements of Rs are image frequency domain samples.

Earth rotation moves baselines for new Rs, more frequency samples.

Interference effects must be removed from Rs directly, beamforming to place nulls is not possible since correlations from all array pairs are needed.

(b) VLA frequency samples with Earth Rotation(d) VLA frequency sample snapshot

Subspace Projection Approach (Leshem & van der Veen, Raza et al)

Interference component of R spans a subspace of rank Q = number of interferers.

aq is array response to qth interferer with power .

Find a projection operator orthogonal to Ri

].,,diag[ ],,[,

,ˆ

2211 QQ

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is

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i

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0RP

)(ˆˆ

,

Use this in imaging.No interferer left!!

2q

Methods of computing P

If array is calibrated and interference direction known:

If ISNR >> 0 dB at feeds and direction unknown:

If interference moves, use short-term integration for

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Hss

sisi

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)(

,]|[]|[ˆ

P

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, and ˆkk PR

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1

1ˆ

Problems: Bias

Projection biases signal subspace, Cannot invert because P is singular.

Solution (Raza et al): use smoothing over short-term integrations to build rank

Now

.)(}ˆ{ PRRPR ssE

.1ˆ1 1

1

1

1,

PPRPPRPP

K

kKkk

sK

kk KK

.}ˆ{ RRR ssE

Problems: Poor Subspace Estimates(main focus of this work)

Signal is many dB below noise.

High gain antennas help reject interferer, but make subspace estimation hard. Often INR 0 dB at feed.

Gain increases SIR by 70 dB.

Sometimes the signal or noise is identified as the interferer, and is projected out.

Poor interference subspace estimate leads to poor interference rejection from projection matrix P.

Solution to Bad Subspace Estimates:Use Auxiliary Antennas

Array consists of high gain “primaries” and low gain “auxiliaries,” perhaps steered to interference,

Auxiliary antennas see high ISNR to guide subspace estimation for the primary array.

Four different approaches for computing P have been evaluated.

.,][

][][

aaap

papp

a

p

n

nn

RR

RRR

x

xx (1)

1. Conventional Full Array Subspace Projection with Auxiliaries

Use the full array, including auxiliaries, with no distinction as to antenna type.

Compute a truncated projection matrix:

Significant performance improvement over using primaries only. Handles weaker interferers.

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pM

HssMB

sisi

MM

UU

UUUU

p

p

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0II

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R

ˆˆ

:,

,)(

,]|[]|[ˆ

Classical MSC beamformer:

Form MSC separately with each primary antenna:

Covariance is :

2. Array Multiple Sidelobe Canceller (AMSC)

)column (

1

, ][][][

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aH

mp nnxny

RRw

xw

][],[][ † nn aapa xRRIy

],[

,

†

†

aapaC

apaapappHCCy

RRIP

RRRRRPPR

(2)

Array Multiple Sidelobe Canceller (cont.)

Neglect estimation error and signal term in auxiliaries.

Thus, our estimate is:

Low risk of signal capturing the interference subspace.

HCCs PRPR ˆˆ

becomes (2) (1), using ,,For pa MMQ

spp

iap

iaa

ipa

ipp

sppy

R

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†)(][

3. Auxiliary Assisted Cross Subspace Projection

Projection uses only cross correlations between primaries and auxiliaries to strongly emphasize the interferer, increase ISNR.

Use only the primaries in final estimate:

Best overall performance.

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s PRPR ˆˆ

HssD

Hpa

)(

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VUSR

VLA in Compact Configuration and Source Geometry

VLA Simulated Examples: Scenario 1, Stationary Interferer, 1 Aux.

1612 MHz with one omni 0 dB aux., 200 Jy source with one GLONASS interferer.

Scenario 2: Two Stationary GLONASS Interferers, 2 Auxiliaries

VLA, 1612 MHz with two 3m aux. dishes, 200 Jy OH source with two GLONASS interferers.

Scenario 3,Two Orbiting Interferers, 2 Auxiliaries

VLA, 1612 MHz with two tracking 3m dish auxiliaries, 20 Jy OH source with two GLONASS interferers. Short-time integration and bias removal.

Conclusions

In all cases, use of auxiliary antennas dramatically improved interference rejection.

Auxiliary assisted cross subspace projection performed best with weak interferer. No jammer detection needed.

AMSC has lowest covariance estimation error.

Auxiliary antennas are low cost, and can be added to existing arrays with modest investment.

Scenario 1, SIR

Scenario 1 MSE

Scenario 2, SIR

Scenario 2, MSE

Scenario 3, SIR

Scenario 3, MSE