2012Unpublished venueRequires access

Recursive updating algorithm for robust Capon beamforming with steering vector mismatches

E. A. Mavrychev

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Abstract

A new algorithm for robust adaptive beamforming is designed in this paper. It is assumed that steering vector is mismatches due to propagation effects, array calibration errors, etc. The proposed algorithm is based on recursive updating of sample covariance matrix and adaptive diagonal loading. New implementation of robust Capon beamformer (RCB) is more robustness to non-stationary interference environment. Simulation results confirm efficiency of recursive robust adaptive beamformer.

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What this paper is about

A new algorithm for robust adaptive beamforming is designed in this paper. It is assumed that steering vector is mismatches due to propagation effects, array calibration errors, etc. The proposed algorithm is based on recursive updating of sample covariance matrix and adaptive diagonal loading. New implementation of robust Capon beamformer (RCB) is more robustness to non-stationary interference environment. Simulation results confirm efficiency of recursive robust adaptive beamformer.

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Available abstract

A new algorithm for robust adaptive beamforming is designed in this paper. It is assumed that steering vector is mismatches due to propagation effects, array calibration errors, etc. The proposed algorithm is based on recursive updating of sample covariance matrix and adaptive diagonal loading. New implementation of robust Capon beamformer (RCB) is more robustness to non-stationary interference environment. Simulation results confirm efficiency of recursive robust adaptive beamformer.

Key concepts: Capon, Adaptive beamformer, Robustness (evolution), Covariance matrix, Algorithm, Diagonal, Beamforming, Computer science

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