A Class of Robust Adaptive Beamforming Algorithms for Coherent Interference Suppression

Zhang, L. and Liu, W. (2012) A Class of Robust Adaptive Beamforming Algorithms for Coherent Interference Suppression. In: 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO), Bucharest, Romania, 27-31 Aug 2012, pp. 1349-1353. ISBN 9781467310680

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Publisher's URL: http://ieeexplore.ieee.org/document/6334243/

Abstract

Based on the uniform linear array (ULA) and the spatial-smoothing technique, a robust beamforming problem for the reception of coherent signals is addressed and a forward-only (FO) beamformer is proposed based on worst-case optimization by considering both the steering vector and the correlation matrix errors. It is then extended to the forward-backward (FB) case with an improved performance. By introducing a preprocessing matrix, real-valued closed-form solutions are then derived with the same performance as in the FB case, but with much lower computational complexity. Simulations verified the effectiveness of the proposed algorithms.

Item Type:Conference Proceedings
Keywords:Adaptive signal detection, array signal processing, coherence, computational complexity, correlation methods, interference suppression, matrix algebra, optimisation, FB beamformer, FO beamformer, ULA, coherent interference suppression, coherent signal reception, computational complexity, correlation matrix errors, forward-backward beamformer, forward-only beamformer, performance improvement, preprocessing matrix, real-valued closed-form solutions, robust adaptive beamforming algorithms, robust beamforming problem, spatial-smoothing technique, steering vector, uniform linear array, worst-case optimization, array signal processing, arrays, correlation, interference, robustness, signal to noise ratio, vectors.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Zhang, Professor Lei
Authors: Zhang, L., and Liu, W.
College/School:College of Science and Engineering > School of Engineering
ISSN:2219-5491
ISBN:9781467310680

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