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Review of user parameter-free robust adaptive beamforming algorithms
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2009 (English)In: Digital signal processing (Print), ISSN 1051-2004, E-ISSN 1095-4333, Vol. 19, no 4, 567-582 p.Article, review/survey (Refereed) Published
Abstract [en]

This paper provides a comprehensive review of user parameter-free robust adaptive beamforming algorithms. We present the ridge regression Capon beamformers (RRCBs), the mid-way (MW) algorithm, and the convex combination (CC) as well as the general linear combination (GLC) approaches. The purpose of these methods is to mitigate the effect of small sample size and steering vector errors on the standard Capon beamformer (SCB). We also present sparsity based iterative beamforming algorithms, namely the iterative adaptive approach (IAA), maximum likelihood based IAA (referred to as IAA-ML) and M-SBL (multi-snapshot sparse Bayesian learning), which exploit sparsity to estimate the signal parameters. We provide a thorough evaluation of these beamforming methods in terms of power and spatial spectrum estimation accuracies. output signal-to-interference-plusnoise ratio (SINR) and resolution under various scenarios including coherent, non-coherent and distributed sources, steering vector mismatches, snapshot limitations and low signal-to-noise ratio (SNR) levels. Furthermore, we discuss the computational complexities of the algorithms and provide insights into which algorithm is the best choice under which circumstances.

Place, publisher, year, edition, pages
2009. Vol. 19, no 4, 567-582 p.
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:uu:diva-104508DOI: 10.1016/j.dsp.2009.02.001ISI: 000265997700005OAI: oai:DiVA.org:uu-104508DiVA: diva2:219870
Available from: 2009-05-28 Created: 2009-05-28 Last updated: 2017-12-13Bibliographically approved

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Stoica, Peter

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