Robust adaptive beamforming based on sparse reconstruction using a non-convex optimisation algorithm

A novel robust adaptive beamforming technique is proposed to solve the problem of performance degradation with one single snapshot. A sparse signal recovery model under the non-convex optimisation framework is first established, which dispenses with the mismatched sample covariance matrix, an indisp...

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Veröffentlicht in:	Electronics letters Jg. 52; H. 19; S. 1584 - 1586
Hauptverfasser:	Chen, Pei, Zhao, Yongjun, Liu, Chengcheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 15.09.2016
Schlagworte:	Adaptive algorithms Algorithms Antennas and propagation array signal processing Beamforming concave programming covariance matrices Electronics Exact solutions iterative algorithm iterative methods Mathematical analysis mismatched sample covariance matrix multiplier nonconvex optimisation algorithm Optimization p‐shrinkage operator robust adaptive beamforming technique Robustness signal reconstruction sparse reconstruction sparse signal recovery model covariance matrices iterative methods multiplier sparse reconstruction iterative algorithm mismatched sample covariance matrix nonconvex optimisation algorithm sparse signal recovery model signal reconstruction robust adaptive beamforming technique concave programming array signal processing p-shrinkage operator
ISSN:	0013-5194, 1350-911X, 1350-911X
Online-Zugang:	Volltext
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Zusammenfassung:	A novel robust adaptive beamforming technique is proposed to solve the problem of performance degradation with one single snapshot. A sparse signal recovery model under the non-convex optimisation framework is first established, which dispenses with the mismatched sample covariance matrix, an indispensable part of most existing beamformers. Then, an iterative algorithm is designed to solve the optimisation problem by using the p-shrinkage operator and the alternating direction method of multipliers. The iteration steps are closed form and convenient to apply in practice. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0013-5194 1350-911X 1350-911X
DOI:	10.1049/el.2016.1810