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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Bibliographic Details
Published in:Electronics letters Vol. 52; no. 19; pp. 1584 - 1586
Main Authors: Chen, Pei, Zhao, Yongjun, Liu, Chengcheng
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 15.09.2016
Subjects:
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 Access:Get full text
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Summary: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.
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ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2016.1810