Robust adaptive beamforming based on interference covariance matrix sparse reconstruction

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	Robust adaptive beamforming based on interference covariance matrix sparse reconstruction
	Gu, Yujie ; Goodman, Nathan A. ; Hong, Shaohua ; Li, Yu ; Hong SH(洪少华)
刊名	http://dx.doi.org/10.1016/j.sigpro.2013.10.009
	2014
关键词	SOURCE LOCALIZATION SENSOR ARRAYS PURSUIT
英文摘要	National Natural Science Foundation of China [61102134]; Adaptive beamformers are sensitive to model mismatch, especially when the desired signal is present in the training data. In this paper, we reconstruct the interference-plus-noise covariance matrix in a sparse way, instead of searching for an optimal diagonal loading factor for the sample covariance matrix. Using sparsity, the interference covariance matrix can be reconstructed as a weighted sum of the outer products of the interference steering vectors, the coefficients of which can be estimated from a compressive sensing (CS) problem. In contrast to previous works, the proposed CS problem can be effectively solved by use of a priori information instead of using l(1)-norm relaxation or other approximation algorithms. Simulation results demonstrate that the performance of the proposed adaptive beamformer is almost always equal to the optimal value. (C) 2013 Elsevier B.V. All rights reserved.
语种	英语
出版者	ELSEVIER SCIENCE BV
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/92723]
专题	信息技术－已发表论文
推荐引用方式 GB/T 7714	Gu, Yujie,Goodman, Nathan A.,Hong, Shaohua,et al. Robust adaptive beamforming based on interference covariance matrix sparse reconstruction[J]. http://dx.doi.org/10.1016/j.sigpro.2013.10.009,2014.
APA	Gu, Yujie,Goodman, Nathan A.,Hong, Shaohua,Li, Yu,&洪少华.(2014).Robust adaptive beamforming based on interference covariance matrix sparse reconstruction.http://dx.doi.org/10.1016/j.sigpro.2013.10.009.
MLA	Gu, Yujie,et al."Robust adaptive beamforming based on interference covariance matrix sparse reconstruction".http://dx.doi.org/10.1016/j.sigpro.2013.10.009 (2014).