首页|A Two-Stage Nonlinear Shrinkage of the Sample Covariance Matrix for Robust Capon Beamforming

A Two-Stage Nonlinear Shrinkage of the Sample Covariance Matrix for Robust Capon Beamforming

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When the number of snapshots used to estimate the Sample covariance matrix (SCM) approaches infinity and the array steering vector is accurately known,the Standard Capon beamformer (SCB) can better suppress spatial noises than data-independent beamformers.On the contrary,the performance of the SCB may decrease.To solve this problem,we propose a two-stage shrinkage scheme for the SCM.Specifically,in the first stage,the SCM is enhanced by the General linear combination (GLC) method,which will be referred to as GLC-SCM;and in the second stage,the GLC-SCM is further improved with the Exponential matrix (EM) method,which will be referred to as GLC-EM-SCM.Compared with the conventional methods,the proposed method can achieve higher signal-to-interference-noise ratio output and more accurate signal power estimate.

ExponentialSample covariance matrixRobust Capon beamforming

WANG Jie、YANG Guangquan、HU Yi、ZHANG Chunliang

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School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China

Department of Electrical Engineering Computer Science, University of Wisconsin-Milwaukee, Milwaukee 53201, USA

This work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of ChinaSpecial Innovation Project of Department of Education of Guangdong ProvinceGuangzhou Science and Technology ProjectKey Laboratory of Information Processing Transmission of GuangzhouModern Video Audio Information Engineering Center of Guangdong Province

11974086517751222017KTSCX141201904010468201605030014

2019

10.1049/cje.2019.06.016

中国电子杂志(英文版)

中国电子杂志(英文版)

CSTPCDCSCDSCIEI
ISSN：1022-4653
年,卷(期)：2019.28(5)
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