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

• Published in: Chinese Journal of Electronics Vol. 28; no. 5; pp. 962 - 967
• Main Authors: WANG, Jie, YANG, Guangquan, HU, Yi, ZHANG, Chunliang
• Format: Journal Article
• Language: English
• Published: Published by the IET on behalf of the CIE 01.09.2019
• Subjects: array signal processing; array steering vector; covariance matrices; data‐independent beamformers; Exponential; Exponential matrix method; General linear combination method; GLC‐EM‐SCM; Robust Capon beamforming; Sample covariance matrix; sample covariance matrix approach; SCB; signal denoising; signal power estimate; signal‐to‐interference‐noise ratio output; spatial noise suppression; standard Capon beamformer; two‐stage nonlinear shrinkage scheme; GLC-EM-SCM; Sample covariance matrix; covariance matrices; data-independent beamformers; Exponential matrix method; signal-to-interference-noise ratio output; array steering vector; Exponential; standard Capon beamformer; spatial noise suppression; signal denoising; SCB; robust capon beamforming; General linear combination method; two-stage nonlinear shrinkage scheme; sample covariance matrix approach; signal power estimate; array signal processing
• ISSN: 1022-4653; 2075-5597
• DOI: 10.1049/cje.2019.06.016

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 GLCSCM 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.