Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint
Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint作者机构：National Laboratory of Radar Signal Processing Xidian University
出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)
年 卷 期：2016年第17卷第11期
页 面：1245-1252页
核心收录：
学科分类：0810[工学-信息与通信工程] 0711[理学-系统科学] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 07[理学] 0839[工学-网络空间安全] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by the Fundamental Research Funds for the Central Universities China(No.K5051202047)
主 题：Beamforming General-rank Low complexity Positive semidefinite(PSD) constraint Model mismatches
摘 要：We propose a low complexity robust beamforming method for the general-rank signal model, to combat against mismatches of the desired signal array response and the received signal covariance matrix. The proposed beamformer not only considers the norm bounded uncertainties in the desired and received signal covariance matrices, but also includes an additional positive semidefinite constraint on the desired signal covariance matrix. Based on the worst-case performance optimization criterion, a computationally simple closed-form weight vector is obtained. Simulation results verify the validity and robustness of the proposed beamforming method.
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