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FITEE
Front. Inform. Technol. Electron. Eng.  2016, Vol. 17 Issue (11): 1245-1252    DOI: 10.1631/FITEE.1601112
    
基于正定约束广义秩信号模型的低复杂度稳健自适应算法
Yu-Tang Zhu, Jun-yong Liu, Yong-Bo Zhao, Jun Liu, Peng-Lang Shui
National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China
Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint
Yu-Tang Zhu, Jun-yong Liu, Yong-Bo Zhao, Jun Liu, Peng-Lang Shui
National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China
 全文: PDF 
摘要： 概要：本文针对广义秩信号模型提出一种低复杂度的稳健自适应波束形成算法，用来抑制期望信号的阵列响应失配和接收信号的协方差矩阵失配。该波束形成算法不仅考虑期望信号以及接收信号协方差矩阵不确定集的范数有界性，还保证期望信号协方差矩阵的正定性。最终，本文在最差性能优化准则下推出一个计算简单的闭式加权矢量。计算机仿真结果验证了所提波束形成算法的有效性和稳健性。
关键词： 波束形成;  广义秩;  低复杂度;  正定约束;  模型失配    
Abstract: 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.
Key words: Beamforming    General-rank    Low complexity    Positive semidefinite (PSD) constraint    Model mismatches
收稿日期: 2016-03-27 出版日期: 2016-11-07
CLC:  TN911.7  
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Yu-Tang Zhu
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Yu-Tang Zhu, Jun-yong Liu, Yong-Bo Zhao, Jun Liu, Peng-Lang Shui. Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint. Front. Inform. Technol. Electron. Eng., 2016, 17(11): 1245-1252.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/FITEE.1601112    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2016/V17/I11/1245

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