AUTOMATIC ROBUST ADAPTIVE BEAMFORMING BASED ON LATENT ROOT REGRESSION

被引:0
作者
Yang, Jun [1 ]
Ma, Xiaochuan [1 ]
Hou, Chaohuan [1 ]
Liu, Yicong [2 ]
机构
[1] Chinese Acad Sci, Inst Acoust, Beijing 100864, Peoples R China
[2] Chinese Acad Sci, State Key Lab Informat Secur, Beijing 100864, Peoples R China
来源
SPAWC: 2009 IEEE 10TH WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS | 2009年
关键词
minimum variance beamforming; adaptive beamforming; robust beamforming; latent root regression;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we describe a fully automatic method using latent root regression based on the generalized sidelobe canceler (GSC) parameterization of the minimum variance beamformer. The proposed method gives a theoretically optimal solution in mean-squared error (MSE) sense (minimized MSE solution) by choosing a linear combination of individual latent root regression predictors in the GSC formulation. The performance of the resulting beamformer is illustrated via numerical examples and compared with existing automatic diagonal loading techniques including HKB and the general linear combination (GLC) shrinkage-based method. The simulations show that the proposed method usually gives better performance than HKB, meanwhile, is more robust to errors on steering vectors than GLC when the sample sizes are high.
引用
收藏
页码:544 / +
页数:2
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