DOA estimation via sparse representation of the smoothed array covariance matrix

被引：0

作者：

Cai J. ^{[1
]}

Zong R. ^{[1
]}

Cai H. ^{[2
]}

机构：

[1] School of Electronic Engineering, Xidian University, Xi'an

[2] 95037 People's Liberation Army Troops China, Wuhan

来源：

Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2016年 / 38卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Compressed sensing; DOA estimation; Sparse reconstruction; Spatial smoothing;

D O I：

10.11999/JEIT150538

中图分类号：

学科分类号：

摘要：

A novel Direction-Of-Arrival (DOA) estimation algorithm based on spatial smoothing and sparse reconstruction is proposed in this paper. Firstly, the covariance matrix is processed using spatial smoothing theory, and it is converted with the Khatri-Rao transformation, then DOA estimation is achieved by sparse reconstruction of the converted matrix. Furthermore, two different kinds of methods are given to deal with the error of the objective function. Experimental results show that the proposed algorithm can reduce the amount of computation, and exhibit better performance on both coherent and non-coherent signals compared with the other DOA algorithms based on compressed sensing, especially under the conditions of low angle interval, low signal-to-noise ratio and low sampling number. © 2016, Science Press. All right reserved.

引用

页码：168 / 173

页数：5

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