Underdetermined DOA estimation of coherent signals based on denoising complex FastICA and sparse reconstruction

被引:0
作者
Hou J. [1 ,2 ]
Li Y. [2 ,3 ]
Li T. [2 ,3 ]
机构
[1] School of Information Science and Technology, Southwest Jiaotong University, Chengdu
[2] National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Chengdu
[3] Graduate School of Tangshan, Southwest Jiaotong University, Tangshan
来源
Tongxin Xuebao/Journal on Communications | 2021年 / 42卷 / 11期
关键词
Coherent signal; Complex fast independent component analysis; Denoising; DOA estimation; Sparse reconstruction; Underdetermined;
D O I
10.11959/j.issn.1000-436x.2021219
中图分类号
学科分类号
摘要
To solve the problem that most of the existing direction of arrival(DOA) estimation methods for coherent signals could not be used in the case of under determination, where the number of incident signals exceeds the number of sensors, a DOA estimation method combining complex fast independent component analysis (FastICA) and sparse reconstruction algorithm was proposed. When the number of uniform circular array(UCA) sensors was M, the DOA of M(M-1) incident signals could be estimatedat most. To solve the problem of poor separation effect of complex FastICA in the case of low signal-to-noise ratio(SNR), two general denoising complex FastICA algorithm were proposed, which could be used in the case of circular signal and non-circular signal. The results of simulation and measured data show that the proposed algorithm can estimate both coherent and incoherent signals in underdetermined cases. Compared with several existing algorithm, the proposed DOA estimation algorithm has good performance. © 2021, Editorial Board of Journal on Communications. All right reserved.
引用
收藏
页码:172 / 181
页数:9
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