基于去噪复数FastICA和稀疏重构的相干信号欠定DOA估计

doi:10.11959/j.issn.1000-436x.2021219

通信学报 ›› 2021, Vol. 42 ›› Issue (11): 172-181.doi: 10.11959/j.issn.1000-436x.2021219

基于去噪复数FastICA和稀疏重构的相干信号欠定DOA估计

侯进¹^,², 李昀喆²^,³, 李天宇²^,³

¹ 西南交通大学信息科学与技术学院，四川成都 611756
² 西南交通大学综合交通大数据应用技术国家工程实验室，四川成都 611756
³ 西南交通大学唐山研究生院，河北唐山 063000

修回日期:2021-10-08 出版日期:2021-11-25 发布日期:2021-11-01
作者简介:侯进（1969− ），女，重庆人，博士，西南交通大学副教授，主要研究方向为无线通信、机器学习、深度学习、图像识别等
李昀喆（1996−），女，河南南阳人，西南交通大学硕士生，主要研究方向为无线电测向、深度学习
李天宇（1995− ），男，山东临沂人，西南交通大学硕士生，主要研究方向为无线通信、信号处理与分析、深度学习
基金资助:
四川省科技计划基金资助项目(2020SYSY0016)

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

Jin HOU¹^,², Yunzhe LI²^,³, Tianyu LI²^,³

¹ School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China
² National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Chengdu 611756, China
³ Graduate School of Tangshan, Southwest Jiaotong University, Tangshan 063000, China

Revised:2021-10-08 Online:2021-11-25 Published:2021-11-01
Supported by:
Science and Technology Plan Project of Sichuan Province(2020SYSY0016)

摘要/Abstract

摘要：

针对现有的存在相干信号的 DOA 估计方法大多数不能用于欠定的情况，即入射信号数超过传感器数的问题，提出了一种复数快速独立成分分析算法（即复数FastICA算法）和稀疏重构算法结合的DOA估计方法。当均匀圆阵传感器数目为 M 时，该算法最多可以估计 M(M-1)入射信号的到达角。针对低信噪比情况下，复数FastICA分离效果差的问题，提出了2种圆信号与非圆信号情况下通用的去噪复数FastICA算法。仿真结果与实测数据结果表明，该算法可以进行欠定情况相干与非相干信号共存的 DOA 估计，与目前的几种算法相比，所提的DOA估计方法算法具有良好的性能。

关键词: 欠定情况, 复数快速独立成分分析, 稀疏重构, 到达角估计, 去噪, 相干信号

Abstract:

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.

Key words: underdetermined, complex fast independent component analysis, sparse reconstruction, DOA estimation, denoising, coherent signal

中图分类号:

TN98

侯进, 李昀喆, 李天宇. 基于去噪复数FastICA和稀疏重构的相干信号欠定DOA估计[J]. 通信学报, 2021, 42(11): 172-181.

Jin HOU, Yunzhe LI, Tianyu LI. Underdetermined DOA estimation of coherent signals based on denoising complex FastICA and sparse reconstruction[J]. Journal on Communications, 2021, 42(11): 172-181.

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算法	DOA估计结果
目标DOA	[103°,[256°,320°]]
L1-SVD	[103°,[256°,319°]]
MUSIC	[103°,320°]
DML	[103°,256°]
本文所提算法	[103°,[256°,320°]]

算法	DOA结果	错误个数
目标DOA	[37°,96°,171°,290°,322°,358°]	—
L1-SVD	[95°,138°,169°,198°,288°,358°]	1
MUSIC	[37°,100°,171°,224°,288°,321°]	2
DML	[95°,169°,195°,260°,333°,358°]	3
本文所提算法	[37°,96°,171°,290°,322°,358°]	0

基于去噪复数FastICA和稀疏重构的相干信号欠定DOA估计

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

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图/表 11

参考文献 19

相关文章 15

Metrics

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算法	平均收敛次数/次
非线性FastICA算法	68
除噪复数FastICA算法	12
去噪复数FastICA算法	14

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