基于去噪复数FastICA和稀疏重构的相干信号欠定DOA估计

侯进; 李昀喆; 李天宇

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

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基于去噪复数FastICA和稀疏重构的相干信号欠定DOA估计

学术论文 | 更新时间：2024-06-05

- 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
- 通信学报 2021年42卷第11期页码：172-181
- 作者机构：
  
  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
- 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" ]
- 基金信息：
  
  四川省科技计划基金资助项目(2020SYSY0016)
- DOI：10.11959/j.issn.1000-436x.2021219
  中图分类号： TN98
- 网络出版日期：2021-11，
  
  纸质出版日期：2021-11-25
- 稿件说明：
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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.
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. DOI： 10.11959/j.issn.1000-436x.2021219.

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

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。

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.

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references

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