尺度不变范数比正则的稀疏DOA估计

王圣杰; 张晗; 杜朝辉

doi:10.12263/DZXB.20221343

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尺度不变范数比正则的稀疏DOA估计

学术论文 | 更新时间：2026-04-10

- 尺度不变范数比正则的稀疏DOA估计
- Scale Invariant Norm Ratio Regularized Sparse DOA Estimation
- 电子学报 2024年52卷第1期页码：298-310
- 作者机构：
  
  1.长安大学工程机械学院,陕西西安 710064
  2.长安大学道路施工技术与装备教育部重点实验室,陕西西安 710064
  3.西北工业大学航海学院,陕西西安 710072
- 作者简介：
  
  [ "王圣杰男，1997年9月出生于江苏省南通市.2020年毕业于江苏科技大学机械设计制造及其自动化系.主要研究方向为阵列信号处理方面研究工作. E-mail: 18862639622@163.com" ]
  [ "张晗女，1988年12月出生于河南省南阳市.2017年获西安交通大学机械工程学科博士学位.现为长安大学工程机械学院副教授.主要研究方向为稀疏信号处理与优化、深度学习、机械健康监测与故障诊断. E-mail: zhanghan@chd.edu.cn" ]
  [ "杜朝辉男，1985年9月出生于四川省达州市.2017年获西安交通大学机械工程学科博士学位.现为西北工业大学航海学院副教授.主要研究方向为机器学习、稀疏优化理论以及针对关键机械系统和海洋信号的阵列信号处理. E-mail: duzh@nwpu.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(52275085;11804279);陕西省自然科学基金(2020JQ-131);中央高校基本科研业务费专项资金(300102252201)
- DOI：10.12263/DZXB.20221343
  中图分类号： TB566;TN911.7
- 收稿：2022-11-25，
  
  修回：2023-05-16，
  
  纸质出版：2024-01-25
- 稿件说明：
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王圣杰,张晗,杜朝辉.尺度不变范数比正则的稀疏DOA估计[J].电子学报,2024,52(01):298-310.

WANG Sheng-jie,ZHANG Han,DU Zhao-hui.Scale Invariant Norm Ratio Regularized Sparse DOA Estimation[J].ACTA ELECTRONICA SINICA,2024,52(01):298-310.
王圣杰,张晗,杜朝辉.尺度不变范数比正则的稀疏DOA估计[J].电子学报,2024,52(01):298-310. DOI： 10.12263/DZXB.20221343.

WANG Sheng-jie,ZHANG Han,DU Zhao-hui.Scale Invariant Norm Ratio Regularized Sparse DOA Estimation[J].ACTA ELECTRONICA SINICA,2024,52(01):298-310. DOI： 10.12263/DZXB.20221343.

摘要

波达方向估计（Direction Of Arrival，DOA）通过使用传感器阵列来识别声源方位，而传统的DOA估计方法忽略了声源在空间分布的稀疏性，目前的凸稀疏DOA估计方法和非凸稀疏DOA估计方法所使用的惩罚函数未考虑稀疏度量

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范数的重要特性——尺度不变性，因此无法精确描述声源的空域稀疏结构，难以获得较高的DOA估计精度.为此，本文首先使用具有尺度不变性的范数比函数来逼近

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范数，刻画声源空域稀疏结构；接着，针对范数比函数的非凸特性，采用光滑化的思想，构建了平滑的近似函数；然后，构建了基于光滑

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比

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范数的稀疏DOA估计模型，开发了基于光滑

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范数的稀疏DOA估计算法（Smoothed

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regularized Sparse DOA Estimation algorithm，SPOQ-SDOA）.大量仿真分析表明，与流行的多快拍DOA估计算法相比，本文提出的算法在不同信噪比和快拍数下有更高的DOA估计精度和更好的性能表现.SWellEx-96海试实验中的S5事件分析结果验证了所提算法的有效性.

Abstract

Direction of arrival (DOA) estimation uses sensor arrays to identify the direction of sound sources

while traditional DOA estimation methods ignore the sparsity of sound sources in spatial distribution. The penalty function used by current convex sparse DOA estimation methods and non-convex sparse DOA estimation methods do not consider the important scale invariance feature of sparse

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norm

which cannot accurately describe the spatial sparse structure of the sound source

and it is difficult to obtain high DOA estimation accuracy. For this reason

firstly

the scale-invariance norm ratio function is used to approximate the

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norm and characterize the spatial sparse structure of the sound source in this paper; Secondly

aiming at the non-convex property of the norm ratio function

a smooth approximation function is constructed by using the idea of smoothing; Then

the scale-invariant

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regularized sparse DOA estimation model is constructed

and meanwhile an optimization algorithm is developed for it. A lot of simulation analysis demonstrate that the proposed algorithm has higher DOA estimation accuracy and better performance under different SNR and snapshot numbers than the popular multi-snapshot DOA estimation algorithm. The analysis results of S5 events in SWellEx-96 sea trial experiment verified the effectiveness of the proposed algorithm.

关键词

Keywords

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