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基于特征值梯度跃变的半谱搜索DOA估计算法

HAN Baojin RUAN Shiqiao ZHANG Yuxin ZHONG Boyuan CHEN Zhe HUANG Yifan

数字海洋与水下攻防2025,Vol.8Issue(5):594-600,7.
数字海洋与水下攻防2025,Vol.8Issue(5):594-600,7.DOI:10.19838/j.issn.2096-5753.2025.05.009

基于特征值梯度跃变的半谱搜索DOA估计算法

Half-Spectral Search DOA Estimation Algorithm Based on Eigenvalue Gradient Jump

HAN Baojin 1RUAN Shiqiao 2ZHANG Yuxin 1ZHONG Boyuan 1CHEN Zhe 3HUANG Yifan1

作者信息

  • 1. School of Information and Communication,Guilin University of Electronic Technology,Guilin 541004,China
  • 2. Guangxi Science and Technology Project Evaluation Center Co.,Ltd.,Nanning 530022,China
  • 3. School of Information and Communication,Guilin University of Electronic Technology,Guilin 541004,China||Cognitive Radio and Information Processing Key Laboratory Authorized by China's Ministry of Education Foundation,Guilin 541004,China
  • 折叠

摘要

Abstract

To address the issues that traditional subspace-based direction of arrival(DOA)estimation algorithms require prior knowledge of the number of sources and suffer from high computational complexity,a half-spectral search DOA estimation algorithm based on the gradient jump of eigenvalues is proposed in this paper.The method first constructs a new matrix using the covariance matrix of the received signal and its complex conjugate.Simultaneously,it introduces scanning sources to form a novel covariance matrix with the scanning angle as a variable.Subsequently,eigenvalue decomposition is performed on the constructed covariance matrix.Leveraging the significant power difference between the eigenvalues of the signal subspace and noise subspace,an eigenvalue gradient discrimination function is formulated.The number of signal sources is automatically estimated by detecting the maximum points of this function.Based on the distinct demarcation characteristic between the power intensities of signal and noise eigenvalues,this method takes the gradient variation of eigenvalues as the judgment criterion and does not require prior knowledge of the number of signal sources.Subsequently,by combining the estimated number of signal sources with the low-complexity half-spectral search spectrum function,it effectively improves the DOA estimation accuracy in complex environments.

关键词

特征值梯度/信源数/半谱搜索

Key words

eigenvalue gradient/the number of sources/half-spectral search

分类

通用工业技术

引用本文复制引用

HAN Baojin,RUAN Shiqiao,ZHANG Yuxin,ZHONG Boyuan,CHEN Zhe,HUANG Yifan..基于特征值梯度跃变的半谱搜索DOA估计算法[J].数字海洋与水下攻防,2025,8(5):594-600,7.

基金项目

江西省教育厅科学技术研究一般项目"基于时序模式表征的水声信号熵特征提取方法研究"(GJJ2201640) (GJJ2201640)

广西技术创新引导专项"基于双频多波束声纳的水下造物高分辨探测研究"(桂科 AC25069006) (桂科 AC25069006)

广西科技基地和人才专项"基于深度学习的声纳图像识别方法研究"(桂科 AD21220098) (桂科 AD21220098)

广西自然科学基金"水下小孔径超增益高阶矢量声呐应用基础研究"(2025GXNSFFA069010) (2025GXNSFFA069010)

国家自然科学基金"水下矢量声场高效稳健方位估计方法研究"(62301179). (62301179)

数字海洋与水下攻防

2096-5753

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