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应用科学学报 >

2023 , Vol. 41 >Issue 6: 926 - 939

DOI: https://doi.org/10.3969/j.issn.0255-8297.2023.06.002

通信工程

基于酉重构子空间的一维DOA估计

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  • 1. 上海大学 通信与信息工程学院, 上海 200444;
    2. 上海大学 上海先进通信与数据科学研究院, 上海 200444;
    3. 卡斯柯信号有限公司, 上海 200070;
    4. 上海轨道交通无人驾驶列控系统工程技术研究中心, 上海 200434

收稿日期: 2022-04-23

  网络出版日期: 2023-11-30

基金资助

上海市自然科学基金（No.22ZR1422200）资助

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One-Dimensional DOA Estimation Based on Unitary Reconstructive Subspace

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  • 1. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China;
    2. Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China;
    3. CASCO Signal Co., Ltd., Shanghai 200070, China;
    4. Shanghai Rail Transit Unmanned Train Control System Engineering and Technology Research Center, Shanghai 200434, China

Received date: 2022-04-23

  Online published: 2023-11-30

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摘要

针对多重信号分类（multiple signal classification,MUSIC）算法在低阵元数目、低信噪比和小节拍数等非理想条件下，对入射间隔较小的信号波达方向（direction of arrival,DOA）估计有效性的问题，提出了改进的基于酉重构子空间的MUSIC算法。该算法首先利用酉变换将均匀线阵接收数据实数化，然后根据子空间特征向量的大小，重新构造子空间和校正矩阵得到新的空间谱函数，最后与信号子空间投影算法联合，实现DOA估计。仿真结果表明，与传统MUSIC算法和SSP算法相比，所提算法在低阵元数目、低信噪比和小节拍条件下具有更好的分辨率。

关键词： 波达方向估计; 酉变换; 重构子空间; 空间谱估计

本文引用格式

金彦亮, 闾儒坤, 汪小勇, 郑国莘 . 基于酉重构子空间的一维DOA估计[J]. 应用科学学报, 2023 , 41(6) : 926 -939 . DOI: 10.3969/j.issn.0255-8297.2023.06.002

Abstract

To address the limitations of traditional multiple signal classification (MUSIC) algorithm, such as ineffective performance in low signal to noise ratio (SNR), small snapshots and low array number under small incident angle interval signals, we propose an improved algorithm called unitary reconstructed subspace MUSIC (URS-MUSIC). The proposed algorithm transforms the actual received signal of a uniform linear array from complex to real value using unitary transformation, then reconstructs subspaces and revised matrices to obtain new spatial spectrums based on the size of the subspace eigenvectors. The obtained spectrums are multiplied by the signal subspace projection (SSP) to realize direction of arrival (DOA) estimation. Simulation results demonstrate that URS-MUSIC outperforms both traditional and signal subspace projection algorithms with better resolution performance, especially under challenging conditions such as low SNR, small snapshots, and low array numbers.

Key words： direction of arrival (DOA) estimation; unitary transform; reconstructive subspace; spatial spectrum estimation

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