基于互质阵列实值互相关矩阵的波达方向估计

DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays.

作者信息

Li Jianfeng, Wang Feng, Jiang Defu

机构信息

Array and information processing laboratory, College of computer and information, Hohai University, Nanjing 211100, China.

出版信息

Sensors (Basel). 2017 Mar 20;17(3):638. doi: 10.3390/s17030638.

DOI:10.3390/s17030638

PMID:28335536

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5375924/

Abstract

A fast direction of arrival (DOA) estimation method using a real-valued cross-correlation matrix (CCM) of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship between the two subspaces, DOA estimations from the two subarrays are simultaneously obtained with automatic pairing. Finally, unique DOA is determined based on the common results from the two subarrays. Compared to partial spectral search (PSS) method and estimation of signal parameter via rotational invariance (ESPRIT) based method for coprime arrays, the proposed algorithm has lower complexity but achieves better DOA estimation performance and handles more sources. Simulation results verify the effectiveness of the approach.

摘要

提出了一种利用互质子阵的实值互相关矩阵（CCM）进行快速到达方向（DOA）估计的方法。首先，构建具有扩展孔径的实值CCM以获得对应于两个子阵的信号子空间。通过分析这两个子空间之间的关系，自动配对同时获得来自两个子阵的DOA估计。最后，基于来自两个子阵的共同结果确定唯一的DOA。与互质阵列的部分谱搜索（PSS）方法和基于旋转不变性估计信号参数（ESPRIT）的方法相比，该算法具有更低的复杂度，但实现了更好的DOA估计性能且能处理更多的源。仿真结果验证了该方法的有效性。