L-Shaped Sparse Array Structure for 2-D DOA Estimation

作     者：Wu, Fan Cao, Fei Ni, Xiaogang Chen, Chong Zhang, Yanhong Xu, Jianfeng 

作者机构：High Tech Inst Xian Xian 710025 Peoples R China Univ Sci & Technol Beijing USTB Sch Comp & Commun Engn Beijing 100083 Peoples R China 

出 版 物：《IEEE ACCESS》 (IEEE Access)

年 卷 期：2020年第8卷

页      面：140030-140037页

核心收录：

基　　金：National Nature Science Foundation of China 

主　　题：Degrees-of-freedom direction-of-arrival estimation L-shaped arrays sparse linear array 

摘      要：In order to improve the performance of two-dimensional (2-D) direction-of-arrival (DOA) estimation, an L-shaped sparse array structured by two new sparse linear arrays is proposed. Each part of the proposed L-shaped array is used for one-dimensional (1-D) azimuth and elevation estimation, respectively. The new sparse linear array configuration is consisted of two subarrays which have N and M physical sensors, respectively. Owing to the advantages of the proposed sparse linear array configuration, higher degrees-of-freedom (DOF) and larger array aperture can be achieved when the second-order statistics of the received data is used. To match the azimuth and elevation angles automatically, the cross-covariance matrix of the two parts of the proposed L-shaped array is used to estimate the paired DOA angles. Based on the proposed L-shaped array configuration, (M + 1)(N - [M/2]) signal directions can be estimated with M CN sensors in each part and totally 2M + 2N + 1 sensors. Through the comparative analysis of the parameters with other sparse planar arrays, the proposed L-shaped array can achieve better performance due to its higher DOF and larger array aperture. Finally, numerical simulation results verify the superiority of the 2-D DOA method based on the proposed L-shaped array.