Monostatic MIMO radar with nested L-shaped array: Configuration design, DOF and DOA estimation

被引:7
|
作者
Li, Zheng [1 ]
Zhang, Xiaofei [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Elect & Informat Engn, Nanjing 211106, Peoples R China
基金
中国国家自然科学基金;
关键词
DOA estimation; L-shaped monostatic MIMO radar; Extensional nested linear array; Iterative Taylor expansion; 2-D ANGLE ESTIMATION; ESTIMATION ALGORITHM; ELEVATION; AZIMUTH;
D O I
10.1016/j.dsp.2020.102883
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we consider the problem of two-dimensional (2-D) direction of arrival (DOA) estimation for L-shaped monostatic MIMO radar with two-level nested linear array (NLA). To obtain more degrees of freedom (DOFs) than traditional nested L-shaped (NLs) MIMO radar, we propose the extensional NLs (ENLs) MIMO radar by extending all of the sensor positions in transmitter array with an identical magnification compared with NLs MIMO radar. The ENLs MIMO radar can offer O(M1M2N1N2) DOFs with only O(M-1 + M-2 + N-1 + N-2) sensors, where M-1(N-1) and M-2(N-2) respectively represents the numbers of the first-level and second-level sensors of NLA in transmitter (receiver) array. Furthermore, to avoid the eigenvalue decomposition, spatial spectral search and polynomial root finding technique in spatial smoothing multiple signals classification (SS-MUSIC) and SS-ROOT-MUSIC, and to improve the estimation accuracy simultaneously, we propose a search-free iterative Taylor expansion (SF-ITE) algorithm to perform DOA estimation, which employs the Discrete Fourier transform (DFT) method to get the coarse estimation, and then utilizes the iterative Taylor expansion technique to obtain fine estimation. SF-ITE can get more precise estimation by performing iteration only once than both SS-MUSIC and SS-ROOT-MUSIC. In addition, we derive an angle-pairing procedure to help to eventually resolve more targets than the total number of sensors. Finally, simulation results are provided to validate the superiority of the ENLs MIMO radar and SF-ITE algorithm. (C) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页数:11
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