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

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.

Automated summary

This paper addresses the 2-D direction of arrival (DOA) estimation problem for L-shaped monostatic MIMO radar with two-level nested linear array (NLA). A more degrees of freedom (DOFs) ENLs MIMO radar is proposed to outperform traditional NLs MIMO radar. The search-free iterative Taylor expansion (SF-ITE) algorithm is introduced to enhance DOA estimation accuracy.