Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar

Sensors (Basel). 2015 Nov 10;15(11):28271-86. doi: 10.3390/s151128271.

Abstract

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri-Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method.

Keywords: DOA estimation; Khatri–Rao product; MIMO radar; sparse representation; unitary transformation.