Target Localization in MIMO Radars with Distributed Antennas

In this paper, the problem of elliptic target localization in distributed multiple-input multiple-output (MIMO) radars is investigated. The goal of elliptic localization is to estimate the target position from a set of noisy bistatic delay measurements. Since the maximum likelihood (ML) problem associated with elliptic localization is nonconvex, iterative methods can be trapped in local minimums, leading to inaccurate location estimation. To solve this problem, a number of (almost closed-form) estimators are proposed, which can locate the target without convergence concern. The proposed methods are efficient, achieving Cramer-Rao lower bound (CRLB) up to relatively high noise levels. These methods are of superior localization accuracy in comparison with the state-of-the-art methods. Furtheremore, according to the closed-form and algebraic nature of the proposed methods, they have very low computational complexity, which is similar to other existing closed-form methods in the literature. It should be noted that the ideas presented in this paper can be considered as a baseline for future research studies in the area of localization in radar systems.