Efficient Joint Moving Target and Antenna Localization in Distributed MIMO Radars

In this paper, a novel solution for the problem of joint moving target and antenna localization in the distributed multiple-input multiple-output (MIMO) radar systems is proposed. The localization problem in the presence of antenna location uncertainty is formulated as a maximum likelihood (ML) estimation problem, which is then recast into convex form by defining some auxiliary variables and applying semidefinite relation (SDR) technique. Next, an algebraic closed-form estimator is proposed to jointly estimate the target and the antennas error terms and refine their uncertain values. The proposed method is shown analytically and verified by the numerical simulations to be an efficient estimator, which can achieve the Cramer–Rao lower bound (CRLB) performance for both the target and antenna estimations under small error conditions. Furthermore, the results of numerical simulations demonstrate that the proposed estimator outperforms the state-of-the-art methods presented for moving target localization in MIMO radars.