An Approximate ML Estimator for Moving Target Localization in Distributed MIMO Radars

Abstract

This letter deals with the problem of moving target localization in distributed multiple-input multiple-output (MIMO) radar systems using time delay (TD) and Doppler shift (DS) measurements. The proposed solution to this problem consists of two stages. In the first stage, an initial estimation of target location is obtained by solving the formulated maximum likelihood (ML) problem based on the TD measurements. In the second stage, by recognizing the obtained position estimate in the previous stage as a priori data and exploiting the DS measurements, another ML problem is formulated, which is efficiently solved via a tractable numerical method to produce a simultaneous estimation of target position and velocity vectors. Overall, the proposed method significantly outperforms the state-of-the-art algorithms under Gaussian noise model as corroborated by numerical simulations.