Multi-target localization for noncoherent MIMO radar with widely separated antennas

This paper addresses the multi-target localization problem for noncoherent multiple-input multiple-output (MIMO) radar with widely separated antennas. To this end, we first adopt a high-dimensional parameter vector, which is the concatenation of the parameters to be estimated for individual targets, and then propose a novel multi-target localization algorithm by estimating the high-dimensional parameter vector based on maximum-likelihood estimation (MLE). However, this solution is usually computationally intractable for most realistic problems as it is involved with a high-dimensional joint maximization. Therefore we also propose a suboptimum algorithm which allows trading better localization accuracy for a much lower implementation complexity. Numerical examples are provided to assess and compare the performances of the proposed multi-target localization algorithms.