Sparse MIMO radar with phase mismatch

In this paper we propose a sparse model to accurately estimate target locations in a distributed multiple-input multiple-output (MIMO) radar system with phase mismatches at transmitters and receivers. We formulate the localization problem based on maximum a posteriori (MAP) estimation. To reduce the effect of phase mismatches we develop a novel alternating minimization approach based on sparse signal recovery and structured matrix perturbation. Using numerical simulations, we show that our algorithms significantly improve the performance of the distributed MIMO radar system.