Target detection and localization using multi-frame information for noncoherent MIMO radar

This paper considers the target detection and localization via jointly processing multi-frame information, attainable by the use of multiple-input multiple-output (MIMO) radar with widely separated antennas. By incorporating the target dynamic model, the problem can be formulated and solved in the framework of maximum a posteriori probability (MAP) criterion. However, the analytical solution of the posteriori probability density is usually intractable. A grid based search method is needed to achieve a computationally tractable approximation. For most realistic problems, directly performing exhaustive search is computationally prohibited due to the high dimensionality of state space. Therefore we resort to dynamic programming algorithm as a fast implementation to reduce the calculation burden. Owing to the utilization of multi-frame information of targets, the proposed algorithm can achieve better detection performance and higher localization accuracy, particularly when the target signal-to-noise ratio is low. Finally, numerical examples are used to demonstrate the efficiency of the proposed algorithm comparing with the localization method only using single-frame information.