A Particle Swarm Approach to Target Detection in MIMO Radar

Devising target detection techniques for Multiple Input Multiple Output (MIMO) Radar systems is the main theme of this paper. A novel Particle Swarm Optimization algorithm based framework for superior target detection and grid localization for MIMO Radar is proposed. PSO algorithm finds effective utility in large signal spaces for multiple target detection and is easy to implement. The signal model characterizing the clutter and clutter-free environments are modelled. We adopt Orthogonal Matching Pursuit (OMP) algorithm as a benchmark for comparison. Mathematical interpretation of the OMP algorithm for multiple target detection is provided. Simulation results which prove the optimality of the proposed PSO approach are presented. The variation of Mean Squared Error (MSE) with Signal-to-Noise Ratio is used as a performance metric for analysis. Time complexity analyses of the PSO and OMP algorithms are also presented. The proposed approach is also extended for estimation of target characteristics.