Design of Waveform Covariance Matrix for MIMO Radar with low cross correlation

This paper aims to enhance the performance of Multiple-Input-Multiple-Output (MIMO) radar systems by efficiently optimizing the covariance matrix and antenna selection vector to minimize the cross correlation among the waveform at several given target locations. The proposed non convex optimization problem is solved using cyclic optimization approach. Furthermore, a modified binary particle swarm optimization (MBPSO) technique is proposed for antenna selection, with the goal of achieving the required beam pattern with a minimal number of antennas and reduced cross-correlation. The proposed methodology not only guarantees optimal solutions but also demonstrates significantly reduced time complexity, making it suitable for real-time implementation in MIMO radar systems. By striking a balance between accuracy and computational efficiency, this technique offers promising performance enhancements, placing it as a tempting option for practical MIMO radar applications.