Joint Waveform Design of Cognitive MIMO Radar for Multi-Target Detection

The waveform design for cognitive multiple input multiple output (MIMO) radar systems remains an active area of research in modern radar signal processing. This study tackles the critical challenge of multi-target detection in cognitive MIMO radar by maximizing the minimum output signal-to-interference-plus-noise ratio (SINR) across all the detected targets. To resolve the nonconvex optimization problem arising from multi-target scenarios, we implement a semi-definite programming (SDP) algorithm incorporating approximate output SINR. Joint waveforms, including intra-pulse and inter-pulse, are applied to improve the freedom of the radar. The proposed work specifically integrates practical peak-to-average ratio (PAR) limitations, ensuring waveform feasibility for implementation in physical radar systems. Simulation results show that the proposed joint waveform can achieve more robust simultaneous multi-target detection performance in coherent clutter, while suppressing coherent interferences from other targets when detecting a certain target. Besides, our optimization algorithm has better real-time performance than existing algorithms.