Dynamic Transmit-Receive Beampattern Optimization of Colocated MIMO Radars for Multi-Target Tracking Under Suppression Jamming

In this paper, we propose a dynamic transmit and receive beampattern optimization (DTRBO) method for colocated MIMO (C-MIMO) radars in cognitive multi-target tracking (MTT) scenarios under suppression jamming. To accurately account for the effects of suppression jamming on MTT performance, we develop a comprehensive signal model that integrates the complete transmit-receive beamforming process into the resource optimization framework. Based on this enhanced signal model, we derive an enumeration-based posterior Cramér-Rao lower bound (PCRLB), which incorporates both measurement errors and target miss detections, providing a more accurate performance metric under suppression jamming. Using the derived PCRLB, the DTRBO strategy is formulated to dynamically optimize transmit and receive beams for each tracking interval, thereby maximizing global MTT performance. Due to the coupling of optimization variables and the non-convexity of the derived PCRLB, the resulting optimization problem is computationally challenging. To address this, we propose a partition-based three-stage iterative method to decouple the variables, employing a first-order Taylor expansion-based convex approximation technique to solve the non-convex problem efficiently. Simulation results demonstrate the effectiveness and the superiority of the proposed DTRBO strategy in terms of both MTT performance and anti-jamming capabilities, outperforming existing approaches that omit the beampattern modeling process in resource-aware optimization.