Transmit-Receive Assignment and Path Planning of Multistatic Radar-Enabled UAVs for Target Tracking in Stand-Forward Jamming

Target tracking in stand-forward swarm jamming for unmanned aerial vehicles (UAVs) is a promising topic but the relevant research is tepid. This article aims at exploring this problem for multistatic radar-enabled UAVs (RUAVs) via a multiagent cooperative sensing and control scheme, in which all RUAVs constitute a multistatic radar system with variable and movable transmitting and receiving platforms, and each RUAV as an autonomous agent makes decision with other agents for transmit–receive task assignment and path planning to seek the optimal overall target tracking performance. The optimization problem of RUAVs is formulated as minimizing the Bayesian Cramér–Rao lower bound with some practical constraints. To solve this problem, an alternating iterative optimization scheme is presented, in which the coalition formation method is applied for transmit–receive task assignment and the improved particle swarm optimization (PSO) method is devised for path planning. The alternating coalition formation and PSO (ACFPSO) algorithm is, therefore, proposed for RUAVs for target tracking in stand-forward jamming. Numerical simulations in the typical scenario are conducted to verify the effectiveness and superiority of the ACFPSO algorithm from aspects of tracking accuracy and jamming elimination.