MADDPG Based Radar Interference Resource Allocation Decision

For the problem of jamming penetration under the one-to-many scenario with jammer, a real-time radar interference resource allocation method based on the Multi-agent deep deterministic policy gradient (MADDPG) algorithm is proposed. This method describes the interference resource allocation model as a Markov Decision Process (MDP), and designed the state space, action space and reward function for interference resource allocation problem. The jammer is divided into three heterogeneous agents, each responsible for selecting jamming targets, jamming patterns, and jamming power, respectively. These three agents coordinate to enhance the convergence ability of the high-dimensional action space algorithm. Simulation results indicate that the jamming resource allocation method designed in this paper provides better jamming effects on radar positions, higher stability, and effectively improves the operational performance of the jammer.