LAUSR

The confrontation between radar and jammer is increasingly competitive in electromagnetic spectrum warfare. The current radar anti-jamming methods are constrained to some extent in complex electromagnetic environment. It is necessary to study not only radar specific action benefit but also confrontation strategy. To improve the anti-jamming capacity of radar system, a game theory-based optimization method is proposed to enhance the decision-making of anti-jamming strategy in this paper. First, we analyzed the radar winning conditions and discussed the temporal constraints of the recognition and preparation process of the radar and jammer actions. Second, a temporal sequence interaction based dynamic game model between radar and jammer is constructed. Then, Q-learning is performed to optimize the radar anti-jamming strategies with the temporal sequence interaction gain as the objective function. The simulation experimental results show that the proposed strategy can significantly improve the radar winning probability in the confrontation.