引入虚拟目标的高超声速巡航导弹智能机动突防策略

An intelligent penetration policy using virtual targets and contextual Markov decision process (CMDP) for hypersonic cruise missiles is proposed to constrain the trajectory deviation and improve the generalization performance in different combat scenarios. The stationary virtual targets are chosen within a tubular envelope with the planned trajectory as axis, and the deep reinforcement learning algorithm is applied to decide their position relative to the axis. Then the proportional guidance law is used to guide the cruise missile to attack these virtual targets one by one with proportional guidance law, thus shaping a maneuvering trajectory meeting the requirements of penetration within the given envelope. The optimal penetration policy for a combat scenario is extended to the probability distribution of combat scenarios using CMDP to improve the generalization performance. The results demonstrate that the penetration policy constrains the trajectory deviation during penetraton and exhibits adaptability to variations of interceptor's launch position and maneuvering capability.