基于预测校正的落角约束计算制导方法

To solve the problem of missile guidance with constraint of terminal impact angle, a learning-based computational guidance algorithm is proposed based on the general predictor-corrector concept. A deep neural network is designed based on the relationship between the flight state and impact angle, to predict the exact terminal impact angle under proportional navigation guidance with realistic aerodynamic characteristics. A biased command to nullify the impact angle error is developed based on the relationship between impact angle error and the acceleration command, and the deep reinforcement learning techniques is utilized. The deep neural network is augmented into the reinforcement learning block to resolve the issue of sparse reward that has been observed in traditional reinforcement learning formulation. Extensive numerical simulations are conducted to verify the proposed algorithm. The simulation results show that the designed computational guidance method can realize impact angle control accurately. The guidance algorithm has high precision and low delay in embedded computer, which shows that the algorithm can be applied to engineering.