Cooperative Guidance with Optimal Angle Constraints Based on Deep Neural Network

Cooperative guidance with optimal angle constraints based on deep neural network (DNN) is developed to address the problem of cooperative guidance of multiple missiles against maneuvering targets. Firstly, Angle-constrained guidance (ACG) law based on sliding mode control is proposed, and the structure of cooperative guidance is designed. Secondly, an optimal method of cooperative angles is designed. Deep neural network is applied to estimate optimal cooperative angles. Input variables of network are normalized to reduce the range of variable values Thirdly, in the scene of 3 missiles against 1 target, cooperative angles are optimized and the network is trained. Simulation is carried out to verify the performance of guidance law.