Research on Guidance Law Recognition Method of Incoming Missile Based on LSTM Neural Network

In the three-body confrontation scenario, the accurate recognition of the guidance law of incoming missile can provide strong support for its trajectory prediction. In view of the semi-cooperative characteristics of incoming missile movement and target movement in this scenario, different target maneuvers are added when collecting missile trajectory data to make the data more realistic. A guidance law recognition method based on long short-term memory (LSTM) neural network is proposed to identify the type of guidance law for incoming missile. A LSTM neural network with attention mechanism is designed to improve the adaptive ability and generalization ability of the network model, and the recognition accuracy and precision are greatly improved. The experimental results show that this method has high recognition accuracy and short recognition time, which can meet the needs of on-board use.