Competitor Matching Method for Penetration Control Based on Deep Learning

For the problem of the competitor needs to be identify when designing a cooperative penetration control scheme against multiple interceptors based on game theory, an attack object matching method of interceptor missile based on long short-term memory (LSTM) network is proposed. Based on the flight sequence and process of the traditional interceptor missile, the interceptor missile flight trajectory library is constructed, and the LSTM network is trained with the trajectory database as the training sample. Based on this trained network, an interceptor track prediction model and an object matching model are constructed to identify the target recognition of the interceptor. The simulation results show that the method can effectively identify the interceptor target and provide support for the follow-up cruise missile penetration research.