Impact Time Cooperative Guidance for Multi-Missile System Based on Incremental Learning

An impact time cooperative guidance method based on incremental learning is proposed for multi-missile cooperative guidance problem in the attack scenario. Firstly, a guidance model is established to represent the relationship of the missiles and the target. Secondly, an impact time coordinated guidance law based on the consensus method is designed. Then, time-to-go of the missile is predicted using an incremental learning algorithm, so that the accuracy of time-to-go can be better than the results calculated by traditional methods. Finally, the trained neural network is used to predict time-to-go. The results show that the algorithm can be used in the cooperative guidance law to complete the coordination in time, which is superior to the traditional guidance rate in coordination and has advantage in the scene of large maneuvering target.