Target assignment and sorting for multi-target attack in Multi-aircraft coordinated based on RBF

In this paper, we make the UAV air combat as the background. Based on air combat situation and target´s air combat ability, the threat evaluation model of UAV air combat is established, then it uses RBF neural network to identify complex nonlinear relation between the types of threats to get the overall threat situation. In the course of air combat, we get the threat situation index of air combat, and then get the target threat matrix through RBF neural network. Finally, it uses the matrix method to get the result of target assignment and sorting. The experimental results show that RBF neural network can successfully approximate the weights of all the types of threats.