Since the traditional threat assessment methods can’t reflect the changing of threat factors during air combat,a dynamic weight calculating method was proposed based on particle swarm and radical basis function neural network (PSO-RBF) by introducing RBF neural network and using a new structure entropy weight method to optimize the training parameters of RBF neural network.On the circumstance of assessing the threat degree during multi-UCAV cooperative combat,simulations were executed by using structure entropy weight method and PSO-RBF method respectively.The result proved that the PSO-RBF process can assess the threat degree of the target during air combat effectively and make the strategic decision more objective and reasonable.