This paper focuses on threat assessment of aerial target under uncertain environment.First, the problem of uncertain information is solved by using fuzzy neural networks.In the environment with less threat target information, the wavelet neural network is used to enhance the self-learning ability of the network and the threat factors are analyzed.The Fuzzy Wavelet Neural Network (FWNN) in the uncertain environment is established to achieve the target threat evaluation.For the uncertainty of the initial parameters, the consequent parameters of each fuzzy rule are updated by using the particle swarm optimization algorithm and the BP algorithm to achieve the purpose of improving the evaluation effect.The simulation results show that:Compared with the fuzzy wavelet neural network, the stability of the system is improved, the convergence speed is accelerated, and the prediction accuracy is enhanced.