Target threat assessment model based on PCA-BP neural network

In this paper, the air threat received in modern naval warfare is taken as the background, and based on the threat assessment index, PCA and BP neural networks are used to establish a target threat assessment model. Through simulation and analysis, the threat values of different incoming targets are derived, and the data results of this model and other models are compared. It is concluded that the results of this model are basically consistent with the original values, and the error is significantly smaller than that of the other models, which realizes the real-time dynamic detection of threatening targets, and provides a strong support for the subsequent combat program.