Threat Assessment in Air Combat Based on ELM Neural Network

Threat assessment is a key issue in air combat situation awareness. A new method based on the extreme learning machine (ELM) neural network is proposed against the shortcomings of the existing assessment methods that are difficult to satisfy both accuracy and real-time performance. The air combat data is selected from the air combat maneuvering instrument (ACMI), and the threat assessment sample data is established based on the threat index method. The threat assessment model based on the ELM neural network is constructed, and the accuracy and real-time performance of the model are analyzed by simulation. The results show that the method not only has high accuracy, but also has good efficiency, and can accurately and quickly perform target threat assessment in air combat.