Research on airspace target threat assessment model in sea battlefield based on GA-RBF

Abstract

The target threat assessment is to quantitatively estimate the target threat level by using the multi-level view generated by the situation assessment, which is an important basis for command and decision in the C2 process. This paper takes the sea battlefield airspace target as the research object and carries out the research on the airspace target threat assessment, systematically analyzes the types and threat factors of airspace targets, extracts the main threat factors for quantification, introduces neural network methods, and designs a genetic algorithm-optimized radial basis neural network (GA-RBF) airspace target threat assessment model to launch threat assessment. By comparing the threat assessment results of other literatures, it is shown that the GA-RBF can effectively evaluate the airspace target threat. This paper provides technical support for the intelligent combat C2 system construction, it also has important theoretical value and military significance.