Air Target Combat Intention Identification Based on IE-DSBN

Air target combat intention identification is a key step in modern air combat. Effective identification can improve the effectiveness of target threat assessment and assist commanders to make decisions. In order to optimize the operational intention recognition algorithm based on the dynamic sequence bayesian network, the information entropy theory is introduced in this paper to objectively allocate the attribute weight by analyzing the amount of useful information provided by different participating attributes. In the hypothetical air combat scenario, this model can effectively realize the combat intention identification.