Research on the Strategy of Ballistic Missile Midcourse Recognition Based on Bayesian Network

Midcourse recognition of ballistic missile is one of the core problems in anti-missile early warning operations. Considering the variety of penetration means of ballistic missile, aiming at the attitude characteristics of missile in midcourse flight, this paper focuses on the analysis of five technologies suitable for the midcourse recognition of the warhead, such as the RCS sequence, establishes a Bayesian network model for midcourse recognition of warhead, and standardizes the conditional probability representation of the results of the five techniques according to the actual usage. Finally, the effectiveness of the model is verified by simulation experiments. Through the Bayesian network comprehensive recognition method, the warhead target can be recognized quickly and accurately, and the model has a certain fault tolerance. This model can provide a reference for the warhead recognition in the midcourse of anti-missile early warning combat.