Abstract
Conventional threat assessment model based on Bayesian Network is a reasoning process in static environment, which is difficult to deal with a large number of broken air combat data in a complex dynamic battlefield environment. Motivated by this fact, a Dynamic Bayesian Network-based threat assessment model is established, and a theoretical method based on Expectation Maximization to deal with missing data is proposed. Finally, simulations are presented to verify the effectiveness of the proposed structure.
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