A Comparison between Two Approaches to Threat Evaluation in an Air Defense Scenario

Threat evaluation is a high-level information fusion problem of high importance within the military domain. This task is the foundation for weapons allocation, where assignment of blue force (own) weapon systems to red force (enemy) targets is performed. In this paper, we compare two fundamentally different approaches to threat evaluation: Bayesian networks and fuzzy inference rules. We conclude that there are pros and cons with both types of approaches, and that a hybrid of the two approaches seems both promising and viable for future research.

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