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<p>In this thesis, we present a Markov-based probability model for a human operated  system of aerial hunter-killers attacking time-sensitive targets. We explore the effect of  two resources -- time and supply of munitions --  and some cognitive aspects of the human  operator on the performance of the system in different operational scenarios. We model  the combat mission as a sequence of engagements; each of which includes a classification  process, followed by a firing decision, and a shooting process. The model of the  classification process addresses possible effects of stress on the operator's behavior and  performance. Two shooting tactics are considered. The random shooting tactic, which is  memory-less and with no fire control, BDA capability or mission support systems, sets a  benchmark for more effective shoot-look-shoot tactic, where resources are utilized more  efficiently. The model represents various tactical parameters regarding rules of  engagement and various mixes of resources. Applying the model on some real-world  scenarios, we identify mixes of resources and tactical engagement rules that enhance the  effectiveness and efficiency of the combat mission.
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<br>Subjects: Air warfare; Tactics; Ammunition; Decision making; Operations research</div>
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Berman, Ohad</div>
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