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In the context of close ground combat, the perception of Battle
Damage Assessment (BDA) is closely linked with a soldier's
engagement decisions and has significant effects on the
battlefield. Perceived BDA is also one of the most complex and
uncertain processes facing the soldier in live combat. As a result,
the modeling and simulation community has yet to adequately model
the perceived BDA process in combat models. This research effort
examines the BDA process from a perception standpoint and proposes
a methodology to collect the pertinent data and model this
perception in the Army's current force-on-force model, CASTFOREM. A
subject matter expert survey design and a method to model the BDA
process as a Discrete Time Markov Chain are proposed. Bayesian
inference is used to update probability distributions at each time
step considering the situational parameters available to the
soldier at the time of an assessment. Comparisons between the known
simulation distributions and those developed from simulated survey
responses suggest an adequate number of subject matter experts to
be polled.
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