Aggregate models for target acquisition in urban terrain
Mlakar, Joseph A.
Rasmussen, Craig W.
Cioppa, Thomas M.
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High-resolution combat simulations that model urban combat currently use computationally expensive algorithms to represent urban target acquisition at the entity level. While this may be suitable for small-scale urban combat scenarios, simulation run time can become unacceptably long for larger scenarios. Consequently, there is a need for models that can lend insight into target acquisition in urban terrain for largescale scenarios in an acceptable length of time. This research develops urban target acquisition models that can be substituted for existing physicsbased or computationally expensive combat simulation algorithms and result in faster simulation run time with an acceptable loss of aggregate simulation accuracy. Specifically, this research explores (1) the adaptability of probability of line of sight estimates to urban terrain; (2) how cumulative distribution functions can be used to model the outcomes when a set of sensors is employed against a set of targets; (3) the uses for Markov Chains and Event Graphs to model the transition of a target among acquisition states; and (4) how a system of differential equations may be used to model the aggregate flow of targets from one acquisition state to another.
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