We develop an object-oriented simulation that models the surveillance and Active Suppression of Enemy Air Defense (SEAD) missions of the Unmanned Aerial Vehicle (UAV) RQ-1A Predator. The simulation, written in Java using the Silk simulation package, interfaces with a Reactive Tabu Search routing algorithm to provide optimal UAV routes. The routing algorithm is called by the simulation to account for changes in weather conditions and to provide a means of dynamically retasking the UAV. The simulation and analysis support a UAV battlelab initiative to test the operational effects of proposed changes in Predator performance and UAV capability to perform in an Active SEAD mission. Analysis efforts examine the effect of speed, endurance, and weather susceptibility on UAV operational effectiveness and the effects of radar cross section, threat density, and threat lethality on UAV Active SEAD mission performance.


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