| The optimal employment of autonomous search and destroy vehicles is addressed. The results apply to air, land, or water vehicles with 1, k , or infinite warheads. The specific scenarios considered involve an air vehicle searching a battle space for stationary targets in the presence of false targets. Encounters are modelled with uniform, Poisson, and normal distributions. Linear and circular search patterns are examined. All relevant parameters are extracted from intelligence information, the sensor performance specification, and the air vehicle performance specification. Analytic system effectiveness measures are derived using applied probability theory. The effectiveness measures derived in this dissertation handle time-varying parameters which characterize the battle space environment and the performance of the system. This allows the formulation and solution of optimization problems that maximize the probability of target attacks while at the same time constraining the probability of false target attacks. Optimal schedules for controlling sensor threshold and area coverage rate during a mission are derived and compared to the constant-parameter results. These schedules establish a system operating characteristic. An increase in system effectiveness is demonstrated when parameters are dynamically controlled during a mission. Plots depicting sensitivity to the constraint on false target attacks and sensitivity to the number of warheads are generated to give decision makers the complete trade space for either designing new systems or operating existing systems. |
