Because target tracking is a stochastic process, comparison of different tracking algorithms or parameter sets within one algorithm relies on time-consuming and computationally demanding simulations. In this paper we present a method to minimize simulation time, yet to achieve a desirable confidence of the obtained results by applying ordinal optimization and computing budget allocation ideas and techniques. The developed method is applied to optimization of sensor processing order in sequential multisensor fusion algorithms.