Comparison of theoretical and simulated performance of optimal and suboptimal filters in a dense multitarget environment

Monte Carlo simulation results demonstrate the validity of the theoretical approach developed recently for optimal filter design and tracking filter error analysis for dense multitarget environments. The predicted error divergence phenomenon is shown to be observed experimentally and to be characterized by an increasing frequency of lost tracks as density increases. The whiteness assumption in the miscorrelation model is examined, and the performance degradations obtained using finite gates are presented.