The characteristic parameters of certain fast tracking algorithms were estimated for a single target in [1-4]under assumptions of a clean environment Cno clutter returns) and a 100% probability of detection Cy. n the present work,we extend our study to more realistic tracking environments.Characteristic properties of both the tapped-delay-line CTDL) fast Kalman Clland the gradient lattice [2 tracking algorithms are considered in the presence of clutter returns. Presence of clutter returns transform the mono target tracking problems into a multi-target case. This entails some form of data association along with the necessary gating so as to mitigate theassociated computational burden.A single target is assumed to be tracked in conditions of clutter that may lower probability Po. A nearest-neighbor CNN) approach to the data association problem is adopted and an algorithm has been developed for investigating effects of gate dimensions on the probability of correct decision P , as well as investigating the effects of PD and the clutter CD density on P and consequently on tracking the assumed target CD with fast Kalman and gradient lattice tracking filter. This study shows that the probability of losing track increases, and the average track life decreases significantly with increasinn clutter density as well as with lowering detection probability. Fast Kalman filter provides.however. a slightly longer track life with lower probability of loosing track at 100% Pp as compared to the lattice filter.Moreover .both algorithms, no improvement in tracking properties was gained with higher-order filters CN>2).