Multi scan target tracking with finite resolution sensors

Target tracking algorithms operate in an environment of uncertain measurement origin. Targets are randomly detected, and clutter measurements from unwanted random scatterers are present. A vast majority of target tracking algorithms have been developed with the assumption of infinite sensor resolution, where a measurement can have only one source. This assumption is not valid for real sensors, such as radars, where measurements from multiple sources may merge. This paper presents a multi-scan target tracking algorithm which removes this restriction. For each measurement the probability that this is a measurement formed by merging a clutter measurement with the target detection is calculated. The merging event creates new data association possibilities, and alters the track quality measure. Both a single target and a suboptimal multi target tracking algorithms are presented. A simulation study shows the benefits of this approach.