Extended object tracking with unknown association, missing observations, and clutter using particle filters

A new method for target tracking of multiple points on an object by using particle filter with its novel importance function is proposed. The assumptions are such that the number of points is fixed and known, and the association between points of object and observed points are unknown. There exists missing and clutter in observation process where which observation corresponds to them are also unknown. The main difficulty of this problem is the formidable number of combinations in the association. The novel importance function using an idea of soft gating makes the problem tractable in a proper framework of particle filter. Simulation experiment illustrates the performance of the method. 1