Tracking Random Sets of Vehicles in Terrain

This paper presents a particle filtering formulation for tracking an unknown and varying number of vehicles in terrain. The vehicles are modeled as a random set, i.e. a set of random variables, for which the cardinality is itself a random variable. The particle filter formulation is here extended according to finite set statistics (FISST) which is an extension of Bayesian theory to define operations on random sets. The filter was successfully tested on a simulated scenario with three vehicles moving in terrain, observed by humans in the terrain.