Tracking Multi-target And Target Types Using Random Sets
Shurong Tian, You He, Yi Xiao · 2006
When tracking unknown number of targets, or number of targets varying with time, random finite sets are natural representations of multi-target sets and observations that allow multi-sensor multi-target filtering to fit in the unifying random set framework for data fusion. This paper presents a framework for tracking multiple targets and target types using random finite sets. Simulations are also presented to demonstrate the performance in tracking a varying number of targets