Multiple detection joint integrated track splitting for multiple extended target tracking

The extended target tracking problem, which occurs due to a high-resolution sensor resolving multiple scattering points of a target, is considered in this paper. Typical target tracking algorithms which use the point target assumption yield poor performances in extended target tracking scenarios, especially in the presence of closely spaced targets. This performance degeneration is mainly caused by a number of measurements that are shared among tracks when the extended targets are closely spaced. In order to achieve robust tracking performances in multiple extended target tracking environments, a novel tracker, named multiple detection joint integrated track splitting (MD-JITS), is proposed here. This tracker incorporates the measurement cells and the random matrix into a target existence based multitarget track splitting structure. In MD-JITS, each track builds a type of tree, and each branch of the tree is a track component corresponding to a sequence of data associations for multiple scans. The track kinematic state and extension state are obtained on the basis of the track components. Then, the proposed algorithm is tested using both Monte Carlo simulations and a real video surveillance application to demonstrate the effectiveness.