Modified Extended Object Tracker for Lidar Data using Random Matrix Model

Abstract

Random Matrix (RM) model is a typical extended objectmodeling method, and has been widely used in extended object tracking. However, the existing RM based filters usually under a assumption that the measurements obey Gaussian distribution, which may lead to the decrease of accuracy when the filter applied to Lidar system. This paper proposed a new observation model and used it to modified a RM smoother by considering the characteristics of Lidar data. Simulation results show that the proposed method achieved better performance compared with the original RM tracker in Lidar system.