Modified extended object tracker for 2D lidar data using random matrix model

Sci Rep. 2023 Mar 29;13(1):5095. doi: 10.1038/s41598-023-32236-w.

Abstract

The random matrix (RM) model is a typical extended object-modeling method that has been widely used in extended object tracking. However, existing RM-based filters usually assume that the measurements follow a Gaussian distribution, which may lead to a decrease in accuracy when the filter is applied to the lidar system. In this paper, a new observation model used to modify an RM smoother by considering the characteristics of 2D LiDAR data is proposed. Simulation results show that the proposed method achieves a better performance than the original RM tracker in a 2D lidar system.