Extended Target Tracking with Constrained PMHT
Jean-Francois Bariant, Llarina Lobo Palacios, Julia Granitzka, Hanne Groener · 2022 25th International Conference on Information Fusion (FUSION) · 2022
This paper aims at adressing specific issues of extended target tracking. Firstly, we propose a method to accurately model the origin of the measurements on the surface of the target. This is achieved by removing the usual hypothesis of the independence of the association of the measurements to possible measurement sources to allow us to assume that a certain number of measurements shall be originating from some specific sources. Secondly, a Gaussian distribution is a poor representation for the length of a target. We developed a method discretizing the length to estimate its distribution without the Gaussian assumption but avoiding the computational burden of a multi-hypothesis tracking for each target. The implementation effectiveness is shown on simulated as well as real data from RADAR.