This academic article introduces a new algorithm for extended target tracking, which estimates the centroid and shape of a target over time. The authors address the issue of interference when tracking multiple targets, particularly when they maneuver behind one another. They propose a Spatio-Temporal Joint Probabilistic Data Association Coupled Filter (ST-JPDACF) that manages the dependency of measurements in space and time using kernel functions. The algorithm shows promising results when compared to other supervised methods in interfering cases.
Publication date: 29 Nov 2023
Project Page: 10.1109/ACCESS.20 22.Doi Number
Paper: https://arxiv.org/pdf/2311.16106
