Trajectory probability hypothesis density filter



Garcia-Fernandez, Angel F ORCID: 0000-0002-6471-8455 and Svensson, Lennart
(2018) Trajectory probability hypothesis density filter. 2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), abs/16. pp. 1430-1437.

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Abstract

This paper presents the probability hypothesis density (PHD) filter for sets of trajectories: the trajectory probability density (TPHD) filter. The TPHD filter is capable of estimating trajectories in a principled way without requiring to evaluate all measurement-to-target association hypotheses. The TPHD filter is based on recursively obtaining the best Poisson approximation to the multitrajectory filtering density in the sense of minimising the Kullback-Leibler divergence. We also propose a Gaussian mixture implementation of the TPHD recursion. Finally, we include simulation results to show the performance of the proposed algorithm.

Item Type: Article
Additional Information: Published in the Proceedings of the 21st International Conference on Information Fusion (FUSION)
Uncontrolled Keywords: Random finite sets, multitarget tracking, sets of trajectories, PHD filter
Depositing User: Symplectic Admin
Date Deposited: 19 Feb 2019 10:12
Last Modified: 19 Jan 2023 01:02
DOI: 10.23919/icif.2018.8455270
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3033095