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), 00. 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:	22 May 2026 21:02
DOI:	10.23919/ICIF.2018.8455270
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3033095
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