Poisson Multi-Bernoulli Mixture Trackers: Continuity Through Random Finite Sets of Trajectories

Granström, Karl, Svensson, Lennart, Xia, Yuxuan, Williams, Jason and García-Femández, Ángel F (2018) Poisson Multi-Bernoulli Mixture Trackers: Continuity Through Random Finite Sets of Trajectories In: 2018 21st International Conference on Information Fusion (FUSION).

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Abstract

The Poisson multi-Bernoulli mixture (PMBM) is an unlabelled multi-target distribution for which the prediction and update are closed. It has a Poisson birth process, and new Bernoulli components are generated on each new measurement as a part of the Bayesian measurement update. The PMBM filter is similar to the multiple hypothesis tracker (MHT), but seemingly does not provide explicit continuity between time steps. This paper considers a recently developed formulation of the multi-target tracking problem as a random finite set (RFS) of trajectories, and derives two trajectory RFS filters, called PMBM trackers. The PMBM trackers efficiently estimate the set of trajectories, and share hypothesis structure with the PMBM filter. By showing that the prediction and update in the PMBM filter can be viewed as an efficient method for calculating the time marginals of the RFS of trajectories, continuity in the same sense as MHT is established for the PMBM filter.

Item Type:	Conference Item (Unspecified)
Uncontrolled Keywords:	40 Engineering, 4001 Aerospace Engineering
Depositing User:	Symplectic Admin
Date Deposited:	19 Feb 2019 10:20
Last Modified:	22 May 2026 21:38
DOI:	10.23919/icif.2018.8455849
Related Websites:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3033094
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