Bayesian Sequential Track Formation

Garcia-Fernandez, Angel F ORCID: 0000-0002-6471-8455, Morelande, Mark R and Grajal, Jesus (2014) Bayesian Sequential Track Formation. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 62 (24). pp. 6366-6379.

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Official URL: http://dx.doi.org/10.1109/tsp.2014.2364013

Abstract

This paper presents a theoretical framework for track building in multiple-target scenarios from the Bayesian point of view. It is assumed that the number of targets is fixed and known. We propose two optimal methods for building tracks sequentially. The first one uses the labelling of the current multitarget state estimate that minimizes the mean-square labeled optimal subpattern assignment error. This method requires knowledge of the posterior density of the vector-valued state. The second assigns the labeling that maximizes the probability that the current multi-target state estimate is optimally linked with the available tracks at the previous time step. In this case, we only require knowledge of the random finite-set posterior density without labels.

Item Type:	Article
Uncontrolled Keywords:	Target labelling, multiple target tracking, Bayesian framework, random finite sets
Depositing User:	Symplectic Admin
Date Deposited:	16 Oct 2019 07:54
Last Modified:	16 Mar 2024 16:34
DOI:	10.1109/TSP.2014.2364013
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3058308