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Fusion of finite set distributions: Pointwise consistency and global cardinality

Uney, M; Houssineau, J; Delande, E; Julier, SJ; Clark, D; (2019) Fusion of finite set distributions: Pointwise consistency and global cardinality. IEEE Transactions on Aerospace and Electronic Systems 10.1109/TAES.2019.2893083. (In press). Green open access

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Abstract

A recent trend in distributed multi-sensor fusion is to use random finite set filters at the sensor nodes and fuse the filtered distributions algorithmically using their exponential mixture densities (EMDs). Fusion algorithms that extend covariance intersection and consensus based approaches are such examples. In this article, we analyse the variational principle underlying EMDs and show that the EMDs of finite set distributions do not necessarily lead to consistent fusion of cardinality distributions. Indeed, we demonstrate that these inconsistencies may occur with overwhelming probability in practice, through examples with Bernoulli, Poisson and independent identically distributed (IID) cluster processes. We prove that pointwise consistency of EMDs does not imply consistency in global cardinality and vice versa. Then, we redefine the variational problems underlying fusion and provide iterative solutions thereby establishing a framework that guarantees cardinality consistent fusion.

Type: Article
Title: Fusion of finite set distributions: Pointwise consistency and global cardinality
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TAES.2019.2893083
Publisher version: https://doi.org/10.1109/TAES.2019.2893083
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
Keywords: Uncertainty , Signal processing algorithms , Probability density function , Sensors , Message passing , Licenses, random finite sets , multi-sensor fusion , exponential mixture density , covariance intersection , target tracking
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10069137
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