Bayesian estimation of multi-object systems with independently identically distributed correlations

Jeremie Houssineau, Daniel E. Clark

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent generalisations of stochastic filtering methods to multi-object systems have become very popular for solving multi-target tracking problems over the last decade. However, there was previously no general means of introducing correlations between objects. In this article, we investigate generalisations of such multi-object filters for systems where there may be dependencies between objects. Determining probability and factorial moment densities is facilitated by the use of a recent result in variational calculus, a general form of Faà di Bruno's formula. The result is illustrated through the Probability Hypothesis Density (PHD) filter, as a first-order moment example of the general form.

Original languageEnglish
Title of host publicationIEEE Workshop on Statistical Signal Processing Proceedings
PublisherIEEE
Pages228-231
Number of pages4
ISBN (Print)9781479949755
DOIs
Publication statusPublished - 2014
Event17th IEEE Workshop on Statistical Signal Processing 2014 - Gold Coast, Australia
Duration: 29 Jun 20142 Jul 2014

Conference

Conference17th IEEE Workshop on Statistical Signal Processing 2014
Abbreviated titleSSP 2014
CountryAustralia
CityGold Coast
Period29/06/142/07/14

Fingerprint

Bayesian Estimation
Identically distributed
Filter
Factorial Moments
Variational techniques
Variational Calculus
Multi-target Tracking
Target tracking
Filtering
Moment
First-order
Object
Generalization
Form

Keywords

  • POINT-PROCESSES

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Applied Mathematics
  • Signal Processing
  • Computer Science Applications

Cite this

Houssineau, J., & Clark, D. E. (2014). Bayesian estimation of multi-object systems with independently identically distributed correlations. In IEEE Workshop on Statistical Signal Processing Proceedings (pp. 228-231). [6884617] IEEE. https://doi.org/10.1109/SSP.2014.6884617
Houssineau, Jeremie ; Clark, Daniel E. / Bayesian estimation of multi-object systems with independently identically distributed correlations. IEEE Workshop on Statistical Signal Processing Proceedings. IEEE, 2014. pp. 228-231
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Houssineau, J & Clark, DE 2014, Bayesian estimation of multi-object systems with independently identically distributed correlations. in IEEE Workshop on Statistical Signal Processing Proceedings., 6884617, IEEE, pp. 228-231, 17th IEEE Workshop on Statistical Signal Processing 2014, Gold Coast, Australia, 29/06/14. https://doi.org/10.1109/SSP.2014.6884617

Bayesian estimation of multi-object systems with independently identically distributed correlations. / Houssineau, Jeremie; Clark, Daniel E.

IEEE Workshop on Statistical Signal Processing Proceedings. IEEE, 2014. p. 228-231 6884617.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Recent generalisations of stochastic filtering methods to multi-object systems have become very popular for solving multi-target tracking problems over the last decade. However, there was previously no general means of introducing correlations between objects. In this article, we investigate generalisations of such multi-object filters for systems where there may be dependencies between objects. Determining probability and factorial moment densities is facilitated by the use of a recent result in variational calculus, a general form of Faà di Bruno's formula. The result is illustrated through the Probability Hypothesis Density (PHD) filter, as a first-order moment example of the general form.

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Houssineau J, Clark DE. Bayesian estimation of multi-object systems with independently identically distributed correlations. In IEEE Workshop on Statistical Signal Processing Proceedings. IEEE. 2014. p. 228-231. 6884617 https://doi.org/10.1109/SSP.2014.6884617