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A Monte Carlo expectation maximisation algorithm for multiple target tracking

Yildirim, S and Singh, SS and Dean, T (2012) A Monte Carlo expectation maximisation algorithm for multiple target tracking. 15th International Conference on Information Fusion, FUSION 2012. pp. 2094-2101.

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Abstract

In this paper, we present an expectation-maximisation (EM) algorithm for maximum likelihood estimation in multiple target models (MTT) with Gaussian linear state-space dynamics. We show that estimation of sufficient statistics for EM in a single Gaussian linear state-space model can be extended to the MTT case along with a Monte Carlo approximation for inference of unknown associations of targets. The stochastic approximation EM algorithm that we present here can be used along with any Monte Carlo method which has been developed for tracking in MTT models, such as Markov chain Monte Carlo and sequential Monte Carlo methods. We demonstrate the performance of the algorithm with a simulation. © 2012 ISIF (Intl Society of Information Fusi).

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 12:25
Last Modified: 08 Dec 2014 02:35
DOI: