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A Gaussian Mixture PHD Filter for Extended Target Tracking
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-3450-988X
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2010 (English)In: Proceedings of the 13th International Conference on Information Fusion, 2010Conference paper, Published paper (Refereed)
Abstract [en]

In extended target tracking, targets potentially produce more than one measurement per time step. Multiple extended targets are therefore usually hard to track, due to the resulting complex data association. The main contribution of this paper is the implementation of a Probability Hypothesis Density (PHD) filter for tracking of multiple extended targets. A general modification of the PHD filter to handle extended targets has been presented recently by Mahler, and the novelty in this work lies in the realisation of a Gaussian mixture PHD filter for extended targets. Furthermore, we propose a method to easily partition the measurements into a number of subsets, each of which is supposed to contain measurements that all stem from the same source. The method is illustrated in simulation examples, and the advantage of the implemented extended target PHD filter is shown in a comparison with a standard PHD filter.

Place, publisher, year, edition, pages
2010.
Keyword [en]
Multi target tracking, Filtering, Estimation, Extended targets, Probability hypothesis density, Gaussian mixture
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-62852ISBN: 978-0-9824438-1-1 (print)OAI: oai:DiVA.org:liu-62852DiVA: diva2:374864
Conference
13th International Conference on Information Fusion, Edinburgh, United Kingdom, 26-29 July, 2010
Funder
Swedish Foundation for Strategic Research
Available from: 2010-12-07 Created: 2010-12-06 Last updated: 2014-03-27Bibliographically approved

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Granström, KarlLundquist, ChristianOrguner, Umut

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