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Bearings-Only Tracking with Particle Filtering for Joint Parameter Learning and State Estimation

Fearnhead, Paul and Mihaylova, Lyudmila and Vorley, D. and Nemeth, Christopher (2012) Bearings-Only Tracking with Particle Filtering for Joint Parameter Learning and State Estimation. In: Information Fusion (FUSION), 2012 15th International Conference on. IEEE, pp. 824-831. ISBN 978-1-4673-0417-7

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Abstract

This paper considers the problem of bearings only tracking of manoeuvring targets. A learning particle filtering algorithm is proposed which can estimate both the unknown target states and unknown model parameters. The algorithm performance is validated and tested over a challenging scenario with abrupt manoeuvres. A comparison of the proposed algorithm with the Interacting Multiple Model (IMM) filter is presented. The learning particle filter has shown accurate estimation results and improved accuracy compared with the IMM filter.

Item Type: Contribution in Book/Report/Proceedings
Additional Information: pp. 824-831
Uncontrolled Keywords: particle filters ; state and parameter estimation ; learning algorithms ; tracking ; nonlinear systems ; IMM filter ; bearings-only tracking ; hidden Markov process ; interacting multiple model filter ; joint parameter learning ; manoeuvering targets ; particle filtering ; state estimation ; unknown model parameters ; unknown target states
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > Mathematics and Statistics
Faculty of Science and Technology > School of Computing & Communications
ID Code: 56275
Deposited By: ep_importer_pure
Deposited On: 27 Jul 2012 10:05
Refereed?: No
Published?: Published
Last Modified: 09 Oct 2013 15:42
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/56275

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