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

Research output: Contribution in Book/Report/ProceedingsPaper

Published

Publication date7/07/2012
Host publicationInformation Fusion (FUSION), 2012 15th International Conference on
PublisherIEEE
Pages824-831
Number of pages8
ISBN (Electronic)978-0-9824438-4-2
ISBN (Print)978-1-4673-0417-7
Original languageEnglish

Conference

ConferenceThe 15th International Conference on Information Fusion
CountrySingapore
Period9/07/1212/07/12

Conference

ConferenceThe 15th International Conference on Information Fusion
CountrySingapore
Period9/07/1212/07/12

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.

Bibliographic note

pp. 824-831