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dc.contributor.authorBattistello, G.
dc.contributor.authorUlmke, M.
dc.contributor.authorPapi, Francesco
dc.contributor.authorPodt, M.
dc.contributor.authorBoers, Y.
dc.date.accessioned2017-01-30T11:57:05Z
dc.date.available2017-01-30T11:57:05Z
dc.date.created2015-10-29T04:09:49Z
dc.date.issued2012
dc.identifier.citationBattistello, G. and Ulmke, M. and Papi, F. and Podt, M. and Boers, Y. 2012. Assessment of vessel route information use in Bayesian non-linear filtering, in 15th International Conference on Information Fusion, FUSION 2012, pp. 447-454.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/16655
dc.description.abstract

Bayesian non-linear filtering is considered in this paper for the state vector estimation of manoeuvring targets at sea. Innovative schemes based on the Extended Kaiman Filter and the Particle Filter are derived by the introduction of a priori vessel route information. Such contextual input drives the selection of the manoeuvre model to be used for target state prediction. This aims at coping with significant measurement gaps suffered by coastal sensors - due to their limited spatial coverage or temporal revisit. The capabilities of the context-aided techniques are assessed for realistic scenarios that include typical vessel manoeuvres. The Kullback-Leibler Divergence is adopted as performance metric. The analysis demonstrates that the use of the a priori information yields dramatic improvements in highly non-linear conditions for target tracking, and the Particle Filter outperforms the Extended Kaiman filter approach in the exploitation of the route information. © 2012 ISIF (Intl Society of Information Fusi).

dc.titleAssessment of vessel route information use in Bayesian non-linear filtering
dc.typeConference Paper
dcterms.source.startPage447
dcterms.source.endPage454
dcterms.source.title15th International Conference on Information Fusion, FUSION 2012
dcterms.source.series15th International Conference on Information Fusion, FUSION 2012
dcterms.source.isbn9780982443859
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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