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dc.contributor.authorMaskell, S
dc.date.accessioned2011-11-09T20:08:47Z
dc.date.available2011-11-09T20:08:47Z
dc.date.issued2004-11-01
dc.identifierhttp://dx.doi.org/10.1155/S1110865704404223
dc.identifier.issn1110-8657
dc.identifier.urihttp://www.dspace.cam.ac.uk/handle/1810/240503
dc.descriptionRIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.
dc.description.abstractSemi-Markov models are a generalisation of Markov models that explicitly model the state-dependent sojourn time distribution, the time for which the system remains in a given state. Markov models result in an exponentially distributed sojourn time, while semi-Markov models make it possible to define the distribution explicitly. Such models can be used to describe the behaviour of manoeuvring targets, and particle filtering can then facilitate tracking. An architecture is proposed that enables particle filters to be both robust and efficient when conducting joint tracking and classification. It is demonstrated that this approach can be used to classify targets on the basis of their manoeuvrability.
dc.publisherSpringer Science and Business Media LLC
dc.rightsAll Rights Reserved
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/
dc.titleJoint tracking of manoeuvring targets and classification of their manoeuvrability
dc.typeArticle
dc.date.updated2011-11-09T20:08:48Z
dc.description.versionPeer Reviewed
dc.language.rfc3066en
dc.rights.holderet al.; licensee BioMed Central Ltd.
prism.publicationNameEURASIP J APPL SIG P
pubs.declined2017-10-11T13:54:31.18+0100
rioxxterms.versionofrecord10.1155/S1110865704404223
dc.identifier.eissn1687-0433
cam.issuedOnline2004-11-07


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