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dc.contributor.authorGarcia Fernandez, Angel
dc.contributor.authorMorelande, M.
dc.contributor.authorGrajal, J.
dc.date.accessioned2018-02-06T06:14:11Z
dc.date.available2018-02-06T06:14:11Z
dc.date.created2018-02-06T05:49:52Z
dc.date.issued2011
dc.identifier.citationGarcia Fernandez, A. and Morelande, M. and Grajal, J. 2011. Multitarget simultaneous localization and mapping of a sensor network. IEEE Transactions on Signal Processing. 59 (10): pp. 4544-4558.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/62915
dc.identifier.doi10.1109/TSP.2011.2160862
dc.description.abstract

This paper addresses the problem of simultaneously localizing multiple targets and estimating the positions of the sensors in a sensor network using particle filters. We develop a new technique called multitarget simultaneous localization and mapping (MSLAM) that has better performance than the well-known FastSLAM when there are several targets in the surveillance area. The proposed algorithm is based on the parallel partition particle filter, especially designed for multiple target tracking, and the truncated unscented Kalman filter for updating the sensors' positions. © 2011 IEEE.

dc.publisherIEEE
dc.titleMultitarget simultaneous localization and mapping of a sensor network
dc.typeJournal Article
dcterms.source.volume59
dcterms.source.number10
dcterms.source.startPage4544
dcterms.source.endPage4558
dcterms.source.issn1053-587X
dcterms.source.titleIEEE Transactions on Signal Processing
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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