Bayesian Sequential Track Formation
dc.contributor.author | Garcia Fernandez, Angel | |
dc.contributor.author | Morelande, M. | |
dc.contributor.author | Grajal, J. | |
dc.date.accessioned | 2017-01-30T12:25:03Z | |
dc.date.available | 2017-01-30T12:25:03Z | |
dc.date.created | 2015-04-09T09:08:03Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | Garcia Fernandez, A. and Morelande, M. and Grajal, J. 2014. Bayesian Sequential Track Formation. IEEE Transactions on Signal Processing. 62 (24): pp. 6366-6379. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/21419 | |
dc.identifier.doi | 10.1109/TSP.2014.2364013 | |
dc.description.abstract |
This paper presents a theoretical framework for track building in multiple-target scenarios from the Bayesian point of view. It is assumed that the number of targets is fixed and known. We propose two optimal methods for building tracks sequentially. The first one uses the labelling of the current multitarget state estimate that minimizes the mean-square labeled optimal subpatternassignment error. This method requires knowledge of the posterior density of the vector-valued state. The second assigns the labeling that maximizes the probability that the current multi-targetstate estimate is optimally linked with the available tracks at the previous time step. In this case, we only require knowledge of the random finite-set posterior density without labels. | |
dc.publisher | IEEE | |
dc.subject | Target labelling | |
dc.subject | Bayesian framework | |
dc.subject | multiple target tracking | |
dc.subject | random finite sets | |
dc.title | Bayesian Sequential Track Formation | |
dc.type | Journal Article | |
dcterms.source.volume | 62 | |
dcterms.source.number | 24 | |
dcterms.source.startPage | 6366 | |
dcterms.source.endPage | 6379 | |
dcterms.source.issn | 1053-587X | |
dcterms.source.title | IEEE Transactions on Signal Processing | |
curtin.note |
Copyright © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
curtin.department | Department of Electrical and Computer Engineering | |
curtin.accessStatus | Open access |