Nonparametric Bayesian filtering for location estimation, position tracking, and global localization of mobile terminals in outdoor wireless environments

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dc.identifier.uri http://dx.doi.org/10.15488/1742
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/1767
dc.contributor.author Khalaf-Allah, M.
dc.date.accessioned 2017-07-19T07:41:50Z
dc.date.available 2017-07-19T07:41:50Z
dc.date.issued 2008
dc.identifier.citation Khalaf-Allah, M.: Nonparametric Bayesian filtering for location estimation, position tracking, and global localization of mobile terminals in outdoor wireless environments. In: Eurasip Journal on Advances in Signal Processing 2008 (2008), 317252. DOI: https://doi.org/10.1155/2008/317252
dc.description.abstract The mobile terminal positioning problem is categorized into three different types according to the availability of (1) initial accurate location information and (2) motion measurement data.Location estimation refers to the mobile positioning problem when both the initial location and motion measurement data are not available. If both are available, the positioning problem is referred to as position tracking. When only motion measurements are available, the problem is known as global localization. These positioning problems were solved within the Bayesian filtering framework. Filter derivation and implementation algorithms are provided with emphasis on the mapping approach. The radio maps of the experimental area have been created by a 3D deterministic radio propagation tool with a grid resolution of 5 m. Real-world experimentation was conducted in a GSM network deployed in a semiurban environment in order to investigate the performance of the different positioning algorithms. eng
dc.language.iso eng
dc.publisher Heidelberg : Springer Verlag
dc.relation.ispartofseries Eurasip Journal on Advances in Signal Processing 2008 (2008)
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Algorithms eng
dc.subject Global system for mobile communications eng
dc.subject Grid computing eng
dc.subject Motion estimation eng
dc.subject Bayesian filtering eng
dc.subject Filter derivation eng
dc.subject Location estimation eng
dc.subject Motion measurement data eng
dc.subject Wireless networks eng
dc.subject.ddc 621,3 | Elektrotechnik, Elektronik ger
dc.title Nonparametric Bayesian filtering for location estimation, position tracking, and global localization of mobile terminals in outdoor wireless environments
dc.type Article
dc.type Text
dc.relation.issn 1687-6172
dc.relation.doi https://doi.org/10.1155/2008/317252
dc.bibliographicCitation.volume 2008
dc.bibliographicCitation.firstPage 317252
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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