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dc.contributor.authorStella, M.cs_CZ
dc.contributor.authorRusso, M.cs_CZ
dc.contributor.authorBegusić, D.cs_CZ
dc.date.accessioned2015-01-22T11:09:04Zcs_CZ
dc.date.accessioned2015-01-22T14:04:01Z
dc.date.available2015-01-22T11:09:04Zcs_CZ
dc.date.available2015-01-22T14:04:01Z
dc.date.issued2012-06cs
dc.identifier.citationRadioengineering. 2012, vol. 21, č. 2, s. 557-567. ISSN 1210-2512cs
dc.identifier.issn1210-2512cs_CZ
dc.identifier.urihttp://hdl.handle.net/11012/37095cs_CZ
dc.description.abstractIn this paper indoor localization system based on the RF power measurements of the Received Signal Strength (RSS) in WLAN environment is presented. Today, the most viable solution for localization is the RSS fingerprinting based approach, where in order to establish a relationship between RSS values and location, different machine learning approaches are used. The advantage of this approach based on WLAN technology is that it does not need new infrastructure (it reuses already and widely deployed equipment), and the RSS measurement is part of the normal operating mode of wireless equipment. We derive the Cramer-Rao Lower Bound (CRLB) of localization accuracy for RSS measurements. In analysis of the bound we give insight in localization performance and deployment issues of a localization system, which could help designing an efficient localization system. To compare different machine learning approaches we developed a localization system based on an artificial neural network, k-nearest neighbors, probabilistic method based on the Gaussian kernel and the histogram method. We tested the developed system in real world WLAN indoor environment, where realistic RSS measurements were collected. Experimental comparison of the results has been investigated and average location estimation error of around 2 meters was obtained.en
dc.formattextcs
dc.format.extent557-567cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2012/12_02_0557_0567.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectIndoor localizationen
dc.subjectReceived Signal Strength (RSS)en
dc.subjectCramer-Rao Lower Bound (CRLB)en
dc.subjectlocation fingerprintsen
dc.titleRF Localization in Indoor Environmenten
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue2cs
dc.coverage.volume21cs
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Except where otherwise noted, this item's license is described as Creative Commons Attribution 3.0 Unported License