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Spatial statistical analysis for the design of indoor particle-filter-based localization mechanisms

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dc.contributor.authorMartínez Gómez, Jesús
dc.contributor.authorMartínez del Horno, Miguel
dc.contributor.authorBrea Luján, Victor Manuel
dc.contributor.authorOrozco Barbosa, Luis
dc.contributor.authorGarcía Varea, Ismael
dc.contributor.authorCastillo Cara, José Manuel
dc.date.accessioned2024-05-20T11:42:21Z
dc.date.available2024-05-20T11:42:21Z
dc.date.issued2016-08-24
dc.description.abstractThe accurate localization of end-users and resources is seen as one of the main pillars toward the successful implementation of context-based applications. While current outdoor localization mechanisms fulfill most application requirements, the design of accurate indoor localization mechanisms is still an open issue. Most research efforts are focusing on the design of mechanisms making use of the receiver signal strength indications generated by WLAN (wireless local area network) devices. However, the accuracy and robustness of such mechanisms can be severely compromised due to the random and unpredictable nature of radio channels. In this article, we develop a methodology incorporating various algorithms capable of coping with the unpredictable nature of radio channels. Following a holistic approach, we start by identifying the wireless equipment parameter setting, better meeting the implementation requirements of a robust indoor localization mechanism. We then make use of RANdom SAmple Consensus paradigm: a robust model-fitting mechanism capable of smoothing the data captured during the space survey. Using an experimental setup, we evaluate the benefits of integrating the floor plan and an ordinary Kriging interpolation algorithm in the estimation process. Our main findings show that our proposal can greatly improve the quality of the information to be used in the development of particle-filter-based indoor localization mechanisms.en
dc.description.versionversión publicada
dc.identifier.doihttps://doi.org/10.1177/1550147716661953
dc.identifier.urihttps://hdl.handle.net/20.500.14468/12444
dc.journal.titleJournal of Distributed Sensor Networks
dc.language.isoen
dc.publisherSAGE
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentInteligencia Artificial
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/deed.en
dc.subject.keywordsLocalization
dc.subject.keywordsmobile devices
dc.subject.keywordssignal processing
dc.subject.keywordsmodel fitting
dc.subject.keywordswireless local area networks
dc.subject.keywordsspatial analysis
dc.titleSpatial statistical analysis for the design of indoor particle-filter-based localization mechanismses
dc.typejournal articleen
dc.typeartículoes
dspace.entity.typePublication
relation.isAuthorOfPublicationc0e39bd2-c0d8-4743-953d-488baf6b977e
relation.isAuthorOfPublication.latestForDiscoveryc0e39bd2-c0d8-4743-953d-488baf6b977e
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