The use of RSS and NI Filtering for the Wireless Indoor Localization and Tracking of Mobile Robots with Different Motion Models

Basit Öğe Kaydı
dc.authoridKarakusak, Muhammed Zahid/0000-0001-6363-2732
dc.contributor.authorKarakusak, Muhammed Z.
dc.contributor.authorOzdemir, Kemal
dc.contributor.authorAslantas, Veysel
dc.date.accessioned2024-09-29T16:11:24Z
dc.date.available2024-09-29T16:11:24Z
dc.date.issued2016
dc.departmentKarabük Üniversitesien_US
dc.description24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEYen_US
dc.description.abstractIn recent years there has been a rapid increase in indoor applications of mobile robots, where the knowledge of real-time location has become more and more important. In this framework, the methods about the location estimation are gaining the focus under the umbrella of Indoor Positioning technology, which is suitable for location-based applications. Here, for the purpose of dynamic and static tracking of a mobile user's location, we combine RSS (Received Signal Strength) measurement of WLANs (Wireless Local Area Networks) with the dynamic modeling of the mobile user. The joint approach is preferred for the minimization of the errors that are bound to occur due to RSS and to improve the accuracy of the overall estimation. This is accomplished through Non-Parametric Information Filter (NI Filter), which does not require an explicit information concerning RSS-position, and the Likelihood Density Estimation, which has low-error rate performance. The overall approach enabled us to develop two algorithms for different dynamic motions. Experimental results are obtained by actual measurements in an office environment and ARMSE (Average Root Mean Square Error) has been used as the assessment criteria. The study in mitigating the difficulties arising due to the unpredictable nature of RSS in indoor environment presented an improvement of 5.15m (49,76 %) in positioning error relative to Memoryless Positioning alone.en_US
dc.description.sponsorshipIEEE,Bulent Ecevit Univ, Dept Elect & Elect Engn,Bulent Ecevit Univ, Dept Biomed Engn,Bulent Ecevit Univ, Dept Comp Engnen_US
dc.identifier.endpage1712en_US
dc.identifier.isbn978-1-5090-1679-2
dc.identifier.startpage1709en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14619/8413
dc.identifier.wosWOS:000391250900404en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2016 24th Signal Processing and Communication Application Conference (Siu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectStatistical Signal Processingen_US
dc.subjectWLAN Localizationen_US
dc.subjectIndoor Geolocationen_US
dc.subjectRSSen_US
dc.subjectFingerprint Matrixen_US
dc.subjectMemoryless Positioningen_US
dc.subjectTrackingen_US
dc.subjectNI Filteren_US
dc.subjectWiFien_US
dc.titleThe use of RSS and NI Filtering for the Wireless Indoor Localization and Tracking of Mobile Robots with Different Motion Modelsen_US
dc.typeConference Objecten_US

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