Publication:
An improved indoor location technique using Kalman Filter

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dc.citedby4
dc.contributor.authorFariz N.en_US
dc.contributor.authorJamil N.en_US
dc.contributor.authorDin M.M.en_US
dc.contributor.authorRusli M.E.en_US
dc.contributor.authorSharudin Z.en_US
dc.contributor.authorMohamed M.A.en_US
dc.contributor.authorid57201613639en_US
dc.contributor.authorid36682671900en_US
dc.contributor.authorid55348871200en_US
dc.contributor.authorid16246214600en_US
dc.contributor.authorid57201617898en_US
dc.contributor.authorid57194596063en_US
dc.date.accessioned2023-05-29T06:56:59Z
dc.date.available2023-05-29T06:56:59Z
dc.date.issued2018
dc.description.abstractIndoor positioning technique is used to trace location of entities within a nonspace environment riding from the incapability of GPS to do so. Most of indoor localization techniques proposed by researchers aimed at discovering an optimized solution for indoor location tracking with high precision and accuracy. This paper proposes an improved indoor location technique by implementing Trilateration and Kalman Filter technique that can manipulate noise signal deduced from raw Received Signal Strength Indicator (RSSI). Upon implementing the technique, observation and comparison are made to measure the effectiveness and reliability of the enhanced Kalman Filter in tracking indoor positioning. Our analysis and finding shows that the enhanced indoor positioning technique improves the accuracy significantly. � 2018 Authors.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.14419/ijet.v7i2.14.11141
dc.identifier.epage4
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85045415508
dc.identifier.spage1
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85045415508&doi=10.14419%2fijet.v7i2.14.11141&partnerID=40&md5=8d2f7ebd419fcd8c58b49923814b1207
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24208
dc.identifier.volume7
dc.publisherScience Publishing Corporation Incen_US
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Technology(UAE)
dc.titleAn improved indoor location technique using Kalman Filteren_US
dc.typeArticleen_US
dspace.entity.typePublication
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