Accuracy improvement of RSSI-based distance localization using unscented kalman filter (UKF) algorithm for wi-fi tracking application

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dc.contributor.authorFuada, S.ko
dc.contributor.authorAdiono, T.ko
dc.contributor.authorPrasetiyoko
dc.date.accessioned2021-03-08T06:30:07Z-
dc.date.available2021-03-08T06:30:07Z-
dc.date.created2021-03-08-
dc.date.issued2020-
dc.identifier.citationInternational Journal of Interactive Mobile Technologies, v.14, no.16, pp.225 - 233-
dc.identifier.issn1865-7923-
dc.identifier.urihttp://hdl.handle.net/10203/281357-
dc.description.abstractIn this report, we perform the digital filter computation using Matlab for Wi-Fi tracking application. This work motivates to improve the accuracy of filter algorithm in the RSSI-based distance localization system. There are several aspects that we can improve, e.g., in the Filter part and Path-loss model. But, in this work, we focus on filter part; Unscented Kalman Filter (UKF) is implemented to replace linear Kalman Filter (KF), which is used in previous work. Based on the performance comparison, UKF has 90% hit ratio while linear KF has only 81.15 % hit ratio. We found that UKF can handle the noise in RSSI. Further work, the UKF algorithm is then embedded on the server system.-
dc.languageEnglish-
dc.publisherInternational Association of Online Engineering-
dc.titleAccuracy improvement of RSSI-based distance localization using unscented kalman filter (UKF) algorithm for wi-fi tracking application-
dc.typeArticle-
dc.identifier.scopusid2-s2.0-85092468554-
dc.type.rimsART-
dc.citation.volume14-
dc.citation.issue16-
dc.citation.beginningpage225-
dc.citation.endingpage233-
dc.citation.publicationnameInternational Journal of Interactive Mobile Technologies-
dc.identifier.doi10.3991/ijim.v14i16.14077-
dc.contributor.nonIdAuthorFuada, S.-
dc.contributor.nonIdAuthorAdiono, T.-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
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