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dc.contributor.authorShin, Beom ju-
dc.contributor.authorJung Ho Lee-
dc.contributor.author유창수-
dc.contributor.author경한결-
dc.contributor.author이택진-
dc.date.accessioned2024-01-12T03:01:37Z-
dc.date.available2024-01-12T03:01:37Z-
dc.date.created2022-08-01-
dc.date.issued2022-07-
dc.identifier.issn0018-9456-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/76670-
dc.description.abstractStable estimation of a user's position in a wide range of indoor spaces is difficult. In an indoor localization field, a fingerprint method that compares the received signal strength (RSS) vector with the previously collected signal strength vector in a radio map is mostly applied. However, this method is dependent on the infrastructure around it and does not always provide stable performance owing to the severity of RSS noise in an indoor environment, which limits the application of this system. In this article, we propose an indoor positioning system using an accumulated RSS for mobile users. A user spatial RSS pattern is generated using the estimated user trajectory and the accumulated RSS. The user's trajectory is estimated using pedestrian dead reckoning (PDR) technology. In particular, we proposed a novel concept, namely, a heading flag, to estimate a user's relative heading change in a certain period. The user's spatial RSS pattern can be generated using this flag even when the user performs various motions while walking. We developed our own Bluetooth low energy (BLE) beacons and installed few beacons on a testbed for real-time positioning. To demonstrate the performance of the proposed system, we conducted a real field test in an office building. An average position estimation result of less than 2 m was obtained using the proposed system. It is expected that a commercial level location-based service (LBS) will be possible using the proposed system.-
dc.languageEnglish-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.titleReceived Signal Strength-Based Robust Positioning System in Corridor Environment-
dc.typeArticle-
dc.identifier.doi10.1109/TIM.2022.3190522-
dc.description.journalClass1-
dc.identifier.bibliographicCitationIEEE Transactions on Instrumentation and Measurement, v.71-
dc.citation.titleIEEE Transactions on Instrumentation and Measurement-
dc.citation.volume71-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000846867100001-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.type.docTypeArticle-
dc.subject.keywordPlusINDOOR-
dc.subject.keywordPlusWIFI-
dc.subject.keywordPlusLOCALIZATION-
dc.subject.keywordPlusFINGERPRINT-
dc.subject.keywordPlusSCHEME-
dc.subject.keywordAuthorFingerprint recognition-
dc.subject.keywordAuthorTrajectory-
dc.subject.keywordAuthorEstimation-
dc.subject.keywordAuthorWireless fidelity-
dc.subject.keywordAuthorReceivers-
dc.subject.keywordAuthorNoise measurement-
dc.subject.keywordAuthorsmartphone-
dc.subject.keywordAuthorGlobal navigation satellite system-
dc.subject.keywordAuthorBluetooth low energy (BLE)-
dc.subject.keywordAuthorfingerprint-
dc.subject.keywordAuthorindoor positioning-
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KIST Article > 2022
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