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dc.contributor.author김선우-
dc.date.accessioned2016-08-30T02:24:14Z-
dc.date.available2016-08-30T02:24:14Z-
dc.date.issued2015-03-
dc.identifier.citationINTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, Page. 1-11en_US
dc.identifier.issn1550-1329-
dc.identifier.issn1550-1477-
dc.identifier.urihttp://dsn.sagepub.com/content/11/8/674635.full-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/22847-
dc.description.abstractThis paper investigates the indoor position tracking problem under the variation of received signal strength (RSS) characteristic from the changes of device statuses and environmental factors. A novel indoor position tracking algorithmis introduced to provide reliable position estimates by integrating motion sensor-based positioning (i.e., dead-reckoning) and RSS-based fingerprinting positioning with Kalman filter. In the presence of the RSS variation, RSS-based fingerprinting positioning provides unreliable results due to different characteristics of RSS measurements in the offline and online phases, and the tracking performance is degraded. To mitigate the effect of the RSS variation, a recursive least square estimation-based self-calibration algorithm is proposed that estimates the RSS variation parameters and provides the mapping between the offline and online RSS measurements. By combining the Kalman filter-based tracking algorithm with the self-calibration, the proposed algorithm can achieve higher tracking accuracy even in severe RSS variation conditions. Through extensive computer simulations, we have shown that the proposed algorithm outperforms other position tracking algorithms without self-calibration.en_US
dc.language.isoenen_US
dc.publisherHINDAWI PUBLISHING CORPORATIONen_US
dc.subjectVARIANCE PROBLEMen_US
dc.subjectWI-FIen_US
dc.subjectSYSTEMSen_US
dc.subjectNAVIGATIONen_US
dc.subjectNETWORKSen_US
dc.titleKalman Filter-Based Indoor Position Tracking with Self-Calibration for RSS Variation Mitigationen_US
dc.typeArticleen_US
dc.identifier.doi10.1155/2015/674635-
dc.relation.page1-11-
dc.relation.journalINTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS-
dc.contributor.googleauthorLee, Sangwoo-
dc.contributor.googleauthorCho, Bongkwan-
dc.contributor.googleauthorKoo, Bonhyun-
dc.contributor.googleauthorRyu, Sanghwan-
dc.contributor.googleauthorChoi, Jaehoon-
dc.contributor.googleauthorKim, Sunwoo-
dc.relation.code2015008330-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF ELECTRONIC ENGINEERING-
dc.identifier.pidremero-
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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