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dc.contributor.author이상선-
dc.date.accessioned2018-05-02T09:00:03Z-
dc.date.available2018-05-02T09:00:03Z-
dc.date.issued2012-02-
dc.identifier.citationIPCSIT, 2012, 26en_US
dc.identifier.issn2010-460X-
dc.identifier.urihttps://www.semanticscholar.org/paper/Using-PDOP-to-Estimate-Kalman-Filter%E2%80%99s-Measurement-Kong-Xu/f8ea4a6b68af881f29ee77874108a77f79beb168?tab=abstract-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/71255-
dc.description.abstractGPS is widely used nowadays but with the absolute positioning technology which is used commonly, the positioning accuracy is not high enough. Many studies use Kalman filter to improve the accuracy of the GPS positioning. As we know, we have to determine the measurement noise covariance whenmodeling the Kalman filter, most of the studies do not pay attention on this and just consider it as a constant. In this paper, we propose a novel method to use the PDOP which can be obtained from the GPS data easily to estimate the measurement noise covariance of the Kalman filter.en_US
dc.description.sponsorshipThis work was supported by the Brain Korea 21 Project in 2011.en_US
dc.language.isoenen_US
dc.publisherIPCSITen_US
dc.subjectKalman filteren_US
dc.subjectGray Platelet Syndromeen_US
dc.subjectDilution of precisionen_US
dc.subjectGlobal Positioning Systemen_US
dc.subjectGNSS positioning calculationen_US
dc.subjectmodelingen_US
dc.titleusing PDOP to estimate Kalman filters measurement noise covariance for GPS Positioningen_US
dc.typeArticleen_US
dc.relation.page--
dc.contributor.googleauthorKong, Qingsheng-
dc.contributor.googleauthorXu, Shenglei-
dc.contributor.googleauthorLee, Sang-sun-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF ELECTRONIC ENGINEERING-
dc.identifier.pidssnlee-
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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