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Reduction of GPS Latency Using RTK GPS/GNSS Correction and Map Matching in a Car NavigationSystem

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dc.contributor.authorKim, Hyo Joong-
dc.contributor.authorLee, Won Hee-
dc.contributor.authorYu, Ki Yoon-
dc.date.accessioned2023-12-11T06:43:54Z-
dc.date.available2023-12-11T06:43:54Z-
dc.date.created2018-10-18-
dc.date.issued2016-06-
dc.identifier.citationjournal of Korean Society for Geospatial Information Science, Vol.24 No.2, pp.37-46-
dc.identifier.issn1598-2955-
dc.identifier.urihttps://hdl.handle.net/10371/198451-
dc.description.abstractThe difference between definition time of GPS (Global Positioning System) position data and actual display time of car positions on a map could reduce the accuracy of car positions displayed in PND (Portable Navigation Device)?type CNS (Car Navigation System). Due to the time difference, the position of the car displayed on the map is not its current position, so an improved method to fix these problems is required. It is expected that a method that uses predicted future positionsto compensate for the delay caused by processing and display of the received GPS signals could mitigate these problems. Therefore, in this study an analysis was conducted tocorrect late processing problems of map positions by mapmatching using a Kalman filter with only GPS position data anda RRF (Road Reduction Filter) technique in a light?weight CNS. The effects on routing services are examined by analyzing differences that are decomposed into along and across the road elements relative to the direction of advancing car. The results indicate that it is possible to improve the positional accuracy in the along?the?road direction of a light?weight CNS device that uses only GPS position data, by applying a Kalman filter and RRF.-
dc.language영어-
dc.publisher한국지형공간정보학회-
dc.titleReduction of GPS Latency Using RTK GPS/GNSS Correction and Map Matching in a Car NavigationSystem-
dc.typeArticle-
dc.identifier.doi10.7319/kogsis.2016.24.2.037-
dc.citation.journaltitlejournal of Korean Society for Geospatial Information Science-
dc.citation.endpage46-
dc.citation.number2-
dc.citation.startpage37-
dc.citation.volume24-
dc.identifier.kciidART002127332-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorYu, Ki Yoon-
dc.type.docTypeArticle-
dc.description.journalClass2-
dc.subject.keywordAuthorCar Navigation System (CNS)-
dc.subject.keywordAuthorKalman Filter-
dc.subject.keywordAuthorMap Matching-
dc.subject.keywordAuthorRoad Reduction Filter (RRF)-
dc.subject.keywordAuthorReal?Time Kinematic (RTK)-
dc.subject.keywordAuthorGlobal Positioning System (GPS)-
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