Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80338
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dc.contributorInterdisciplinary Division of Aeronautical and Aviation Engineering-
dc.creatorZhang, G-
dc.creatorWen, W-
dc.creatorHsu, LT-
dc.date.accessioned2019-02-19T04:10:44Z-
dc.date.available2019-02-19T04:10:44Z-
dc.identifier.urihttp://hdl.handle.net/10397/80338-
dc.language.isoenen_US
dc.publisherION Institute of Navigationen_US
dc.rightsPosted with permission of the publisher.en_US
dc.rightsThe following publication Zhang, Guohao, Wen, Weisong, Hsu, Li-Ta, "Collaborative GNSS Positioning with the Aids of 3D City Models," Proceedings of the 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018), Miami, Florida, September 2018, pp. 143-149 is published by ION Institute of Navigation and is available at https://doi.org/10.33012/2018.15830en_US
dc.titleCollaborative GNSS positioning with the aids of 3D city modelsen_US
dc.typeConference Paperen_US
dc.identifier.spage143en_US
dc.identifier.epage149en_US
dc.identifier.doi10.33012/2018.15830en_US
dcterms.abstractGNSS collaborative positioning receives great attention because of the rapid development of vehicle-to-vehicle (V2V) communication. Its current bottleneck is in urban areas. During the calculation of double difference of GNSS measurements between two receivers to obtain their relative positions, the notorious multipath effects and NLOS reception in the pseudorange measurement cannot be eliminated. Even worse, these effects become more severe due to the multipath effects of two receivers are aggregated. Recently, the studies explored the use of 3D city models to aid GNSS positioning are increasing. It is widely believed the3D map aided (3DMA) GNSS is a solution to mitigate or even correct the multipath and NLOS effects. This paper therefore investigates the potential to aid GNSS collaborative positioning using 3D city models. The 3D models are used in two phases. The first phase is in single receiver level. The models is used to exclude NLOS measurements based on GNSS shadow matching (SDM) positioning result. The second phase is in multi-receiver level. The 3D building model is used together with broadcast ephemeris data to generate the predicted GNSS positioning error map. Based on the error map, each receiver will be labelled as, good, medium and bad, conditions. The receiver labelled as bad condition will be improved by the receiver labelled as good condition. Five low-cost GNSS receivers are used to conduct a static experiment. According to the result, the positioning accuracy of the receiver located at deep urban canyon will be improved from 26.6 to 17.9 meters, where its SDM result is 19.3 meters.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings of the 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018), September 24 - 28, 2018, Hyatt Regency Miami, Miami, Florida, p. 143-149-
dcterms.issued2018-
dc.relation.ispartofbookProceedings of the 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018), September 24 - 28, 2018, Hyatt Regency Miami, Miami, Floridaen_US
dc.relation.conferenceInternational Technical Meeting of The Satellite Division of the Institute of Navigation [ION GNSS+]en_US
dc.description.validate201902 bcrcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera0272-n07en_US
dc.description.pubStatusPublisheden_US
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