Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81173
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorInterdisciplinary Division of Aeronautical and Aviation Engineeringen_US
dc.creatorZhang, Gen_US
dc.creatorWen, Wen_US
dc.creatorHsu, LTen_US
dc.date.accessioned2019-08-16T08:32:36Z-
dc.date.available2019-08-16T08:32:36Z-
dc.identifier.issn1080-5370en_US
dc.identifier.urihttp://hdl.handle.net/10397/81173-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© Springer-Verlag GmbH Germany, part of Springer Nature 2019en_US
dc.rightsThis is a post-peer-review, pre-copyedit version of an article published in GPS Solutions. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10291-019-0872-9en_US
dc.subjectCollaborative positioningen_US
dc.subject3D building modelsen_US
dc.subjectUrban canyonen_US
dc.subjectConsistency checken_US
dc.subjectNLOSen_US
dc.titleRectification of GNSS‑based collaborative positioning using 3D building models in urban areasen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage12en_US
dc.identifier.volume23en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1007/s10291-019-0872-9en_US
dcterms.abstractGNSS collaborative positioning receives great attention because of the rapid development of vehicle-to-vehicle communication. Its current bottleneck is in urban areas. During the relative positioning using GNSS double-difference pseudorange measurements, the multipath effects and non-line-of-sight (NLOS) reception cannot be eliminated, or even worse, both might be aggregated. It has been widely demonstrated that 3D map aided GNSS can mitigate or even correct the multipath and NLOS effects. We, therefore, investigate the potential of aiding GNSS collaborative positioning using 3D city models. These models are used in two phases. First, the building models are used to exclude NLOS measurements at a single receiver using GNSS shadow matching positioning. Second, the models are used together with broadcast ephemeris data to generate a predicted GNSS positioning error map. Based on this error map, each receiver will be identified as experiencing healthy or degraded conditions. The receiver experiencing degraded condition will be improved by the receiver experiencing the healthy condition, hence the aspect of collaborative positioning. Five low-cost GNSS receivers are used to conduct experiments. According to the result, the positioning accuracy of the receiver in a deep urban area improves from 46.2 to 14.4 m.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationGPS solutions, July 2019, v. 23, no. 3, 83, p. 1-12en_US
dcterms.isPartOfGPS solutionsen_US
dcterms.issued2019-07-
dc.identifier.eissn1521-1886en_US
dc.identifier.artn83en_US
dc.description.validate201908 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0353-n04en_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Zhang_Rectification_GNSS_3D.pdfPre-Published version5.13 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

127
Last Week
1
Last month
Citations as of Mar 24, 2024

Downloads

304
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

18
Citations as of Mar 22, 2024

WEB OF SCIENCETM
Citations

15
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.