Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/92762
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dc.contributorDepartment of Aeronautical and Aviation Engineeringen_US
dc.creatorNg, HFen_US
dc.creatorZhang, Gen_US
dc.creatorHsu, LTen_US
dc.date.accessioned2022-05-16T09:07:36Z-
dc.date.available2022-05-16T09:07:36Z-
dc.identifier.issn0373-4633en_US
dc.identifier.urihttp://hdl.handle.net/10397/92762-
dc.language.isoenen_US
dc.publisherCambridge University Pressen_US
dc.rightsThis article has been published in a revised form in the Journal of Navigation https://doi.org/10.1017/S037346332000003X. This version is free to view and download for private research and study only. Not for re-distribution or re-use. © The Royal Institute of Navigation 2020.en_US
dc.rightsWhen citing an Accepted Manuscript or an earlier version of an article, the Cambridge University Press requests that readers also cite the Version of Record with a DOI link. The article is subsequently published in revised form in the Journal of Navigation https://dx.doi.org/10.1017/S037346332000003X.en_US
dc.subject3D building modelen_US
dc.subject3DMA GNSSen_US
dc.subjectNLOSen_US
dc.subjectUrban canyonen_US
dc.titleA computation effective range-based 3D mapping aided GNSS with NLOS correction methoden_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1202en_US
dc.identifier.epage1222en_US
dc.identifier.volume73en_US
dc.identifier.issue6en_US
dc.identifier.doi10.1017/S037346332000003Xen_US
dcterms.abstractGlobal navigation satellite system (GNSS) positioning in dense urban areas remains a challenge due to the signal reflection by buildings, namely multipath and non-line-of-sight (NLOS) reception. These effects degrade the performance of low-cost GNSS receivers such as in those smartphones. An effective three-dimensional (3D) mapping aided GNSS positioning method is proposed to correct the NLOS error. Instead of applying ray-tracing simulation, the signal reflection points are detected based on a skyplot with the surrounding building boundaries. The measurements of the direct and reflected signals can thus be simulated and further used to determine the user's position based on the measurement likelihood between real measurements. Verified with real experiments, the proposed algorithm is able to reduce the computational load greatly while maintaining a positioning accuracy within 10 metres of error in dense urban environments, compared with the conventional method of ray-tracing based NLOS corrected positioning.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of navigation, Nov. 2020, v. 73, no. 6, p. 1202-1222en_US
dcterms.isPartOfJournal of navigationen_US
dcterms.issued2020-11-
dc.identifier.scopus2-s2.0-85081972277-
dc.identifier.eissn1469-7785en_US
dc.description.validate202205 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberAAE-0067-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS42722465-
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