Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/106136
DC Field | Value | Language |
---|---|---|
dc.contributor | Interdisciplinary Division of Aeronautical and Aviation Engineering | en_US |
dc.creator | Wen, WS | en_US |
dc.creator | Bai, XW | en_US |
dc.creator | Hsu, LT | en_US |
dc.date.accessioned | 2024-05-03T00:45:24Z | - |
dc.date.available | 2024-05-03T00:45:24Z | - |
dc.identifier.issn | 0028-1522 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/106136 | - |
dc.language.iso | en | en_US |
dc.publisher | Wiley-Blackwell Publishing, Inc. | en_US |
dc.rights | © 2023 Institute of Navigation | en_US |
dc.rights | Licensed under CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/) | en_US |
dc.rights | The following publication Wen, W., Xiwei Bai, & Hsu, L.-T. (2023). 3D Vision Aided GNSS Real-Time Kinematic Positioning for Autonomous Systems in Urban Canyons. NAVIGATION: Journal of the Institute of Navigation, 70(3), navi.590 is available at https://dx.doi.org/10.33012/navi.590. | en_US |
dc.subject | 3D vision autonomous system | en_US |
dc.subject | GNSS-RTK | en_US |
dc.subject | NLOS | en_US |
dc.subject | Urban canyons | en_US |
dc.title | 3D vision aided GNSS real-time kinematic positioning for autonomous systems in urban canyons | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 70 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.doi | 10.33012/navi.590 | en_US |
dcterms.abstract | In this paper, a three-dimensional vision-aided method is proposed to improve global navigation satellite system (GNSS) real-time kinematic (RTK) position-ing. To mitigate the impact of reflected non-line-of-sight (NLOS) reception, a sky-pointing camera with a deep neural network was employed to exclude these measurements. However, NLOS exclusion results in distorted satellite geometry. To fill this gap, complementarity between the low-lying visual landmarks and the healthy but high-elevation satellite measurements was explored to improve the geometric constraints. Specifically, inertial measurement units, visual landmarks captured by a forward-looking camera, and healthy GNSS measurements were tightly integrated via sliding window optimization to estimate the GNSS-RTK float solution. The integer ambiguities and the fixed GNSS-RTK solution were then resolved. The effectiveness of the proposed method was verified using several challenging data sets collected in urban canyons in Hong Kong. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Navigation, Sept 2023, v. 70, no. 3, navi.590 | en_US |
dcterms.isPartOf | Navigation | en_US |
dcterms.issued | 2023-09 | - |
dc.identifier.isi | WOS:001046442800011 | - |
dc.identifier.eissn | 2161-4296 | en_US |
dc.identifier.artn | navi.590 | en_US |
dc.description.validate | 202405 bcrc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | University Grants Committee of Hong Kong | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
navi.590.full.pdf | 5.68 MB | Adobe PDF | View/Open |
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