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http://hdl.handle.net/10397/106136
Title: | 3D vision aided GNSS real-time kinematic positioning for autonomous systems in urban canyons | Authors: | Wen, WS Bai, XW Hsu, LT |
Issue Date: | Sep-2023 | Source: | Navigation, Sept 2023, v. 70, no. 3, navi.590 | 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. | Keywords: | 3D vision autonomous system GNSS-RTK NLOS Urban canyons |
Publisher: | Wiley-Blackwell Publishing, Inc. | Journal: | Navigation | ISSN: | 0028-1522 | EISSN: | 2161-4296 | DOI: | 10.33012/navi.590 | Rights: | © 2023 Institute of Navigation Licensed under CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/) 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. |
Appears in Collections: | Journal/Magazine Article |
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