PT  - JOURNAL ARTICLE
AU  - Wen, Weisong
AU  - Bai,, Xiwei
AU  - Hsu, Li-Ta
TI  - 3D Vision Aided GNSS Real-Time Kinematic Positioning for Autonomous Systems in Urban Canyons
AID  - 10.33012/navi.590
DP  - 2023 Sep 21
TA  - NAVIGATION: Journal of the Institute of Navigation
PG  - navi.590
VI  - 70
IP  - 3
4099  - https://navi.ion.org/content/70/3/navi.590.short
4100  - https://navi.ion.org/content/70/3/navi.590.full
SO  - NAVIGATION2023 Sep 21; 70
AB  - In this paper, a three-dimensional vision-aided method is proposed to improve global navigation satellite system (GNSS) real-time kinematic (RTK) positioning. 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.