Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas
1
UTBM IRTES-SET, Rue Ernest Thierry Mieg, 90010 Belfort CEDEX, France
2
IFSTTAR-COSYS-LEOST, 20 rue Élysée Reclus, BP 70317 59666 Villeneuve d’Ascq CEDEX, France
*
Author to whom correspondence should be addressed.
Academic Editor: Felipe Jimenez
Sensors 2017, 17(1), 119; https://doi.org/10.3390/s17010119
Received: 30 October 2016
/
Revised: 27 December 2016
/
Accepted: 4 January 2017
/
Published: 17 January 2017
(This article belongs to the Special Issue Sensors for Autonomous Road Vehicles)
A precise GNSS (Global Navigation Satellite System) localization is vital for autonomous road vehicles, especially in cluttered or urban environments where satellites are occluded, preventing accurate positioning. We propose to fuse GPS (Global Positioning System) data with fisheye stereovision to face this problem independently to additional data, possibly outdated, unavailable, and needing correlation with reality. Our stereoscope is sky-facing with 360° × 180° fisheye cameras to observe surrounding obstacles. We propose a 3D modelling and plane extraction through following steps: stereoscope self-calibration for decalibration robustness, stereo matching considering neighbours epipolar curves to compute 3D, and robust plane fitting based on generated cartography and Hough transform. We use these 3D data with GPS raw data to estimate NLOS (Non Line Of Sight) reflected signals pseudorange delay. We exploit extracted planes to build a visibility mask for NLOS detection. A simplified 3D canyon model allows to compute reflections pseudorange delays. In the end, GPS positioning is computed considering corrected pseudoranges. With experimentations on real fixed scenes, we show generated 3D models reaching metric accuracy and improvement of horizontal GPS positioning accuracy by more than 50%. The proposed procedure is effective, and the proposed NLOS detection outperforms CN0-based methods (Carrier-to-receiver Noise density).
View Full-Text
Keywords:
vehicle positioning; GPS; fisheye stereovision; 3D point cloud
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Moreau, J.; Ambellouis, S.; Ruichek, Y. Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas. Sensors 2017, 17, 119. https://doi.org/10.3390/s17010119
AMA Style
Moreau J, Ambellouis S, Ruichek Y. Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas. Sensors. 2017; 17(1):119. https://doi.org/10.3390/s17010119
Chicago/Turabian StyleMoreau, Julien, Sébastien Ambellouis, and Yassine Ruichek. 2017. "Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas" Sensors 17, no. 1: 119. https://doi.org/10.3390/s17010119
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
