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Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas

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 f...

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Detalles Bibliográficos
Autores principales: Moreau, Julien, Ambellouis, Sébastien, Ruichek, Yassine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298692/
https://www.ncbi.nlm.nih.gov/pubmed/28106746
http://dx.doi.org/10.3390/s17010119
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author Moreau, Julien
Ambellouis, Sébastien
Ruichek, Yassine
author_facet Moreau, Julien
Ambellouis, Sébastien
Ruichek, Yassine
author_sort Moreau, Julien
collection PubMed
description 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Positioning System) data with fisheye stereovision to face this problem independently to additional data, possibly outdated, unavailable, and needing correlation with reality.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).
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spelling pubmed-52986922017-02-10 Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas Moreau, Julien Ambellouis, Sébastien Ruichek, Yassine Sensors (Basel) Article 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). MDPI 2017-01-17 /pmc/articles/PMC5298692/ /pubmed/28106746 http://dx.doi.org/10.3390/s17010119 Text en © 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Moreau, Julien
Ambellouis, Sébastien
Ruichek, Yassine
Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas
title Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas
title_full Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas
title_fullStr Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas
title_full_unstemmed Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas
title_short Fisheye-Based Method for GPS Localization Improvement in Unknown Semi-Obstructed Areas
title_sort fisheye-based method for gps localization improvement in unknown semi-obstructed areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298692/
https://www.ncbi.nlm.nih.gov/pubmed/28106746
http://dx.doi.org/10.3390/s17010119
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