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About Non-Line-Of-Sight satellite detection and exclusion in a 3D map-aided localization algorithm
Sébastien Peyraud1, David Bétaille, Stéphane Renault
1XLIM, UMR CNRS 7252, Limoges University, 87060 Limoges, France. peyraud@ensil.unilim.fr
Sensors (Basel, Switzerland)
|January 25, 2013
Summary
This study enhances Global Positioning System (GPS) accuracy in urban areas by using 3D city models to predict satellite visibility and filter faulty signals. This method improves GPS localization reliability in challenging city environments.
Area of Science:
- Geomatics Engineering
- Satellite Navigation Systems
- Urban Planning
Background:
- Global Positioning System (GPS) signals suffer from multipath interference and poor satellite geometry in urban canyons, degrading positioning accuracy.
- Urban environments present significant challenges for reliable GPS localization due to signal obstruction and reflections.
Purpose of the Study:
- To improve GPS positioning reliability in urban environments by integrating 3D urban models.
- To develop a method for forecasting satellite visibility and eliminating faulty GPS measurements in cities.
Main Methods:
- Utilizing a 3D urban model to predict satellite visibility.
- Employing virtual image processing to detect and remove erroneous measurements.
- Generating a virtual image based on a priori navigation estimates under road constraints.
- Updating the position using measurements from line-of-sight satellites exclusively.
Main Results:
- The closed-loop, real-time processing demonstrated promising initial results in full-scale tests.
- The method effectively filters faulty measurements by considering satellite visibility and road constraints.
Conclusions:
- Integrating 3D urban models and virtual image processing enhances GPS localization accuracy in challenging city settings.
- The proposed method offers a robust solution for reliable real-time GPS positioning in urban navigation.
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