GNSS Shadow Matching: Improving Urban Positioning Accuracy Using a 3D City Model with Optimized Visibility Scoring Scheme | Zendy

Wang Lei | Zendy; Groves Paul D. | Zendy; Ziebart Marek K. | Zendy

Open Access

GNSS Shadow Matching: Improving Urban Positioning Accuracy Using a 3D City Model with Optimized Visibility Scoring Scheme

Author(s) -

Wang Lei,

Groves Paul D.,

Ziebart Marek K.

Publication year - 2013

Publication title -

navigation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.847

H-Index - 46

eISSN - 2161-4296

pISSN - 0028-1522

DOI - 10.1002/navi.38

Subject(s) - gnss applications , visibility , shadow (psychology) , scheme (mathematics) , matching (statistics) , computer science , computer vision , artificial intelligence , geography , statistics , mathematics , telecommunications , global positioning system , meteorology , psychology , mathematical analysis , psychotherapist

Global navigation satellite system (GNSS) positioning is widely used in land vehicle and pedestrian navigation systems. Nevertheless, in urban canyons GNSS remains inaccurate due to building blockages and reflections, especially in the cross‐street direction. Shadow matching is a new technique, recently proposed for improving the cross‐street positioning accuracy using a 3D model of the nearby buildings. This paper presents a number of advances in the shadow‐matching algorithm. First, a positioning algorithm has been developed, interpolating between the top‐scoring candidate positions. Furthermore, a new scoring scheme has been developed that accounts for signal diffraction and reflection. Finally, the efficiency of the process used to generate the grid of building boundaries used for predicting satellite visibility has been improved. Real‐world GNSS data has been collected at 22 different locations in central London to provide the first comprehensive and statistical performance analysis of shadow matching. Copyright © 2013 Institute of Navigation.

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