Sidewalk matching: a smartphone-based GNSS positioning technique for pedestrians in urban canyons
Duojie Weng, Wu Chen, Mengyu Ding, Simin Liu, Jingxian Wang
Abstract
Abstract In urban canyons, most of Global Navigation Satellite System (GNSS) signals are blocked or reflected by high-rising buildings. The lack of redundant fault-free measurements poses a great challenge for detecting and isolating faulty measurements, degrading the GNSS positioning accuracy, particularly in the cross-street direction. The current GNSS positioning accuracy in urban canyons is not sufficient for identifying the sides of a street, which is highly demanded by numerous pedestrian applications. To address this issue, this study proposes a sidewalk matching technique to improve the redundancy of fault-free measurements and achieve positioning accuracy at sidewalk level in urban canyons. The technique relies on a simple pedestrian map and smartphone sensors, without Three-Dimensional (3D) building models. A new algorithm is proposed to identify the sides of the street, and a searching algorithm is developed to find GNSS position under constraints of the sidewalk. Extensive evaluation of the proposed technique based on a real-time platform demonstrated that the accuracy of GNSS positioning was less than 5 m, enabling seamless determination of the street sides in urban canyons. The new sidewalk matching technique can be used in various real-life applications, including pedestrian collision avoidance systems, online ride-hailing service, and jaywalking monitoring.