A team of researchers from Shenzhen University, The Hong Kong Polytechnic University, and Wuhan University have developed a new GNSS positioning technique to overcome the challenges of urban canyons. The researchers are tackling the phenomenon in modern cities of tall buildings blocking satellite signals, leading to inaccuracies in pedestrian navigation. The new method, known as “sidewalk matching,” uses smartphone sensors and a simple pedestrian map to improve positioning accuracy to within 5 metres.

This approach can support applications requiring precise identification of street sides, such as pedestrian collision avoidance, ride-hailing services, and jaywalk monitoring.

The new method, “sidewalk matching,” uses smartphone sensors combined with pedestrian maps to provide accurate positioning in challenging urban canyons.

The algorithm works by identifying which half of the sky has more Line-of-Sight (LOS) signals, enabling it to determine the correct side of the street. By analysing the Carrier-to-Noise Ratio (C/N0) and satellite azimuth angles, the system can filter out faulty measurements using a sliding window method, ensuring that only reliable data is used.

A feature is the incorporation of Pedestrian Dead Reckoning (PDR), which uses smartphone accelerometers and gyroscopes to validate GNSS positions, especially at intersections where traditional methods may struggle. Extensive tests conducted in Hong Kong demonstrated that the technique provides positioning accuracy of less than 5 meters—far superior to traditional GNSS systems, which can have errors exceeding 18 meters in urban canyons.

“This sidewalk matching technique represents a significant leap forward in urban pedestrian navigation,” said Dr. Duojie Weng, the lead researcher. “By combining smartphone sensors with pedestrian network data, we’ve created a practical solution that doesn’t require costly 3D models or large training datasets. This makes it an accessible, cost-effective solution for a wide range of real-world applications, from pedestrian safety to ride-hailing services.”

The sidewalk matching technique promises to improve pedestrian collision avoidance systems by providing real-time, precise positioning even in densely built urban areas. Ride-hailing services can employ this technology to enhance pick-up and drop-off accuracy, while jaywalking monitoring systems can more reliably determine which side of the street a pedestrian is on.

Additionally, the method could be used by visually impaired individuals, providing greater independence and safety in urban environments. According to the researchers, the innovation could become a standard feature in future navigation systems, revolutionising how pedestrians navigate cities.