Smartphones often rely on Global Navigation Satellite System (GNSS) for their navigation and location-based services. However, their positioning accuracy tends to decline significantly in dense urban settings. This degradation is primarily due to tall buildings blocking satellite signals, which leads to issues such as frequent cross-street errors and trajectory discrepancies.
Challenges of Urban Smartphone Positioning
The conventional methods used to mitigate these issues—like robust estimation and machine learning—often struggle under the complex geometries of city landscapes. High-precision GNSS signals, such as carrier phase measurements, are not fully utilized. This underutilization stems from frequent signal interruptions inherent in urban environments.
Innovative Positioning Framework
Researchers from the China University of Mining and Technology and Shandong Jianzhu University have proposed a novel smartphone positioning strategy. Published in the journal Satellite Navigation, their research introduces a tightly-coupled factor graph optimization framework designed to enhance urban navigation. This framework integrates 3D city maps with various GNSS observations, including pseudorange, Doppler, and time-differenced carrier phase measurements.
Key Features of the New Framework
- Integrates spatial constraints from urban maps with high-precision temporal information.
- Utilizes time-differenced carrier phase (TDCP) constraints to improve satellite visibility scoring.
- Applies a probabilistic map-matching strategy to identify the most likely road segments.
- Implements a RANSAC-based clustering method for refined candidate distributions.
Field Testing and Results
Field experiments conducted in densely populated urban areas demonstrated significant improvements. The new approach achieved horizontal positioning errors within 3 meters for 76.7% of the observed instances and within 5 meters for 93.1%. These results notably outperformed existing advanced GNSS multi-source fusion methods.
Benefits of the Advanced Method
This innovative framework not only enhances accuracy but also improves reliability and continuity—critical for effective navigation in urban environments. By leveraging often-overlooked high-precision GNSS data, this approach significantly narrows the gap between absolute positioning and short-term relative accuracy.
Future Directions for Urban Navigation
The research team emphasizes several potential avenues for advancing smartphone GNSS positioning in urban areas:
- Developing higher-resolution 3D urban models for better satellite visibility predictions.
- Creating reliable TDCP acquisition strategies to maintain robustness during signal interruptions.
- Integrating GNSS with inertial sensors, vision techniques, and other smartphone sensors to enhance continuity during outages.
These advancements could lead to more accurate and scalable smartphone-based positioning systems, with significant implications for urban navigation and smart city applications.
