Enhancing Smartphone Positioning with Galileo HAS Corrections and an Environmentally-Aware PPP/IMU Approach
Ding Yi, Caitlyn Hayden, and Sunil Bisnath, York University
Location: Grand Ballroom ABC
Date/Time: Thursday, May. 1, 2:35 p.m.
With the increasing demand for high-precision positioning in smartphone-based navigation applications, such as smart transportation, autonomous driving, and urban mobility, achieving real-time lane-level accuracy remains a significant challenge due to noisy Global Navigation Satellite System (GNSS) observations, frequent signal outages, and cycle slip false alarms. To address these issues, this study extends the iterative Precise Point Positioning (PPP) algorithm by integrating an environmentally-aware approach, which adaptively selects ambiguity candidates based on historical data and environments to mitigate errors in ambiguity estimation. Additionally, this study incorporates multi-constellation GNSS processing by integrating HAS corrections for GPS and Galileo (GE) constellations with broadcast ephemeris for GLONASS and BeiDou (RC) constellations, enhancing observation redundancy and positioning stability. To further improve GNSS outage mitigation, smartphone Inertial Measurement Unit (IMU) data are fused with GNSS observations to bridge signal interruptions. The proposed approach is validated through three real-world vehicle datasets. Results demonstrate that the environmentally-aware iterative PPP algorithm with multi-constellation (GREC) support reduces overall horizontal rms from 2.3 m to 1.4 m for dataset 1 and achieves sub-meter accuracy for dataset 2. By further integrating smartphone IMU data, maximum positioning errors in severe GNSS outages are reduced from 10.9 m to 2.9 m, with overall horizontal rms improving from 1.4 m to 1.3 m for dataset 3. These findings highlight the potential of real-time smartphone-based PPP in achieving sub-meter lane-level navigation, paving the way for next-generation smartphone-based positioning services.
Index Terms—Galileo HAS; GNSS; smartphone positioning; precise point positioning; iterative filter; environmentally-aware; PPP/IMU