A High Precision and Robustness Positioning Algorithm Based on IMU-Aided RTK/DGNSS-PD Integration Framework for Urban Vehicle Position Monitoring

Yiqian Li, Yuting Yang, Di He, Wenxian Yu

Abstract:	In urban areas, vehicles serve as the main mode of transportation, and smartphones are essential for travel, integrating location measurement sensors like global navigation satellite system and inertial measurement unit (GNSS/IMU). Smartphone-based monitoring of vehicle positions has gained research interest. However, existing urban vehicle localization algorithms struggle with issues like inaccuracy, high algorithm complexity, and discontinuous results. These challenges arise mainly due to low reception rates and incorrect fixes of carrier phase, pseudorange multipath effects, and complex signal error modeling. Therefore, this study proposes a novel IMU-aided RTK/DGNSS-Parking Detection (IGP) algorithm framework to enhance the accuracy, stability, and robustness of urban vehicle localization on smartphone platforms. Firstly, the system employs adaptive real-time kinematic and differential global navigation satellite system (RTK/DGNSS) integrated positioning. Secondly, to avoid fatal errors, a two-step filtering process based on vehicular dynamics eliminates speed and position anomalies. This aids in controlling drift in low-quality IMUs, enabling successful modeling and position computation during position outliers. Additionally, the method incorporates position constraints based on frequent, prolonged stopping behavior in urban vehicles. The proposed algorithm undergoes experimental evaluation using data from Google. Taking the second dataset as an example, comparisons with baseline methods, RTKLib open-source software, and factor graph optimization reveal that our approach achieves significant error reduction in complex urban environments. Specifically, the average positioning error is reduced by 3.6, 1.2, and 3.2 meters, while the maximum error is dramatically decreased by 7434, 41, and 14 meters, respectively. These improvements demonstrate that the system substantially enhances both precision and reliability for urban vehicular navigation.
Published in:	Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025) September 8 - 12, 2025 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	1068 - 1082
Cite this article:	Li, Yiqian, Yang, Yuting, He, Di, Yu, Wenxian, "A High Precision and Robustness Positioning Algorithm Based on IMU-Aided RTK/DGNSS-PD Integration Framework for Urban Vehicle Position Monitoring," Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 1068-1082. https://doi.org/10.33012/2025.20272
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