Abstract: | Network-based real-time kinematic GNSS precise point positioning (PPP-RTK) is able to achieve instantaneous centimeter-level precision with the augmentation of precise atmospheric products, which is treasured in emerging applications such as autonomous driving. However, in a typical urban environment, satellite signals can easily be blocked, and thus GNSS observations across all signal frequencies (e.g., GPS L1, L2 and L5; Galileo E1, E5a/b and E6) can hardly be kept intact or complete. This difficulty would disable the conventional PPP-RTK techniques, which prescribe or require specific signal combinations. For instance, a loss of the GPS L2 signal will negate GPS L1/L2 based PPP-RTK; but an instant switch to alternative L1 or L1/L5 signal based PPPRTK is not straightforward since the satellite phase bias products enabling undifferenced ambiguity resolution are normally tied to the L1/L2 signal combinations. In this study aiming at urban environments, we developed a concept of all-frequency PPP-RTK where undifferenced GPS/Galileo/BDS ambiguity resolution can be achieved over any signal combination using observable-specific signal biases (OSBs). Specifically, all-frequency PPP-RTK is not tied to any prescribed signals, but accessible to all available pseudorange and carrier-phase signals surviving in GNSS adverse environments. To validate all-frequency PPP-RTK, we first computed GPS/Galileo/BDS OSBs for all available frequencies of signals using a global reference network. In a vehicle-borne experiment carried out in Wuhan City, all-frequency PPP-RTK could achieve an ambiguity fixing rate of 43%, 51% and 81% for GPS, Galileo and BDS-3 signals, respectively, while only 38%, 22% and 54% in conventional PPP-RTK; correspondingly, the percentage of the epochs with a horizontal positioning error of less than 0.1 m was increased by 5-30% from conventional to all-frequency PPP-RTK. We, therefore, demonstrate that all-frequency PPP-RTK outperforms conventional PPP-RTK in terms of high-precision positioning availability, which will benefit self-driving vehicles in urban canyons. |
Published in: |
Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023) September 11 - 15, 2023 Hyatt Regency Denver Denver, Colorado |
Pages: | 2682 - 2697 |
Cite this article: | Wang, Feng, Zhang, Kunlun, "All-Frequency GNSS PPP-RTK Using Observable-Specific Signal Biases for Urban Environments," Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 2682-2697. https://doi.org/10.33012/2023.19277 |
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