Multi-frequency and multi-GNSS PPP based on BDS PPP-B2b and Galileo high accuracy service

Abstract

With the recent deployment of real-time Precise Point Positioning (PPP) services such as PPP-B2b from BeiDou and HAS from Galileo, users now have multiple options for satellite-based PPP augmentation. However, these services operate independently and differ in supported constellations, limiting the full exploitation of multi-GNSS potential. This study proposes an integrated processing strategy for orbit and clock combination of HAS and PPP-B2b to improve multi-GNSS positioning performance. Specifically, Helmert coordinate transformation method is employed for orbit combination to reconcile coordinate frame discrepancies between different satellite-based services, while a constrained least-squares estimation is used for clock combination to resolve the time datum differences between different satellite-based services. In addition to the usage of multi-GNSS, a multi-frequency uncombined PPP model is further developed to leverage multi-frequency observations. To validate the proposed algorithm, HAS and PPP-B2b products from DOY 309–315, 2023, were collected at a Zhengzhou, China. After the evaluation of the availability, orbit, and clock quality of both services, static and kinematic PPP tests are conducted to validated the integrated product. Using data from 20 GNSS stations across China and adjacent regions, results demonstrated that individual HAS and PPP-B2b solutions achieved average horizontal/vertical accuracies of (3.99, 3.33 cm) and (3.06, 2.37 cm), respectively. The integrated strategy significantly improved performance, reaching 2.57 cm (horizontal) and 2.17 cm (vertical), corresponding to 8–35% enhancement over standalone products. Additionally, it exhibits significantly faster convergence in all directions (E, N, U, and 3D). In a kinematic vehicle test under typical urban conditions, GNSS data was processed using the standard dual-frequency ionosphere-free (IF) combination and the multi-frequency uncombined (UC) approach. The integrated product with IF processing achieved accuracies of 0.52 m (horizontal) and 1.06 m (vertical), improved by 81.5% and 84.5% over HAS, and by 56.3% and 60.7% over PPP-B2b. Compared to the IF solution, the UC-based solution further improved positioning accuracy by 12.1–26.5% in the horizontal direction and 23.4–36.6% in the vertical direction. These results demonstrate that the integrated strategy substantially improves PPP performance over any single product. Moreover, the UC solution more effectively utilizes multi-frequency and multi-system observations from the integrated product, particularly in challenging urban environments. The proposed method significantly enhances their applicability for global high-precision positioning.