Abstract
The performance of precise point positioning (PPP) has been significantly improved thanks to the continuous improvements in satellite orbit, clock, and ambiguity resolution (AR) technologies, but the convergence speed remains a limiting factor in real-time PPP applications. To improve the PPP precision and convergence time, tropospheric delays from a regional network can be modeled to provide precise correction for users. We focus on the precise modeling of zenith wet delay (ZWD) over a wide area with large altitude variations for improving PPP-AR. By exploiting the water vapor exponential vertical decrease, we develop a modified optimal fitting coefficients (MOFC) model based on the traditional optimal fitting coefficients (OFC) model. The proposed MOFC model provides a precision better than 1.5 cm under sparse inter-station distances over the Europe region, with a significant improvement of 70% for high-altitude stations compared to the OFC model. The MOFC model with different densities of reference stations is further evaluated in GPS and Galileo kinematic PPP-AR solutions. Compared to the PPP-AR solutions without tropospheric delay augmentation, the positioning precision of those with 100-km inter-station spacing MOFC and OFC is improved by 25.7% and 17.8%, respectively, and the corresponding time to first fix (TTFF) is improved by 36.9% and 33.0% in the high-altitude areas. On the other hand, the OFC model only slightly improves the TTFF and positioning accuracy when using the 200 km inter-station spacing modeling and even degrades the positioning for high-altitude stations, whereas using the MOFC model, the PPP-AR solutions always improve. Moreover, the positioning precision improvement of MOFC compared with OFC is about 22.1%, 21.7%, and 25.7% for the Galileo-only, GPS-only, and GPS + Galileo PPP-AR solutions, respectively.
Highlights
Precise point positioning (PPP) (Malys and Jensen 1990; Zumberge et al 1997) is a commonly used technique for real-time Global Navigation Satellite Systems (GNSS) applications that employ precise orbits and clocks derived from the global network to achieve high-precision positioning (Fotopoulos and Cannon 2001)
In the experimental validations part, we briefly present the data processing strategy, and introduce the EUREF Permanent GNSS Network (EPN) and EPN densification network observations, which are used for both tropospheric delay modeling and PPP-ambiguity resolution (AR) validation
In the performance of tropospheric delay augmented PPP-AR part, we investigate the performance of both optimal fitting coefficients (OFC) and modified optimal fitting coefficients (MOFC) regional tropospheric augmentation in GPS and Galileo PPP-AR using about 200 stations
Summary
Precise point positioning (PPP) (Malys and Jensen 1990; Zumberge et al 1997) is a commonly used technique for real-time Global Navigation Satellite Systems (GNSS) applications that employ precise orbits and clocks derived from the global network to achieve high-precision positioning (Fotopoulos and Cannon 2001). One of the main errors limiting the PPP convergence time is the atmospheric delay error (Teunissen and Khodabandeh 2015). The satellite signals travel through the atmosphere and suffer considerable delays in the ionosphere and the troposphere. The ionospheric delay is usually mitigated by the ionosphere-free (IF) combination for dual-frequency users or estimated as an epoch-wise parameter for the uncombined solution (Zhao et al 2019). The zenith tropospheric delay (ZTD) is usually divided into zenith hydrostatic delay (ZHD) and zenith wet delay (ZWD) (Davis et al 1985). ZHD can be precisely modeled given the surface pressure, temperature,
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