Real-Time Precise Point Positioning Using Tomographic Wet Refractivity Fields

Abstract

Abstract:The tropospheric wet delay induced by water vapor is a major error source in precise point positioning (PPP), significantly influencing the convergence time to obtain high-accuracy positioning. Thus, high-quality water vapor information is necessary to support PPP processing. This study presents the use of tomographic wet refractivity (WR) fields in PPP to examine their impacts on the positioning performance. Tests are carried out based on 1-year of 2013 global navigation satellite system (GNSS) observations (30 s sampling rate) from three stations with different altitudes in the Hong Kong GNSS network. Coordinate errors with respect to reference values at a 0.1 m level of convergence is used for the north, east, and up components, whilst an error of 0.2 m is adopted for 3D position convergence. Experimental results demonstrate that, in both static and kinematic modes, the tomography-based PPP approach outperforms empirical tropospheric models in terms of positioning accuracy and convergence time. Compared with the results based on traditional, Saastamoinen, AN (Askne and Nordis), and VMF1 (Vienna Mapping Function 1) models, 23-48% improvements of positioning accuracy, and 5-30% reductions of convergence time are achieved with the application of tomographic WR fields. When using a tomography model, about 35% of the solutions converged within 20 min, whereas only 23%, 25%, 25%, and 30% solutions converged within 20 min for the traditional, Saastamoinen, AN, and VMF1 models, respectively. Our study demonstrates the benefit to real-time PPP processing brought by additional tomographic WR fields as they can significantly improve the PPP solution and reduce the convergence time for the up component.

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

“…The GNSS tomography technique, one of the most promising methods of GNSS meteorology, reconstructs the three-dimensional (3D) water vapor maps of the troposphere (Flores et al 2000;Champollion et al 2005). Relying on the remarkable reductions of cost, all-weather availability, widecoverage, and high spatiotemporal resolution, this technique has developed rapidly and has made some applications come true, e.g., assimilating and improving the Weather Research and Forecasting (WRF) system (Trzcina et al 2020), investigating the life cycle of super typhoon events (Zhu et al 2020), and correcting the tropospheric wet delay in precise point positioning (PPP) (Zumberge et al 1997;Yu et al 2018;Haji-Aghajany et al 2020a).…”

Reconstruction of Wet Refractivity Field Using an Improved Parameterized Tropospheric Tomographic Technique

“…After this successful trial, a number of significant studies have been performed in terms of the theoretical models and experimental analysis for GNSS-based tropospheric tomography [5,[16][17][18][19][20][21][22]. The vital significance of tomographic water vapor products for scientific research (e.g., heavy precipitation monitoring [23][24][25], precise point positioning (PPP) augmentation [26], and assimilation into NWP models [27]) has justified the various efforts in tomographic modeling.…”