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.
Highlights
The increasingly popular precise point positioning (PPP) technique has been demonstrated to be a potent tool in many Global Navigation Satellite System (GNSS) applications, such as meteorology, precise orbiting, earthquake detection, and precise timing [1,2,3,4]
The tropospheric delay consists of two parts: a hydrostatic component induced by the neutral hydrostatic atmosphere and a wet component caused by the atmospheric water vapor
We extend the application of tomographic wet refractivity (WR) fields to constrain tropospheric estimates in real-time PPP processing
Summary
The increasingly popular precise point positioning (PPP) technique has been demonstrated to be a potent tool in many Global Navigation Satellite System (GNSS) applications, such as meteorology, precise orbiting, earthquake detection, and precise timing [1,2,3,4]. Yao et al investigated the use of ZTDs derived from a GNSS-based global troposphere model as virtual observations to isolate and fix the tropospheric delay in PPP processing [13]. They showed that the proposed algorithm can bring about a 15% improvement in PPP convergence time. Wilgan et al investigated the impact of using tropospheric delays derived from a high-resolution NWP Weather Research and Forecasting (WRF) model in Poland [9] They demonstrated significant improvements of station coordinates and convergence time by using this strategy in comparison to the PPP approaches where the tropospheric corrections were provided by UNB3m and Forecast Gridded Vienna Mapping Function 1—VMF1-FC.
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