Abstract

The key to performing successful multi-GNSS (Global Navigation Satellite System) precise point positioning is calibrating ISB (inter-system bias) in different systems. We can use the method of modeling to eliminate the ISB error. However, the ISB series are commonly discontinuous, as they contain jumps and outliers caused by day boundaries, gaps, or outliers in the precise clock products, which will break the ability of modeling. Thus, before modeling the ISB, we must remove outliers and repair jumps to improve the ISB continuity and achieve a continuous and smooth ISB series. Preprocessing on precise clock products is focused on in this study for the detection of ISB jumps and their repair. From the results, a positive correlation is revealed within the residuals of satellite clock offset and ISB differences between adjacent days. This finding implies ISB continuity can be improved through the preprocessing of precise clock products. It is also found that the exact reason for the occurrence of ISB jumps is the presence of extrema (i.e., maximum or minimum points) in the frequency domain. From the clock data in the frequency domain, larger extrema are identified directly. Meanwhile, for the detection of smaller extrema, a robust estimation method based on the median filter was applied. Then, all smaller extrema were classified into three types. Different preprocessing methods were applied for every type. After that, a new preprocessed precise clock product was obtained. With this preprocessed satellite clock product, the ISB continuity was substantially improved, and the improvement in the ISB continuity can reach 85.1%, on the average. These results indicate that for detecting and repairing ISB jumps, the proposed preprocessing method on satellite clock products is very effective.

Highlights

  • GNSS (Global Navigation Satellite System) is developing quickly along with the modernizing of American GPS and Russian GLONASS and the launching of Europe’s Galileo, China’s BDS (BeiDou navigation satellite system) with new frequency signals being transmitted

  • Fixed to GFZ MGEX (GBM) products Zenith hydrostatic delay with Saastamoinen model, Zenith wet delay using random walk process with a constraint of 1 cm2/h; Global mapping function (GMF) is implemented as the mapping function The first-order error eliminated by the way of the ionospheric-free linear combination In GPS, igs14.atx are used for phase center offset (PCO) and phase center variations (PCV) correction; In BDS, corrections are applied the same as GPS igs14.atx are used for PCO and PCV correction

  • The satellite clock product is converted from time domain into frequency domain, since it is more sensitive to the detection of inter-system bias (ISB) jumps

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Summary

Introduction

GNSS (Global Navigation Satellite System) is developing quickly along with the modernizing of American GPS (global positioning system) and Russian GLONASS (global navigation satellite system) and the launching of Europe’s Galileo, China’s BDS (BeiDou navigation satellite system) with new frequency signals being transmitted. Found that GPS/BDS combined with PPP can achieve improvements on the positioning accuracy, reliability, and availability. Jiang et al [15] designed five schemes to evaluate the impacts of the different ISB stochastic models on GPS/BDS combined PPP. It is possible to improve the convergence time and accuracy of combined PPP with a priori ISB constraining from the precise modeling [13]. In this study, to detect and repair jumps in the satellite clock products, a preprocessing method is presented to improve the continuity of ISB. In order to analyze new satellites and signals to handle the solution by combined multiple GNSS observations, IGS (International GNSS Service) launched MGEX (multi-GNSS experiment). Trimble NeTR9/5.01 Trimble NeTR9/5.01 Trimble NeTR9/5.03 SEPT PolaRx4/2.9.0 SEPT PolaRx4TR/2.9.0Patch SEPT PolaRx4TR/2.9.0Patch

Estimation Model and Processing Strategies
Processing Strategies
The Incentive of Precise Satellite Clock Preprocessing
Results and Discussion
Conversion from Time Domain into Frequency Domain
Detection of Small Extrema in CFD
Conclusions
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