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<p>Real-time precise point positioning (PPP) time transfer is a crucial technique for the time and frequency field. However, its performance remains limited by the relatively long convergence time resulting from unstable parameter estimation in the initial stage. In this contribution, predicted tropospheric products provided by the Global Forecast System (GFS) are employed to derive predicted Zenith Wet Delays (ZWDs) for each station. The predicted ZWDs are subsequently incorporated into the real-time PPP as virtual observations, thereby enhancing the performance of the real-time PPP time transfer. One week of data from 20 globally distributed stations was used to form 19 time links. Results showed that the average root mean square error (RMSE) for the predicted ZWD amounts to 1.4&#xa0;cm. For the traditional PPP strategy with ZWD estimation, the average convergence time of all links is 7.18 and 9.24&#xa0;min for the static and kinematic modes, respectively. With the ZWD augmentation, they are shortened to 5.77 and 7.26&#xa0;min, with improvements of 19.6% and 21.4%, respectively. In terms of the time link precision, the traditional and GFS ZWD-augmented methods yield 0.483 and 0.414 ns in the static mode, and 0.607 and 0.508 ns in the kinematic mode, with improvements of 14.3% and 16.3%, respectively. Regarding time link stability, improvements range from 10.0 to 20.6% in the static mode and from 9.7 to 21.4% in the kinematic mode when the averaging time is from 30 to 3600&#xa0;s. These results clearly demonstrate that incorporating ZWD as external constraints can significantly enhance real-time PPP time transfer, particularly during the convergence period.</p>

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Improving real-time PPP time transfer with the augmentation of predicted tropospheric products

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月27日

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  • Wei Xie,
  • Kan Wang,
  • Mengyuan Li,
  • Zi Chen,
  • Guolin Liu,
  • Mengjun Wu,
  • Xiaolong Mi,
  • Xuhai Yang

摘要

Real-time precise point positioning (PPP) time transfer is a crucial technique for the time and frequency field. However, its performance remains limited by the relatively long convergence time resulting from unstable parameter estimation in the initial stage. In this contribution, predicted tropospheric products provided by the Global Forecast System (GFS) are employed to derive predicted Zenith Wet Delays (ZWDs) for each station. The predicted ZWDs are subsequently incorporated into the real-time PPP as virtual observations, thereby enhancing the performance of the real-time PPP time transfer. One week of data from 20 globally distributed stations was used to form 19 time links. Results showed that the average root mean square error (RMSE) for the predicted ZWD amounts to 1.4 cm. For the traditional PPP strategy with ZWD estimation, the average convergence time of all links is 7.18 and 9.24 min for the static and kinematic modes, respectively. With the ZWD augmentation, they are shortened to 5.77 and 7.26 min, with improvements of 19.6% and 21.4%, respectively. In terms of the time link precision, the traditional and GFS ZWD-augmented methods yield 0.483 and 0.414 ns in the static mode, and 0.607 and 0.508 ns in the kinematic mode, with improvements of 14.3% and 16.3%, respectively. Regarding time link stability, improvements range from 10.0 to 20.6% in the static mode and from 9.7 to 21.4% in the kinematic mode when the averaging time is from 30 to 3600 s. These results clearly demonstrate that incorporating ZWD as external constraints can significantly enhance real-time PPP time transfer, particularly during the convergence period.