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<p>Global navigation satellite system (GNSS) precise point positioning (PPP) performance experiences significant degradation under complex ionospheric conditions, particularly during geomagnetic storm events. To address this challenge, this study develops an adaptive geometry-free (GF) cycle slip detection threshold model, leveraging GNSS Doppler measurements to reduce the incorrect cycle slip detection, thereby enhancing the accuracy and reliability of GNSS PPP. The proposed threshold model is fitted using Doppler index data extracted from 110 International GNSS Service (IGS) stations on the 11th May 2024 when an extreme geomagnetic storm occurred. 72 IGS stations which are not used in modeling on the same day are employed to validate its performance. The results show that PPP with adaptive GF cycle slip detection threshold can achieve positioning accuracy improvements by 42.4% and 37.2% in horizontal and vertical directions, respectively, compared with traditional strategy. Furthermore, positioning accuracy improvements of 63.1% and 50.1% in horizontal and vertical are obtained with data from another geomagnetic storm event on the 11th October 2024, which further demonstrates the efficiency and uniformity of proposed model. Comparison of positioning accuracy with tight and loose thresholds during the ionospheric quiescence periods also verifies the adaptability of the built model.</p>

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Precise point positioning with an adaptive geometry-free cycle slip detection threshold under complex ionospheric conditions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月23日

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  • Long Tang,
  • Luheng Zhou,
  • Fan Xu,
  • Jiahuan Hu,
  • Xiaohong Zhang

摘要

Global navigation satellite system (GNSS) precise point positioning (PPP) performance experiences significant degradation under complex ionospheric conditions, particularly during geomagnetic storm events. To address this challenge, this study develops an adaptive geometry-free (GF) cycle slip detection threshold model, leveraging GNSS Doppler measurements to reduce the incorrect cycle slip detection, thereby enhancing the accuracy and reliability of GNSS PPP. The proposed threshold model is fitted using Doppler index data extracted from 110 International GNSS Service (IGS) stations on the 11th May 2024 when an extreme geomagnetic storm occurred. 72 IGS stations which are not used in modeling on the same day are employed to validate its performance. The results show that PPP with adaptive GF cycle slip detection threshold can achieve positioning accuracy improvements by 42.4% and 37.2% in horizontal and vertical directions, respectively, compared with traditional strategy. Furthermore, positioning accuracy improvements of 63.1% and 50.1% in horizontal and vertical are obtained with data from another geomagnetic storm event on the 11th October 2024, which further demonstrates the efficiency and uniformity of proposed model. Comparison of positioning accuracy with tight and loose thresholds during the ionospheric quiescence periods also verifies the adaptability of the built model.