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<p>Accurate extraction of high-precision ionospheric observables is crucial for developing reliable ionospheric models. Conventional methods, such as code or carrier-to-code leveling observables, are limited by pseudorange multipath, noise, and leveling biases. With the recent advances in real-time precise point positioning with ambiguity resolution (PPP-AR), carrier-phase ambiguity-fixed ionospheric observables can be derived. This study develops a real-time multi-GNSS PPP-AR framework for ionospheric observable extraction, addressing three critical challenges: (1) one-cycle inconsistency in wide-lane ambiguity resolution, (2) satellite eclipse-induced attitude modeling errors, and (3) receiver hardware biases. Experiments using real-time products and GPS/Galileo/BDS observations from 14 MGEX stations over two weeks were conducted. Co-location experiments showed that the standard deviations of single-differenced slant TEC were 1.4, 2.1, and 2.0 TECu for GPS, Galileo, and BDS with PPP-float, while reduced to 0.05, 0.05, and 0.07 TECu with PPP-AR. Receiver bias correction further improved the consistency with CODE global ionospheric maps, yielding station-wise mean offsets at the submeter level. Overall, PPP-AR achieved an accuracy improvement of up to 96% compared to PPP-float, demonstrating its effectiveness and reliability for real-time ionospheric monitoring.</p>

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Real-time extraction of multi-GNSS ionospheric observables based on PPP-AR

  • 期刊论文

  • 发表日期：

    2025年10月22日

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  • Yan Xiang,
  • Yifan Zhao,
  • Tiantian Tang,
  • Ningbo Wang,
  • Zishen Li,
  • Ling Pei,
  • Wenxian Yu

摘要

Accurate extraction of high-precision ionospheric observables is crucial for developing reliable ionospheric models. Conventional methods, such as code or carrier-to-code leveling observables, are limited by pseudorange multipath, noise, and leveling biases. With the recent advances in real-time precise point positioning with ambiguity resolution (PPP-AR), carrier-phase ambiguity-fixed ionospheric observables can be derived. This study develops a real-time multi-GNSS PPP-AR framework for ionospheric observable extraction, addressing three critical challenges: (1) one-cycle inconsistency in wide-lane ambiguity resolution, (2) satellite eclipse-induced attitude modeling errors, and (3) receiver hardware biases. Experiments using real-time products and GPS/Galileo/BDS observations from 14 MGEX stations over two weeks were conducted. Co-location experiments showed that the standard deviations of single-differenced slant TEC were 1.4, 2.1, and 2.0 TECu for GPS, Galileo, and BDS with PPP-float, while reduced to 0.05, 0.05, and 0.07 TECu with PPP-AR. Receiver bias correction further improved the consistency with CODE global ionospheric maps, yielding station-wise mean offsets at the submeter level. Overall, PPP-AR achieved an accuracy improvement of up to 96% compared to PPP-float, demonstrating its effectiveness and reliability for real-time ionospheric monitoring.