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<p>GNSS network RTK is widely used in autonomous driving and precision mapping due to its high accuracy and coverage. However, NRTK relies on stable communication links. In complex environments such as mountainous or offshore areas, communication interruptions or limited bandwidth can delay the transmission of correction data, thereby degrading positioning accuracy. Asynchronous RTK (ARTK) has attracted increasing attention for its strong tolerance to communication outages. However, with increasing data age, accumulating errors from orbit, clock, ionospheric, and tropospheric delays cannot be fully eliminated by conventional double-difference models, resulting in diminished positioning performance. To address this issue, this paper proposes an asynchronous RTK method enhanced by satellite-based PPP corrections, with PPP-B2b selected as a representative case (B2b-ARTK). It models and compensates the four major error sources. Precise orbit and clock corrections derived from PPP-B2b are applied to mitigate residual errors caused by asynchronous updates. The first-order ionospheric delay is eliminated through a dual-frequency ionosphere-free combination, and the tropospheric delay is corrected using the empirical GPT2w model. Experimental results based on both static and dynamic datasets indicate that, after communication interruptions, the B2b-ARTK method achieves higher positioning accuracy than the ARTK model based on broadcast ephemeris (Brdc-ARTK) and the single-station PPP approach using PPP-B2b corrections (B2b-PPP). In dynamic vehicle experiments, B2b-ARTK maintained a reliable fixed solution for approximately 650&#xa0;s after communication loss, with a maximum 3D positioning error of 0.085&#xa0;m, whereas Brdc-ARTK sustained fixed solutions for only 382&#xa0;s with a maximum error of 0.178&#xa0;m. These results demonstrate that the B2b-ARTK method effectively mitigates the degradation of RTK performance under unstable communication conditions, ensuring reliable GNSS positioning for applications such as autonomous driving.</p>

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Asynchronous RTK positioning enhanced by satellite-based PPP corrections: a case study with PPP-B2b

  • 期刊论文

  • 发表日期：

    2025年11月22日

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  • Hong Huang,
  • Wang Gao,
  • Shuguo Pan,
  • Longlei Qiao,
  • Qing Zhao

摘要

GNSS network RTK is widely used in autonomous driving and precision mapping due to its high accuracy and coverage. However, NRTK relies on stable communication links. In complex environments such as mountainous or offshore areas, communication interruptions or limited bandwidth can delay the transmission of correction data, thereby degrading positioning accuracy. Asynchronous RTK (ARTK) has attracted increasing attention for its strong tolerance to communication outages. However, with increasing data age, accumulating errors from orbit, clock, ionospheric, and tropospheric delays cannot be fully eliminated by conventional double-difference models, resulting in diminished positioning performance. To address this issue, this paper proposes an asynchronous RTK method enhanced by satellite-based PPP corrections, with PPP-B2b selected as a representative case (B2b-ARTK). It models and compensates the four major error sources. Precise orbit and clock corrections derived from PPP-B2b are applied to mitigate residual errors caused by asynchronous updates. The first-order ionospheric delay is eliminated through a dual-frequency ionosphere-free combination, and the tropospheric delay is corrected using the empirical GPT2w model. Experimental results based on both static and dynamic datasets indicate that, after communication interruptions, the B2b-ARTK method achieves higher positioning accuracy than the ARTK model based on broadcast ephemeris (Brdc-ARTK) and the single-station PPP approach using PPP-B2b corrections (B2b-PPP). In dynamic vehicle experiments, B2b-ARTK maintained a reliable fixed solution for approximately 650 s after communication loss, with a maximum 3D positioning error of 0.085 m, whereas Brdc-ARTK sustained fixed solutions for only 382 s with a maximum error of 0.178 m. These results demonstrate that the B2b-ARTK method effectively mitigates the degradation of RTK performance under unstable communication conditions, ensuring reliable GNSS positioning for applications such as autonomous driving.