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<p>As most global navigation satellite system (GNSS) receivers have limited support for all satellite signals across diverse frequency bands for power consumption, the strategy of fully exploiting the multi-frequency data becomes crucial. This paper proposes multi-GNSS mixed-frequency precise point positioning (MGMF-PPP), integrating single-frequency PPP (SF-PPP) and dual-frequency PPP (DF-PPP). Single-frequency ionospheric delays are corrected via global ionospheric map (GIM) products, while dual-frequency data are processed with an uncombined model. MGMF-PPP has been validated through static and dynamic experiments. The results demonstrate that in static experiment, the horizontal and vertical accuracy of MGMF-PPP is increased by 53.1%/28.1% compared to SF-PPP, and 21.1%/25.8% compared to DF-PPP. In open-environment dynamic experiment, the horizontal and vertical accuracy of MGMF-PPP is increased by 33.8%/25.9% compared to SF-PPP, and 12.5%/57.0% compared to DF-PPP. In complex environments, MGMF-PPP exhibits significant vertical accuracy advantages.</p>

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Hybrid Single/Dual-frequency PPP Model for Superior Positioning Performance

  • 期刊论文

  • 发表日期：

    2025年11月6日

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  • Weijia Xiao,
  • Yan Xiang,
  • Huan Liu,
  • Qianyi Ren,
  • Ling Pei

摘要

As most global navigation satellite system (GNSS) receivers have limited support for all satellite signals across diverse frequency bands for power consumption, the strategy of fully exploiting the multi-frequency data becomes crucial. This paper proposes multi-GNSS mixed-frequency precise point positioning (MGMF-PPP), integrating single-frequency PPP (SF-PPP) and dual-frequency PPP (DF-PPP). Single-frequency ionospheric delays are corrected via global ionospheric map (GIM) products, while dual-frequency data are processed with an uncombined model. MGMF-PPP has been validated through static and dynamic experiments. The results demonstrate that in static experiment, the horizontal and vertical accuracy of MGMF-PPP is increased by 53.1%/28.1% compared to SF-PPP, and 21.1%/25.8% compared to DF-PPP. In open-environment dynamic experiment, the horizontal and vertical accuracy of MGMF-PPP is increased by 33.8%/25.9% compared to SF-PPP, and 12.5%/57.0% compared to DF-PPP. In complex environments, MGMF-PPP exhibits significant vertical accuracy advantages.