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A Two-Step Regional Ionospheric Modeling Approach for PPP-RTK.

Zhenyu Xu1, Changsheng Cai1,2, Lin Pan1

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Summary
This summary is machine-generated.

This study introduces a new two-step ionospheric modeling method for precise point positioning/real-time kinematic (PPP-RTK) to improve positioning accuracy. The Polynomial Fitting Model combined with Kriging Interpolation (PFM/KI) significantly reduces ionospheric delay errors and speeds up convergence.

Keywords:
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Area of Science:

  • Geodesy and Geomatics
  • Atmospheric Science
  • Satellite Navigation

Background:

  • Precise Point Positioning/Real-Time Kinematic (PPP-RTK) relies on accurate ionospheric delay corrections for rapid convergence.
  • Current ionospheric models in PPP-RTK often neglect residual ionospheric delays, impacting positioning accuracy.
  • Existing methods primarily focus on the trend term of ionospheric total electron content (TEC) variations.

Purpose of the Study:

  • To develop and validate a novel two-step regional ionospheric modeling approach for enhanced PPP-RTK performance.
  • To improve the accuracy of ionospheric delay corrections by modeling both trend and residual TEC variations.
  • To assess the impact of the proposed model on PPP-RTK convergence speed and positioning accuracy.

Main Methods:

  • A two-step modeling approach combining a Polynomial Fitting Model (PFM) for the trend term and Kriging Interpolation (KI) for the residual term of TEC variations.
  • Validation using datasets from Continuously Operating Reference Stations (CORSs) in Hunan Province, China.
  • Comparison against a single PFM method and a PFM combined with Inverse Distance Weighting Interpolation (IDWI).

Main Results:

  • The PFM/KI method achieved an average root mean square (RMS) error of 1.8 cm for modeled ionospheric delay, outperforming PFM (48% improvement) and PFM/IDWI (23% improvement).
  • PPP-RTK using PFM/KI converged to 1.3 cm horizontal accuracy in 1.8 minutes and 2.5 cm vertical accuracy in 4.0 minutes.
  • Convergence times were reduced by 18% (horizontal) and 9% (vertical) compared to PFM, and 14% (horizontal) and 5% (vertical) compared to PFM/IDWI.

Conclusions:

  • The proposed two-step PFM/KI ionospheric modeling significantly enhances the accuracy of ionospheric delay corrections in PPP-RTK.
  • This improved modeling leads to faster convergence times and higher positioning accuracy in PPP-RTK applications.
  • The PFM/KI method offers a superior alternative to existing ionospheric modeling techniques for real-time kinematic positioning.