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On the Problem of Double-Filtering in PPP-RTK.

A Khodabandeh1, P J G Teunissen1,2,3, D Psychas4

  • 1Department of Infrastructure Engineering, The University of Melbourne, Melbourne 3010, Australia.

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|January 8, 2023
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Summary
This summary is machine-generated.

This study introduces a new multi-epoch filter for Precise Point Positioning-Real Time Kinematic (PPP-RTK) users. It improves Global Navigation Satellite System (GNSS) parameter solution precision by accounting for correction uncertainty and temporal correlation.

Keywords:
Kalman filterdouble-filteringglobal navigation satellite system (GNSS)integer ambiguity resolution enabled precise point positioning (PPP-RTK)time-correlated corrections

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Area of Science:

  • Geomatics Engineering
  • Satellite Navigation Systems
  • Signal Processing

Background:

  • Precise Point Positioning-Real Time Kinematic (PPP-RTK) systems rely on external corrections.
  • Standard user-filters violate Kalman filter assumptions due to time-correlated corrections, leading to imprecise Global Navigation Satellite System (GNSS) solutions.
  • Correction latency exacerbates precision loss in traditional PPP-RTK user-filters.

Purpose of the Study:

  • To develop a novel multi-epoch formulation for the PPP-RTK user-filter.
  • To incorporate both the uncertainty and temporal correlation of corrections into the user-filter.
  • To enhance the precision of GNSS parameter solutions in PPP-RTK.

Main Methods:

  • Augmenting the user-filter state-vector to include correction characteristics.
  • Jointly updating user parameters and corrections within the measurement update step.
  • Implementing a multi-epoch Kalman filter approach.

Main Results:

  • The proposed formulation successfully incorporates correction uncertainty and temporal correlation.
  • Numerical results demonstrate superior performance compared to conventional methods.
  • The new filter achieves the minimum-variance property, enhancing solution precision.

Conclusions:

  • The novel multi-epoch PPP-RTK user-filter formulation significantly improves GNSS solution precision.
  • Accounting for correction temporal correlation and uncertainty is crucial for optimal filter performance.
  • This approach offers a more robust and accurate method for real-time GNSS positioning.