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A Partial Carrier Phase Integer Ambiguity Fixing Algorithm for Combinatorial Optimization between Network RTK

Shouhua Wang1,2,3, Zhiqi You1,3, Xiyan Sun1,3

  • 1College of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.

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Summary
This summary is machine-generated.

This study introduces a new network real-time kinematic (RTK) algorithm to improve positioning accuracy in challenging environments. The method enhances the reliability of network RTK reference station results by optimizing ambiguity fixing.

Keywords:
ambiguity resolutionnetwork RTKpartial ambiguity fixationrobust extended Kalman filtering

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Area of Science:

  • Geomatics Engineering
  • Satellite Navigation Systems
  • Signal Processing

Background:

  • Network real-time kinematic (RTK) positioning accuracy is challenged by complex observation environments and signal occlusions.
  • Jointly solving multiple systems increases ambiguity dimensions, complicating estimation.
  • Gross errors in satellite observations due to occlusions lead to positioning deviations.

Purpose of the Study:

  • To develop a novel network RTK algorithm for fixing partial ambiguity among reference stations.
  • To enhance the reliability and accuracy of positioning results in obstructed environments.
  • To address the challenges of increased ambiguity dimensions and gross errors in network RTK.

Main Methods:

  • Robust extended Kalman filtering (EKF) with mean estimation for floating-point ambiguity.
  • Optimized partial ambiguity solving for identifying optimal ambiguity subsets.
  • Least-squares ambiguity decorrelation adjustment (LAMBDA) and joint R-ratio/bootstrapping tests for final fixing.

Main Results:

  • The proposed algorithm significantly improves the ambiguity fixation rate in network RTK.
  • Enhanced reliability of positioning results is achieved.
  • Effective handling of gross errors and high ambiguity dimensions demonstrated.

Conclusions:

  • The new partial ambiguity fixing algorithm offers a robust solution for network RTK in complex environments.
  • Improved fixation rates directly translate to more reliable positioning outcomes.
  • The method effectively mitigates issues caused by signal occlusions and multi-system integration.