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Single-Frequency GNSS Integer Ambiguity Solving Based on Adaptive Genetic Particle Swarm Optimization Algorithm.

Ying-Qing Guo1, Yan Zhang1, Zhao-Dong Xu2

  • 1College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.

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|December 9, 2023
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Summary
This summary is machine-generated.

This study introduces an Adaptive Genetic Particle Swarm Optimization (AGPSO) algorithm for faster and more accurate single-frequency Global Navigation Satellite Systems (GNSS) positioning by improving integer ambiguity resolution.

Keywords:
adaptive genetic particle swarm optimization (AGPSO)carrier phase measurementglobal navigation satellite system (GNSS)integer ambiguity

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Area of Science:

  • Geomatics Engineering
  • Satellite Navigation Systems
  • Artificial Intelligence in Positioning

Background:

  • Accurate positioning with Global Navigation Satellite Systems (GNSS) relies heavily on resolving carrier phase integer ambiguities.
  • Traditional methods for integer ambiguity resolution can be inefficient and slow, hindering rapid positioning.

Purpose of the Study:

  • To develop a novel algorithm for efficient and accurate single-frequency GNSS integer ambiguity resolution.
  • To improve the speed and stability of the ambiguity search process using intelligent optimization techniques.

Main Methods:

  • Proposed an Adaptive Genetic Particle Swarm Optimization (AGPSO) algorithm for single-frequency GNSS.
  • Utilized carrier-phase double difference equations for floating-point solutions and covariance matrix estimation.
  • Employed the inverse integer Cholesky algorithm for decorrelation and an improved fitness function for enhanced performance.
  • Integrated particle swarm optimization with adaptive weights, crossover, and mutation for robust integer ambiguity search.

Main Results:

  • The AGPSO algorithm demonstrated faster convergence rates compared to traditional and other intelligent algorithms.
  • Achieved improved stability in integer ambiguity search results.
  • Practical experiments showed a baseline accuracy within 0.02 m for short baselines.

Conclusions:

  • The AGPSO algorithm offers a significant improvement in efficiency and accuracy for single-frequency GNSS integer ambiguity resolution.
  • The method shows practical application value, particularly for short baseline scenarios.
  • The developed algorithm effectively addresses the limitations of existing methods in speed and stability.