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Updated: Sep 19, 2025

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GNSS signal processing based on improved lifting wavelet transform with prior constraint.

Chen Jiang1, Wenbo Yang1, Yiya Wang1

  • 1College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.

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|June 18, 2025
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Summary
This summary is machine-generated.

This study introduces an improved lifting wavelet transform for Global Navigation Satellite System (GNSS) deformation monitoring. The method effectively reduces noise, enabling accurate extraction of structural vibration information for dynamic analysis.

Keywords:
GNSSlifting wavelet transformmultipath effectprior constraintvibration deformation

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Area of Science:

  • Geodesy and Geomatics Engineering
  • Signal Processing

Background:

  • Global Navigation Satellite System (GNSS) deformation monitoring faces challenges in controlling noise and extracting structural vibration.
  • Initial GNSS signals contain significant interference, complicating accurate data analysis.

Purpose of the Study:

  • To develop an improved method for denoising GNSS signals.
  • To enhance the extraction of structural vibration information from noisy GNSS data.
  • To improve the efficiency of lifting wavelet transform using prior information.

Main Methods:

  • An improved three-segment soft threshold function was proposed for noise control.
  • Wavelet decomposition was applied to denoised signals for vibration and noise extraction.
  • The improved algorithm was compared against conventional lifting wavelet transform.

Main Results:

  • The improved lifting wavelet transform demonstrated superior performance in signal denoising compared to the conventional method.
  • Valid structural vibration information and significant noises were effectively identified using prior information constraints.
  • The algorithm improved coordinate calculation accuracy in GNSS monitoring points.

Conclusions:

  • The developed algorithm offers a valuable approach for GNSS data processing and dynamic deformation extraction.
  • It provides a reliable method for identifying structural vibrations and significant noises.
  • The research supports external load analysis and structural health monitoring using GNSS.