GNSS Coordinate Time Series Denoising Method Based on Parameter-Optimized Variational Mode Decomposition

LU Tieding; HE Jinliang; HE Xiaoxing; TAO Rui

doi:10.13203/j.whugis20220363

Volume 49 Issue 10

Oct. 2024

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Geomatics and Information Science of Wuhan University > 2024 > 49(10): 1856-1866. > DOI: 10.13203/j.whugis20220363

LU Tieding, HE Jinliang, HE Xiaoxing, TAO Rui. GNSS Coordinate Time Series Denoising Method Based on Parameter-Optimized Variational Mode Decomposition[J]. Geomatics and Information Science of Wuhan University, 2024, 49(10): 1856-1866. DOI: 10.13203/j.whugis20220363

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GNSS Coordinate Time Series Denoising Method Based on Parameter-Optimized Variational Mode Decomposition

LU Tieding^{1, 2,},
HE Jinliang^1, ,,
HE Xiaoxing³,
TAO Rui¹

1.
School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang330013, China
2.
Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake, Ministry of Natural Resources,Nanchang330013, China
3.
School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou341000, China

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Received Date: October 24, 2022
Available Online: April 12, 2023

Graphical Abstract

Abstract

Abstract

Objectives
In order to effectively filter out complex noise components in GNSS coordinate time series and extract effective signals, we construct a denoising method based on parameter-optimized variational modal decomposition (VMD).
Methods
First, the combination of permutation entropy and mutual information is used as fitness function, and the optimal parameter combination of the mode decomposition number $K$ and the quadratic penalty factor $α$ of VMD is obtained by using grey wolf optimization algorithm(GWO). Then the GNSS coordinate time series is decomposed into $K$ eigen mode function components by VMD. Finally, the sample entropy is used to determine the effective modal component, which is reconstructed as an effective signal, so as to realize the effective separation of signal and noise.The GWO-VMD method is compared and analyzed with the empirical mode decomposition (EMD), wavelet denoising (WD) and IVMD methods by using the simulated signal and the measured data from 20 reference stations of the crustal movement observation network of China for experiments.
Results
The simulated signal experiments show that the three denoising evaluation indexes of root mean square error,correlation coefficient and signal-to-noise ratio of GWO-VMD denoising signal are better than EMD, WD and IVMD methods. The experiments on the measured data show that the GWO-VMD method can reduce the amplitude of noise significantly. In terms of the velocity uncertainty of the reference station, the overall GWO-VMD method reduces the velocity uncertainty better than the EMD, WD and IVMD methods.
Conclusions
The GWO-VMD method can more effectively remove the noise from GNSS coordinate time series and better preserve the original characteristics of the signal, which can provide reliable data for subsequent analysis and processing.
- GNSS coordinate time series,
- VMD,
- GWO,
- permutation entropy,
- mutual information,
- sample entropy,
- signal denoising

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References

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