Denoising analysis of GNSS coordinate time series by combining EMD-HD and wavelet decomposition

doi:10.11947/j.AGCS.2022.20210175

Abstract

Abstract: This study proposes the EMD-HD&WD algorithm to solve the limitations of screening rules and mode mixing in the denoising analysis of the GNSS coordinate time series when using empirical mode decomposition (EMD). The improved algorithm introduces the Hausdorff distance (HD) as a screening criterion for EMD and combines wavelet decomposition (WD). The reliability and universality of EMD-HD&WD algorithm were verified by 149 GNSS vertical time series in the crustal movement observation network of China. The results show that the HD is better than the existing screening criteria; the average correction rates of the EMD-HD&WD for the velocity uncertainty and the amplitude of flicker noise of GNSS stations are 88.4%. The algorithm can effectively identify the observational noise, reduce the mode aliasing of EMD, and improve the model accuracy of GNSS vertical coordinate time series.

Key words: GNSS coordinate time series, empirical mode decomposition, wavelet decomposition, Hausdorff distance, velocity uncertainty

CLC Number:

P228

YANG Bing, YANG Zhiqiang, TIAN Zhen, CHEN Xiang. Denoising analysis of GNSS coordinate time series by combining EMD-HD and wavelet decomposition[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(9): 1881-1889.

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