Abstract:Aiming at the characteristics of complex noise and poor precision of GNSS vertical coordinate time series, we use the locally weighted regression(LOESS) method to denoise the vertical coordinate time series of 289 GNSS stations in the crustal movement observation network of China. Firstly, we use the LOESS method to denoise the preprocessed time series, and obtain the denoised time series and noise series. Then, we use the Durbin-Watson test for autocorrelation of denoised series, and the Wilcoxon rank sum test method for significance test of the standard deviation, noise term and velocity uncertainty of the series before and after denoising. Finally, we use the signal-noise ratio and the above three indicators to quantitatively evaluate the denoising effects. The results show there is no autocorrelation in the noise series of each station after denoising, and each evaluation index has significant correction after noise reduction by using LOESS method. LOESS method can effectively reduce the noise of GNSS vertical coordinate time series, and improve the accuracy of the GNSS vertical coordinate time series.
CHEN Xiang,YANG Zhiqiang,YANG Bing et al. Noise Recognition and Extraction of GNSS Vertical Coordinate Time Series Based on LOESS[J]. jgg, 2021, 41(10): 1024-1029.