GNSS coordinate time series denoising analysis combined with weighted wavelet and EEMD

Aiming at the problem that it is difficult to accurately separate the useful signal and noise in the GNSS coordinate time series, this paper proposes a noise reduction method based on combined weighted wavelet Z-transform (WWZ) and set empirical mode decomposition (EEMD). Through the noise reduction processing of the vertical coordinate time series of 70 continuous stations in the northwest region, the root mean square error (RMSE), signal-to-noise ratio (SNR), flicker noise (FN) amplitude and velocity uncertainty are used as the evaluation indicators respectively, which verifies that the noise reduction effect of the method in this paper is superior to wavelet noise reduction and EEMD noise reduction to a certain extent. The results show that compared with wavelet denoising and EEMD denoising, the RMSE of signal sequence after denoising is reduced by 0.331 mm and 0.757 mm respectively, and the SNR is increased by 1.911 dB and 3.635 dB respectively; The uncertainty of FN amplitude and velocity has been significantly improved, which verifies the effectiveness of the noise reduction method in this paper.