EMD 在 GNSS 时间序列周期项处理中的应用.

Objectives: The position time series of global navigation satellite system (GNSS) contain rich tectonic and non-tectonic deformation information, and the complex components are difficult to accurately model and effectively separate non-tectonic information. It is very important to remove the non-tectonic de‐ formation information for the accurate and effective application of the observation data. Methods: Empirical mode decomposition （EMD） is an adaptive time-frequency processing method to correct the period term of time series at 24 GNSS continuous stations and 2 mobile stations in Sichuan Province and Yunnan Province. Results: The results show that the correction of the period term is necessary, and the EMD method can ex‐ tract the different frequency and amplitude period components adaptively according to its own characteristics of signal at each station. Compared with the original time series, the average root mean square error after correction is reduced significantly in N, E and U directions. And EMD method is more accurate and effective than harmonic model modification. We use the modified continuous station time series to simulate the mobile observations, and find that relatively reliable motion velocities can be obtained after an observation period of 5 ‐6 years. The stability and reliability of EMD method are verified by correcting the period term of the mobile station with the actual continuous observation station at a close distance. Conclusions: This paper provides a reference and theoretical basis for the implementation of mobile GNSS observation and the correction of observation data. [ABSTRACT FROM AUTHOR]