Application of EMD to GNSS Time Series Periodic Term Processing

  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 deformation 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 extract 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.