Complex singular spectrum analysis of earth orientation time series

Abstract

The separation of geodetic time series into a sum of a small number of independent and interpretable components is of great importance. Approaches such as Singular Spectrum Analysis (SSA) and Multi-channel Singular Spectrum Analysis (MSSA) have shown their advantage in this field. The aim of this thesis is to develop theoretical aspects of Complex Singular Spectrum Analysis (CSSA) technique and demonstrate that CSSA can be considered as a powerful method of time series analysis. CSSA is a non-parametric method which extends SSA into bivariate time series analysis technique with complex values. Using EOP time series in the time period spanning from 1960 to 2009, Chandler wobble (CW), annual wobble (AW) as well as a non-linear trend are successfully separated in both x and y direction by SSA and MSSA. This paper provides evidence for CSSA when performing tasks of EOP time series decomposition. CSSA functions quasi-equivalent with SSA and MSSA of polar motion time series analysis.