Abstract:Based on the ability of ICEEMDAN algorithm to accurately separate and extract low-frequency signals and trend information without a priori information, and the advantage of SSA with better signal reconstruction, we propose a joint reconstruction method based on ICEEMDAN and SSA. The method extracts and reconstructs the weak periodic signals by using ICEEMDAN method; this makes up for a deficiency of the SSA method, namely that it is difficult to extract periodic signals when the singular values of the Hankel matrix corresponding to the weak periodic signals are close to the singular values of the noisy Hankel matrix, which are easily masked by noise. We verify the decomposition and reconstruction accuracy of the algorithm by simulated experiments and real site data. We further compare the algorithm with the singular spectrum analysis, wavelet decomposition, and moving ordinary least squares methods. The experimental results show that the joint ICEEMDAN-SSA algorithm has better reconstruction accuracy compared with existing methods.
ZHANG Yilei,BIAN Jiawen,DING Kaihua et al. GPS Coordinate Time Series Reconstruction Based on ICEEMDAN and SSA Joint Algorithm[J]. jgg, 2022, 42(9): 904-909.