Spatiotemporal Signal and Noise Analysis of GPS Position Time Series of the Permanent Stations in China

Abstract

This paper aims to analyze the signal and noise characteristics of the GPS position time series of the permanent stations in China. We first extract the Common Mode Components (CMC) from the position series of regional GPS stations using principal component analysis and separate the GPS station position time series into CMC and the filtered series of each station. Then we detect the Unmodeled Common Signals (UCS) and Common Noises (CN) in CMC using power spectrum analysis, and analyze the noise characteristics of CN using a MINQUE (Minimum Norm Quadratic Unbiased Estimation) method of variance component estimation. We also detect periodic signals using power spectrum analysis and analyze different noise components using MINQUE method from the filtered series. Total 7-year GPS station position time series of the 24 permanent stations in China have been processed. The results show that the CMC accounts for 38.8 %, 39.1 % and 32.7 % from the total variances in north, east and up, respectively. CMC are dominated by CN. The dominant periods of UCS are about 792 days in north and up and about 594 days in east. In CN, the flicker noise is slightly larger than the white noise, and the random walk noise is very small. The periodic signals are all significant in the filtered series of all stations, especially the annual signals in up direction. Furthermore, the flicker noise of filtered series is also slightly larger than the white noise; however random walk noise is significantly large in most stations and even larger than white or flicker noise in few stations.