Feasibility study of GPS time series analysis with time-dependent periodic coefficients model (TDPC)

A timedependent periodic coefficients (TDPC) model was proposed to analyze the Global Positioning System (GPS) time series. Due to the variations of the amplitude and phaselag of the GPS signals over time, we propose a TDPC to analyze the daily time series. A new solution approach, where the serial correlations of the disturbances are eliminated by sequentially differencing the measurements, was used to estimate the model parameters using weighted least squares. As a numerical performance of the proposed method, the time series of 19 permanent stations in the United States via the Website of Scripps Orbit and Permanent Array Center (SOPAC) between the 2000 and 2010 year was selected. The results show a decrease in the RMS values of the residuals, especially for the height components. Moreover, using the 90 simulated GPS data analysis, in which their noises were different combinations of white noise and flicker noise, we demonstrate that the proposed model can extract amplitude varying periodic variabilities from GPS coordinate time series.