Offset Detection in GPS Position Time Series with Colored Noise

Offsets in GPS position time series often lead discontinuities in deformation analysis. The estimation of geodetic station velocities and their uncertainties will be biased if the offsets are not modeled. The detection and correction of offsets are fundamental steps in pre-processing of GPS position time series in dynamic geodetic studies. In this paper, based on the Sequential t-Test Analysis of Regime Shifts (STARS) algorithm, we propose a colored modified method called COL-STARS to detect offsets considering the noise characteristics of GPS position time series. We first use an AR(1) model to whiten the original GPS position time series, then the STARS method is applied to detect the offsets. Simulated and real examples show that the COL-STARS algorithm can reduce the ratio of miss-identification of the offsets somewhat, and can be used for offset detection and correction. The impact of parameters setting and filtering on the offsets detection is also discussed.