Extraction of Seasonal Signal of GPS Coordinate Time Series Using Atomic Norm Minimization
Baozhou Chen, Jiawen Bian, Hongwei Li, Lihua Fu, Zhihui Liu, Tong Zhou · 2020
Global positioning system (GPS) coordinate time series shows obvious seasonal oscillation, especially in the vertical direction. In order to separate tectonic movement from the other signals accurately and obtain reliable long-term movement trend, it is necessary to obtain accurate seasonal signal estimation. In this paper, seasonal signals in the GPS time series are modelled by time-varying sinusoidals, and the Atomic Norm Minimization (ANM) is used to extract the seasonal signals. To verify the efficiency of the proposed algorithm, a set of experiments is carried out on both the synthetic dataset and real GPS time series. The results of ANM are compared with the state-of-the-art methods under different noise levels. All the elicited results indicated that the ANM has certain advantages and can be used as an effective alternative way to extract the seasonal signals.