Abstract:In this paper, we introduce a data-driven RegEM algorithm into GPS coordinate time series. The interpolation effects and performances of RegEM and Lagrange method, cubic spline method and orthogonal polynomial method are compared by simulating continuous missing data of different proportions and measuring missing data respectively. The experimental results show that RegEM interpolation is superior to traditional interpolation methods in simulating continuous missing data with different proportions, and the best result is obtained in the case of continuous missing data. RegEM interpolation method has the best effect in maximizing the retention variance of the sequence with missing data, which is about 1.17 times that of orthogonal polynomial method and 1.38 times that of cubic spline method.
WANG Fangchao,LU Zhiping,LU Hao et al. Application Analysis of GPS Coordinate Time Series Interpolation Based on RegEM Algorithm[J]. jgg, 2020, 40(1): 45-50.