Abstract:To solve the problem that the data interpolating empirical orthogonal functions(DINEOF) in GNSS coordinate time series interpolation are affected by low correlation sites and poor interpolation effect of continuous long vacancies, we propose the coefficent data interpolating empirical orthogonal functions(CDINEOF) method. Firstly, we calculate the correlation between the target site data and its surrounding site data, then filter out the site data with higher correlation to construct the observation matrix, and finally use DINEOF to interpolate the missing data in the observation matrix. Experiments are conducted to verify the feasibility of the new method by simulated and actual data, and the results are compared and analyzed with those of DINEOF method and polynomial interpolation method. The experimental results of simulated data show that the interpolation effect of CDINEOF method is better than that of DINEOF method and polynomial interpolation method when there are continuous long vacancies in the observed data; the experimental results of measured data show that CDINEOF method is the best in maximizing the retained variance, and the maximum variance is improved by 11.8% and 6.7% based on DINEOF method and polynomial interpolation method, respectively.