Estimation Method and Correlation Analysis for Noise in GPS Coordinate Time Series

This paper firstly compares and analyzes the effect of maximum like lihood estimation (MLE) and least square variance estimation (LS-VCE) and minimum norm quadratic unbiased estimation (MINQUE) in the variance component estimation of GPS coordinate time series noise. After determining the minimum norm of two unbiased estimation method for the optimal estimation of noise variance, the correlations between the noises in each direction are analyzed by means of unitary linear regression, and the linear regression equations are determined.Experimental results show that, compared with the least squares variance component estimation method and maximum likelihood estimation method, MINQUE has a better estimation effect for the noise variances of GPS coordinate time series.In addition, the influence of noise on the estimation of motion parameters of the station can be reduced by using long span time series.Moreover, the same kind of noise in GPS coordinate time series of each direction has more significant correlation and the correlation between flicker noise in north and other directional flicker noises are better than that of white noises. The 40%-60% of the variance of the vertical noise can be explained by the noise variance in the horizontal direction, and north noise variance can explain the 60%-80% of change of the noise variance in east.The obtained linear regression equation has practical value.