Abstract: Abstract Based on the calculation of the coordinate time series of CORS network in China during the period from 1999 to 2009 base on the CGCS2000 frame, the paper proposes the adoption of spatial filtering algorithm based on principal component analysis (PCA) to extract the space-time characteristics of Common Mode Error (CME) in coordinate time series of CORS network in China base on the CGCS2000(Chinese geocentric 3D coordinate system). Secondly, the method of power spectrum analysis is applied to analyze the frequency spectrum characteristics of coordinate time series after spatial filtering and fitting, the noise characteristic of the residual coordinate time series are estimated quantitatively with the criterion of maximum likelihood estimation. Finally, it evaluates the annual speed evaluation and the actual accuracy of national CORS network under different color noise modes with the weight least squares method. The result shows the adoption of PCA method can promote the accuracy and reliability of CORS network base on the CGCS2000 frame, describes more precisely the movement characteristic of CORS network. The mean square error in the orientation of the north, the east and the height are reduced by 22%, 26% and 46% respectively after filtering. The white noise is not the main part of the noises in the coordinate time series of CORS network in China, while the white noise, flicker noise and random walk noise are the basic characteristics in the coordinate time series of CORS network, based on which can describe better the movement parameters of CORS network. The colored noise in CORS network is regular in the orientation of the horizon, the height, the North-South, the East-West. With the comparison of the consideration of the colored noise and the white noise, the change percentage of speed evaluation in CORS network is generally around 2%--10%, the error of the former is 2-6 times bigger than the latter.