Study on the Effect of PCA Spatial Filtering on High-rate GPS Positioning

In recent years,monitoring strong ground movement based on high-rate GPS continuous observing network has become a research focus in geo-scientific field.The spatial filtering we used is the principal component analysis(PCA) to extract the CME from the high-rate GPS position time series,and the Karhunen-Loeve expansion(KLE) is used to test the components.We process the high rate data from Sichuan GPS Continuous Observing Network,the results show that this method can eliminate the CME effectively,and the accuracy is slightly higher than the stacking.The key is that the spatial response of CME can be showed accurately by PCA,which is meaningful for applications and developments of the high rate GPS technology.