Application of PCA/KLE in analysis of regional GPS coordinate time series

For Common Mode Error(CME)existed in the regional GPS coordinate time series,it is usually removed by stacking spatial filtering which assumes that CME be invariable in the airspace field.While Principal Component Analysis(PCA)and Karhunen-Loeve Expansion methods(KLE)decompose the network time series into a set of principal components over the time and a characteristic component in the space domain,without limiting the intrinsic characteristic of CME.Therefore,this paper attempted to do the spatial filtering for a regional GPS coordinate time series via PCA and KLE.Some discussion was made for a continuous GPS monitoring network on the Carrizo Plain,California,USA,and the result showed that PCA/KLE method could extract the CME effectively,improve the accuracy of site coordinates and enhance the robustness of the spatial filtering.