一种大尺度区域GNSS坐标时间序列自适应时空滤波方法OA北大核心CSTPCD

We proposed an adaptive spatiotemporal filtering method for GNSS coordinate time series,which dynamically subdivides the filtering region into several subregions,facilitating the extraction and elimination of common mode errors under specified thresholds.We conduct a case study on 184 vertical GNSS coordinate time series from CMONOC.The results of three groups of randomized experiments show that the average RMS values of the station sequences after adaptive PCA spatiotemporal filtering are reduced by about 39.7％,38.4％,and 39.7％on average compared with that before the filtering,and the filtering effect is better than that of the overall PCA spatiotemporal filtering method.Analysis of pre-and post-filtering site noise charac-teristics reveals that,compared to traditional PCA filtering,our method resulted in an additional attenuation of approximately 17.8％in power-law noise amplitudes within site residual time series.