Research on common mode error extraction of European GNSS coordinate time series
Aiming at the problem that the common mode error (CME)of GNSS coordinate time series in large-scale regions is harshly defined and difficult to be extracted,the independent component analysis(ICA) was adopted to extract the CME of GNSS coordinate time series in Europe from 2015 to 2021 in a subregion and compared it with that extracted in Europe as a whole in this paper,to study the reasonable method of CME extraction in large-scale regions,the period of CME information and its effect on the velocity field.Europe was divided into four sub-regions,and CMEs were extracted for the whole and sub-regions respectively,and power spectrum analysis was performed to study their effects on the velocity field in the European region.The results showed that the effect of extracting CME in subregions was larger than that of the overall CME,the average reduction rate of root mean square (RMS)was less than 2％ and the average reduction rate of uncertainty of speed was less than 6％ after the overall exclusion of CMEs,while the reduction rate of RMS after the exclusion of CMEs in subregions could be up to 27％,and the average reduction rate of uncertainty of speed was all higher than 10％;moreover,the information of the CME cycle extracted in subregions was richer,which showed that the CME in Europe was dominated by 426.17 d and 319.63 d cycle signals.
GNSS coordinate time seriesindependent component analysiscommon-mode errorsvelocity fieldpower spectrum analysis
万方数据
维普
