联合环境负荷改正与VBPCA滤波的香港GNSS三维速度场构建OA

To improve the estimation accuracy of the three-dimensional velocity field derived from GNSS coordinate time series,this paper proposes a data processing strategy combining global environ-mental load model correction with variational Bayesian principal component analysis(VBPCA)filter-ing.Firstly,based on the atmospheric,hydrological,and non-tidal ocean load models provided by the German Research Centre for Geosciences(GFZ),environmental load correction is performed on the original coordinate time series of 17 GNSS stations in the Hong Kong region.The results show that environmental load correction can effectively reduce the root mean square(RMS)values of the vertical(U)time series with an average reduction of approximately 20%and weaken the spatial correlation between stations.However,such correction leads to an increase in the RMS values and spatial correla-tion of the horizontal north(N)and east(E)time series.Secondly,the VBPCA algorithm which does not require missing data interpolation is adopted to filter and eliminate the common-mode errors of the corrected coordinate time series.After VBPCA filtering,the RMS values in the N,E,and U direc-tions are reduced by approximately 20%,13%,and 18%,respectively.After the joint processing of environmental load correction and VBPCA filtering,the velocity uncertainties in the N,E,and U direc-tions are averagely reduced by about 63%,47%,and 68%,respectively.The calculated results based on the ITRF2020 international terrestrial reference frame indicate that the average horizontal crustal movement rate of the GNSS stations in the study area is 34.6±0.2 mm/a with a dominant movement direction of N109.5°E.The vertical movement presents a slow uplift trend,while local subsidence occurs in partial areas.This study provides an effective approach for the construction of high-precision GNSS velocity fields in regions affected by significant environmental load effects and data missing.