A Fast Atmospheric Correction Method of SBAS-InSAR based on Fixed Rank Kriging

Objectives: In the process of monitoring surface deformation using Interferometric Synthetic Aperture Radar (InSAR) technology, the atmospheric delay error constrains the accuracy of the deformation monitoring results. The traditional small baseline subsets InSAR (SBAS-InSAR) technology usually utilizes the statistical analysis of the interferometric phase-height relationship and spatio-temporal filtering to suppress the atmospheric effect, but the former only removes the vertically stratified atmosphere and ignores the effect of turbulent atmosphere, while the latter is highly subjective in the selection of the filtering window. On the other hand, the millions or even tens of millions of data points in SAR images bring a considerable burden to the calculation process. Methods: In order to improve the deformation monitoring accuracy of time-series InSAR technology and ensure efficient calculation efficiency, a SBAS-InSAR atmospheric rapid correction method based on Fixed Rank Kriging (FRK) and the interferogram itself is proposed. Starting from spatial correlation, a multi-scale spatial model is constructed to estimate the atmospheric random effects of the interferogram, and spatial dimensionality reduction is used to greatly improve the efficiency of atmospheric correction. Finally, a real experiment was conducted using 25 scenes of Sentinel-1 SAR images covering Datong City, Shanxi Province, to verify the effectiveness and performance of this method. Results: The results show that: (1) Compared with the deformation results obtained by traditional SBAS-InSAR, the root mean square error (RMSE) of this method is reduced by 48% on average; (2) The atmospheric estimation efficiency of the fixed-rank kriging method is 15 times higher than that of the ordinary kriging method with the same amount of data. Conclusions: The proposed method can significantly improve the deformation monitoring accuracy of the SBAS-InSAR technique without relying on external data, and greatly improve the efficiency of atmospheric correction.