Multi-Model Joint Atmospheric Correction for Widearea InSAR Surface Deformation Monitoring

With the rapid development of society and the advancement of urbanization, surface deformation monitoring has become increasingly important. InSAR (Interferometric Synthetic Aperture Radar) technology, with its advantages of high precision, all-weather, all-day capabilities, and wide-area observation, has become an ideal means for surface deformation monitoring. However, the application of InSAR technology is severely affected by atmospheric delay errors. Most existing atmospheric error correction methods are proposed for smallscale areas and struggle to accommodate various atmospheric error components simultaneously under wide-area conditions. Moreover, correction methods that rely on external data are inefficient. Therefore, this paper focuses on atmospheric errors in wide-area InSAR surface deformation monitoring and proposes a multi-model joint atmospheric correction method. Firstly, a linear function model is used to remove atmospheric errors related to topography in the interferometric phase. Then, spatiotemporal filtering is employed to eliminate the effects of atmospheric turbulence. Finally, residual atmospheric errors are corrected through quadratic polynomial fitting and temporal averaging. Experimental results show that the multi-model joint method significantly improves correction, with no discontinuities at the boundaries of data frames, enhancing deformation monitoring accuracy.