Compressed SAR Interferometry in the Big Data Era

Modern Synthetic Aperture Radar (SAR) missions provide an unprecedented massive interferometric SAR (InSAR) time series. The processing of the Big InSAR Data is challenging for long-term monitoring. Indeed, as most deformation phenomena develop slowly, a strategy scheme can be worked on reduced volume data sets. This paper introduces novel ComSAR algorithm based compression technique reducing computational efforts while maintaining performance robustly. divides into many mini-stacks and then compresses them. compressed estimator close to theoretical Cramer–Rao lower bound under realistic C-band Sentinel-1 decorrelation scenario. Both persistent distributed scatterers (PSDS) are exploited in algorithm. validated via simulation application map land subsidence salt mine Vauvert area, France. proposed yields consistently better when compared with state-of-the-art PSDS technique. We make our algorithms open-source TomoSAR package. To it more practical, we exploit other projects so that people apply methods end-to-end chain. knowledge, first public domain tool available jointly handle PS DS targets.