Closure-Based Correction of InSAR Phase Unwrapping Errors by Integrating Block-Wise Tikhonov Regularization and Flux Analysis

Interferometric synthetic aperture radar (InSAR) has proven to be a unique tool for investigating large-scale surface deformation. Although the applications of InSAR are widespread, especially following the deployment of the Sentinel-1A/B twin satellites, large-scale automatic InSAR processing is primarily limited by phase unwrapping for interferograms with low coherence and strong atmospheric artifact. Fixing phase unwrapping errors in steep relief and dense vegetation scenarios is challenging for the existing methods that rely on either redundant interferogram loops [e.g., linear absolute shrinkage and selection operator (LASSO)] or spatial connectivity of the unwrapped patches [e.g., flux analysis (FA)]. Here we develop a hybrid approach by integrating Tikhonov regularization (TR) and FA to automatically correct phase unwrapping errors, abbreviated as TR and FA corrector (TRAFAC). Our methodology involves three major steps. First, we identify phase unwrapping errors by analyzing phase closures. Second, we make a TR model to estimate phase unwrapping errors for pixels within multiple loops. Importantly, our approach departs from pixel-by-pixel inversion, opting instead to estimate an unknown for the entire block, ensuring uniform correction across all pixels within the block. For the remaining few blocks within isolated loops, we employ the FA algorithm as the third step. We test our approach using both synthetic and real data collected along the Longmenshan fault zone (LMSFZ) in Sichuan, China. The results show that our approach can successfully correct 95% of unwrapping errors in such a demanding scenario. Our TRAFAC approach is able to correct phase unwrapping errors in isolated loops and isolated patches, thereby can contribute to the reliability of automatic large-scale InSAR processing systems.