Interferometric Synthetic Aperture Radar Statistical Inference in Deformation Measurement and Geophysical Inversion: A review

With the rapid advancements in synthetic aperture radar (SAR) satellites and associated processing algorithms over recent decades, interferometric SAR (InSAR) has emerged as a routine method for monitoring large-scale ground deformation and interpreting geophysical processes. Statistical inference serves as a major component in InSAR technique developments and applications. This article provides an overview of InSAR deformation measurement and InSAR-constrained geophysical inversion, using a statistical inference point of view. Its objectives are to facilitate understanding of the method by addressing its underlying mathematical challenges. We begin by introducing the concept of statistical inference and the structure of our content organization framework. Next, we investigate the distinct concerns associated with statistical inference in InSAR deformation measurement and InSAR-constrained geophysical inversion. Finally, we propose several significant directions for future research.
Table 1
includes abbreviations used throughout this article. Additionally, we highlight relevant resources, such as mathematical background, open source codes, and data repositories, in an appendix, which is available as supplementary material at
https://doi.org/10.1109/MGRS.2023.3344159
.