Estimation of terrain's linear deformation rates using synthetic aperture radar systems

Synthetic Aperture Radars (SAR) are currently one of the most popular systems in the remote sensing domain, being widely utilized in the earth observation field. Their range of applicability extends in both marine and terrestrial regions. In the maritime domain, SAR systems are intensively used for the study of oceanic waves, waves breaking, marine currents, underwater topography, oil stains, for monitoring the glacier's ice flow, and also for ships detection and localization. In the land areas, a class of applications which exploits the coherence propriety of SAR signals is able to retrieve information related to terrain's characteristics, like topography and displacements. In this work, a processing chain for linear deformation rates estimation is presented and implemented on a dataset of 30 SAR images of Buzau and Foc.ani cities regions (Romania). The algorithm is based on identification of targets with stable electromagnetic response, exploiting their temporal coherence to obtain reliable estimates. An iterative phase regression analysis is conducted exclusively in the set of detected stable targets. The main challenge is represented by the estimation of the residual component of the phase, due to its random nature. Main feature of the proposed processing chain consists in the fact that it includes a step for terrain's topography estimation, instead of using an external digital elevation model.