A New Decorrelation Phase Covariance Model for Noise Reduction in Unwrapped Interferometric Phase Stacks

The accuracy of geophysical parameter estimation made with interferometric synthetic aperture radar (InSAR) time-series techniques can be improved rapidly increasing available data volumes and the development noise covariance matrices applicable to joint analysis networks interferograms. In this article, we present a new decorrelation phase model discuss its role in reduction unwrapped stacks. We demonstrate an example which average interferogram stacks that span over transient event how aid reduction. Our suggests that, for decorrelating surfaces (i.e., much shorter correlation time than SAR acquisition intervals), it is preferable incorporate all interferograms from long observation windows. For slowly longer our small subset pairs sufficient. validate three existing models both Cascadia, region heavy vegetation cover, Death Valley, desert C-band Sentinel-1 A observations. proposed matches observations smallest discrepancy between theory