Covariance fitting based InSAR Phase Linking

Abstract

This paper proposes an algorithm for phase differences estimation in multi-temporal InSAR. The proposed approach is based on covariance fitting estimation and the majorization-minimization algorithm. Experiments with Sentinel-1 images of Mexico City demonstrate that the proposed approach compares favorably to the state-of-the-art phase linking (i.e., maximum likelihood-based approaches) when the sample support is low (i.e., when the number of pixels in the multi-look window cannot scale with the number of SAR images). Hence, the proposed approach can improve the spatial resolution of phase difference estimation in case of large SAR image time series.