A GENERALIZED-SVD-BASED TECHNIQUE FOR ENHANCING PERFORMANCE OF MULTI-TEMPORAL DINSAR ANALYSES: THE WEIGHTED ADAPTIVE VARIABLE-LENGTH (WAVE) TECHNIQUE

This work is based on the use of weighted Least-squares (WLS) approaches for the generation of ground line-of-sight (LOS) displacement time-series through differential interferometric SAR methods. More precisely, in this paper, a WLS method that extends the usability of the Multi-Temporal InSAR (MT-InSAR) Small Baseline Subset (SBAS) algorithm in regions with medium-to-low coherence is presented. The proposed method relies on the adaptive selection and exploitation, pixel-by-pixel, of the medium-to-high coherent interferograms, such as to discard the noisy phase measurements. In such a way, for each pixel, it is possible to obtain several disjoined sets of interferograms, which are then connected by exploiting the weighted singular value decomposition (WSVD) method. As a consequence, the interferogram networks reduction may lead to rejecting some SAR acquisitions from the used dataset, this results in the generation of so called variable-length displacement time-series. The experimental results have been performed considering by applying the Weighted Adaptative Variable-lEngth (WAVE) technique to a dataset composed of 50 SAR images, gathered by the Italian Space Agency Cosmo-SkyMed (CSK) constellation sensors over the Basilicata region, Southern Italy.