Efficiency of Contextual Information in Processing of Interferometric Data Stacks

Among available methods for geodetic measurements, synthetic aperture radar (SAR) interferometry (InSAR) has been considered as a powerful tool for the monitoring of earth's surface, digital elevation model generation and possible slow temporal deformation mapping. In this context, multi-baseline SAR interferometry with the availability of multiple interferograms obtained from multi-pass satellite observations significantly improves the accuracy of the estimated target's parameters, i.e. the residual height and the mean deformation velocity. In this paper contextual spatial information has been exploited as a regularization term in order to improve the capability of multibaseline SAR Interferometry in dealing with possible artifacts and outliers induced by temporal decorrelation and remained atmospheric phase noise effects which can impair the accuracy of estimated target's parameters. The superiority of regularized processing is related to depletion of velocity variations over the scene and reducing ambiguity in parameter estimation. The proposed method is evaluated using a simulated and a real data set acquired by COSMO-SkyMed sensor over Tehran, Iran; and the results are compared with conventional adapted approach in the literature. The evaluation indicated that adaptation of contextual information can significantly improve the interferometric-based parameter estimation over partially coherent targets which are affected by outliers and artifacts.