Unwrapping-free interpolation of sparse DInSAR phase data: experimental validation

Abstract

ABSTRACTIn multi-temporal applications of synthetic aperture radar (SAR) interferometry, differential phase contributions due to atmospheric inhomogeneities, estimated over sparse points, have to be interpolated and removed from the regular-grid interferograms in order to highlight the phase stability of more image pixels, which then add to the available data to infer useful information about terrain displacements or other phenomena of interest. Interpolation is usually done on the phase data after a phase unwrapping (PU) operation. In a previous work, we considered the alternative interpolation step applied directly to the complex phasor derived from the wrapped phase, thus bypassing the error-prone sparse PU operation. In this article, the performances of the proposed methodology are evaluated over atmospheric phase screen (APS) data estimated from a previous processing through persistent scatterers interferometry (PSI) methods. The original persistent scatterer (PS) population is reduced by thresholding their inter-image coherence values, and then further subsampled randomly in a rectangle inside a detected subsidence bowl. Both the classical and the proposed interpolation procedures are applied to the subsampled APS phase values. The interpolated fields are then removed from the rest of the PS, and the residual phase values are compared in terms of inter-image coherence. Results confirm that interpolating complex phasors, thus avoiding PU, gives results equivalent to the standard procedure in good sampling conditions. Moreover, when point sparsity induces phase aliasing, thus hindering the PU operation, the proposed method allows to better recover phase information over unsampled pixels, improving the final results of the PSI processing.