An iterative Goldstein SAR interferogram filter

Abstract

This article presents a new modified Goldstein synthetic aperture radar (SAR) interferogram filter algorithm, named the iterative Goldstein filter. The main idea of this approach is to iteratively filter the SAR interferogram, by determining the filtering parameter alpha adaptively with respect to the pseudo-correlation value of the original and/or last filtered interferograms several times. The filter can be stopped automatically by pre-setting the threshold of mean value and the improvement of pseudo-correlation in given filter windows. Experimental results with both a simulated digital elevation model (DEM) interferogram and real SAR deformation interferogram show an improvement in the new algorithm results compared with those using the Goldstein filter, and its enhanced version, the Baran filter. In addition, from a pseudo-correlation map of the iteratively filtered interferogram, some valuable information can also be abstracted based on the signal residues.