Improving the accuracy of local frequency estimation for interferometric synthetic aperture radar interferogram noise filtering considering large coregistration errors

Abstract

This study deals with the problem of estimating the local frequencies for interferometric synthetic aperture radar (InSAR) phase image (i.e. interferogram) noise filtering considering large coregistration errors. The estimation of local frequencies is frequently applied to achieving high performance of interferometric phase noise filtering, which is a key step in InSAR processing procedures. Unfortunately, the generated interferograms suffer seriously from coregistration errors especially for complicated topographies, thus imposing strong limits on the accuracy of local frequencies estimation by the existing methods. Taking large coregistration errors into account, the proposed method makes full use of the neighbouring pixels to construct joint pixel vector and take the separation extent of the signal and noise subspaces as the criterion to accurately estimate the local frequencies so that the effects of the envelope misalignment can be mitigated. Theoretical analysis and the simulated data as well as the real ERS-1/2 data show that the presented method has the ability to provide accurate estimation of local frequencies even if the coregistration error reaches one pixel.

Noise Reduction of High-Resolution SAR Image over Vegetation and Urban Areas

“…Jiao Guo et.al. [2] "Improving the accuracy of local frequency evaluation for interferometric synthetic aperture radar interferogram noise filtering considering large co-registration inaccuracy" In this an inventive technique to estimate the local frequencies of interferogram considering large coregistration error has been presented. Based on the construction of the joint pixel vector and the covariance matrix, the proposed method adopts the separation extent of the signal and noise subspaces as the criteria, optimized to determine the estimates of local frequencies.…”