Improving the accuracy of local frequency estimation for interferometric synthetic aperture radar interferogram noise filtering considering large coregistration errors. Issue 6 (1st July 2014)

• Record Type: Journal Article
• Authors: Guo, Jiao; Zhang, Weitao; Liu, Yanyang; Fu, Longsheng
• Is Part Of: IET radar, sonar & navigation. Volume 8:Issue 6(2014)
• Page Start: 676
• Page End: 684
• Publication Date: 2014-07-01
• Subjects: synthetic aperture radar -- radar interferometry -- frequency estimation -- image denoising -- image registration -- vectors; ERS‐1‐2 data -- noise subspaces -- signal subspaces -- pixel vector -- InSAR phase image -- coregistration errors -- interferometric synthetic aperture radar interferogram noise filtering -- local frequency estimation accuracy; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2013.0202
• Languages: English
• ISSNs: 1751-8784

Abstract

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.