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SPECTRAL ALGORITHMS EFFICIENCY FOR INSAR PHASE NOISE SUPPRESSION
Abstract
Interferometric data processing (InSAR) for extraction of information about the Earth terrain heights is one of the general guidelines in development of contemporary space-based radar systems. The InSAR processing for building the digital elevation models (DEM) and terrain displacement maps includes a phase noise suppression step, which is usually performed by different image filters, as well as spectral and adaptive spectral filters (mean/boxcar, spectral domain filtration with different window functions, Wiener, Goldstein, etc.), and an analysis of filtration algorithms efficiency is one of important issues of InSAR processing. For ALOS PALSAR data, different phase noise filters were researched, and the processing results were compared with the ground control data reprojected into the radar coordinate system. It is shown, that the gaussian spectral filter with some definite parameters shows the best results in the phase noise suppression, and a dependence of filter parameters on interferogram spectral characteristics was obtained.
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