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Cheap, Valid Regularizers for Improved Interferometric Phase Linking

delete2022-01-01
delete17
PRE
AI
Z
Zwieback, S. *
DOI:10.1109/LGRS.2022.3197423delete
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摘要

摘要

En 中文
Retrieving a consistent phase history from a multilooked Interferometric synthetic aperture radar (InSAR) stack depends critically on the accuracy of the (coherence) magnitude estimates. To estimate the magnitudes more reliably, the author proposes three regularization methods: Hadamard, spectral, and Hadamard-spectral regularization. All three are computationally cheap and parameterized such that they are guaranteed to yield valid magnitude matrices. These regularizers achieved relative improvements in the phase history with an accuracy of up to 40% in simulations. The improvements were greatest for low long-term coherences. All three methods performed similarly in the simulations and in a Sentinel-1 stack, for which the local phase dispersion decreased with regularization. Implementation of the regularizers into operational processing chains is expected to improve deformation and uncertainty estimates, especially for local movements over decorrelating terrain.
Keyword:
Coherence
History
Dispersion
Estimation
Eigenvalues and eigenfunctions
Decorrelation
Snow
Radar interferometry
synthetic aperture radar (SAR)

期刊

IEEE Geoscience and Remote Sensing Magazine 封面图
IEEE Geoscience and Remote Sensing Magazine
IF:
16.4
论文数:
1.0W
被引数:
5.1K

机构

University of Alaska System 封面图
University of Alaska System
学者数:
4.6K
论文数: 3.9K
被引数: 27
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