.png){kind=icon}
Return
Cheap, Valid Regularizers for Improved Interferometric Phase Linking
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2022.3197423.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
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.
Keywords:
Coherence
History
Dispersion
Estimation
Eigenvalues and eigenfunctions
Decorrelation
Snow
Radar interferometry
synthetic aperture radar (SAR)
Journal
IF:
16.4
Papers:
1.0W
Citations:
5.1K
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveMathematical Framework for Phase-Triangulation Algorithms in Distributed-Scatterer Interferometry
PREAI
ShareSaveShareSave
View more