학술논문

Autofocus-Based Estimation of Penetration Depth and Permittivity of Ice Volumes and Snow Using Single SAR Images
Document Type
Periodical
Source
IEEE Transactions on Geoscience and Remote Sensing IEEE Trans. Geosci. Remote Sensing Geoscience and Remote Sensing, IEEE Transactions on. 60:1-15 2022
Subject
Geoscience
Signal Processing and Analysis
Ice
Permittivity
Synthetic aperture radar
Radar
Spaceborne radar
Scattering
Radar imaging
Autofocus
cryosphere
depth
glacier
penetration
permittivity
synthetic aperture radar (SAR)
tomography
Language
ISSN
0196-2892
1558-0644
Abstract
An intrinsic challenge in the geophysical interpretation of low-frequency synthetic aperture radar (SAR) imagery of semitransparent media, such as ice sheets, is the position ambiguity of the scattering structures within the glacial volume. Commonly tackled by applying interferometric and tomographic techniques, their spaceborne implementation exhibits by orders higher complexity compared to missions relying on single SAR images, making them cost expensive or, in the context of planetary missions, even impossible due to limited navigation capability. Besides, even these sophisticated techniques are commonly biased due to inaccurate permittivity estimates, leading to geometric distortions up to several meters. We present a novel inversion procedure to estimate volume parameters of ice sheets, namely, the depth of the scattering layer within the glacial volume and the dielectric permittivity of the ice, based on single-image single-polarization SAR acquisitions. The information is inherent in the processed SAR data as phase errors on the azimuth signals resulting from uncompensated nonlinear propagation of the radar echoes through ice. We suggest a local map-drift autofocus approach to quantify and spatially resolve the phase errors and an inversion model to relate them to the penetration depth and permittivity. Testing the proposed technique using P-band SAR data acquired using DLR’s airborne sensor F-SAR during the ARCTIC15 campaign in Greenland shows promising results and good agreement with tomographic products of the analyzed test site.