Subglacial Radar Reflectivity Estimation Considering Volumetric Scattering Loss from Englacial Dielectric Inhomogeneities

To improve the accuracy of subglacial reflectivity estimation using ice-sounding radar, this study proposes a method that explicitly incorporates volumetric scattering loss caused by englacial dielectric inhomogeneities. Particle scattering from englacial dielectric inhomogeneities is accounted for using Rayleigh and Mie theory, with the applicable formulation selected according to the relationship between the characteristic size of the inhomogeneities and the radar wavelength. The resulting scattering loss is incorporated into the conventional propagation-loss model to obtain corrected basal reflectivity estimates. Main simulations of bedrock–subglacial water and bedrock–sediment transitions were conducted at a center frequency of 200 MHz using an effective scatterer radius of 0.2 mm and porosities of 0.5% and 0.8%. Supplementary simulations were further performed at 60 MHz, corresponding to the operating frequency of the airborne radar system used in the field experiments. Compared with the conventional attenuation-correction method, the proposed method produced reflectivity estimates closer to the prescribed reference values and reduced the RMSE by approximately 29.2–34.8%. The method was further validated using airborne radar data from Lake Snow Eagle, Lake Vostok, the Lambert Glacier Basin, and Dome A. At Lake Vostok, the absolute deviation from the reference value was reduced from 0.85 to 0.47 dB, while at Dome A it was reduced from 1.01 to 0.71 dB. These results demonstrate that explicitly accounting for volumetric scattering loss can reduce systematic reflectivity bias and improve the accuracy and reliability of subglacial water, sediment, and bedrock characterization.

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Publication Details

Journal
Remote Sensing
Published
2026-10-09
DOI
https://doi.org/10.3390/rs18203458
Primary Topic
Cryospheric studies and observations
Type
article
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article

Subglacial Radar Reflectivity Estimation Considering Volumetric Scattering Loss from Englacial Dielectric Inhomogeneities

Xiangbin Cui, Shinan Lang, Bo Sun, Ruixuan Jiang
Remote Sensing
Cryospheric studies and observations
article

Subglacial Radar Reflectivity Estimation Considering Volumetric Scattering Loss from Englacial Dielectric Inhomogeneities

Xiangbin Cui, Shinan Lang, Bo Sun, Ruixuan Jiang
article en

Abstract

To improve the accuracy of subglacial reflectivity estimation using ice-sounding radar, this study proposes a method that explicitly incorporates volumetric scattering loss caused by englacial dielectric inhomogeneities. Particle scattering from englacial dielectric inhomogeneities is accounted for using Rayleigh and Mie theory, with the applicable formulation selected according to the relationship between the characteristic size of the inhomogeneities and the radar wavelength. The resulting scattering loss is incorporated into the conventional propagation-loss model to obtain corrected basal reflectivity estimates. Main simulations of bedrock–subglacial water and bedrock–sediment transitions were conducted at a center frequency of 200 MHz using an effective scatterer radius of 0.2 mm and porosities of 0.5% and 0.8%. Supplementary simulations were further performed at 60 MHz, corresponding to the operating frequency of the airborne radar system used in the field experiments. Compared with the conventional attenuation-correction method, the proposed method produced reflectivity estimates closer to the prescribed reference values and reduced the RMSE by approximately 29.2–34.8%. The method was further validated using airborne radar data from Lake Snow Eagle, Lake Vostok, the Lambert Glacier Basin, and Dome A. At Lake Vostok, the absolute deviation from the reference value was reduced from 0.85 to 0.47 dB, while at Dome A it was reduced from 1.01 to 0.71 dB. These results demonstrate that explicitly accounting for volumetric scattering loss can reduce systematic reflectivity bias and improve the accuracy and reliability of subglacial water, sediment, and bedrock characterization.

Remote SensingVol. 18(20)
Polar Research Institute of China (CN), Zhejiang Ocean University (CN), Beijing University of Technology (CN)
Openalex Percentile: Top 19%
Cryospheric studies and observations
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