Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering

Radio-echo sounding (RES) can be used to understand ice-sheet processes, englacial flow structures and bed properties, making it one of the most popular tools in glaciological exploration. However, RES data are often subject to ‘strip noise’, caused by internal instrument noise and interference, and...

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Bibliographic Details
Published in:Annals of Glaciology
Main Authors: Bangbing Wang, Bo Sun, Jiaxin Wang, Jamin Greenbaum, Jingxue Guo, Laura Lindzey, Xiangbin Cui, Duncan A. Young, Donald D. Blankenship, Martin J. Siegert
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press 2020
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Online Access:https://doi.org/10.1017/aog.2019.4
https://doaj.org/article/1bf237a1e8dd4fad90b1c9f187ea8e8a
Description
Summary:Radio-echo sounding (RES) can be used to understand ice-sheet processes, englacial flow structures and bed properties, making it one of the most popular tools in glaciological exploration. However, RES data are often subject to ‘strip noise’, caused by internal instrument noise and interference, and/or external environmental interference, which can hamper measurement and interpretation. For example, strip noise can result in reduced power from the bed, affecting the quality of ice thickness measurements and the characterization of subglacial conditions. Here, we present a method for removing strip noise based on combined wavelet and two-dimensional (2-D) Fourier filtering. First, we implement discrete wavelet decomposition on RES data to obtain multi-scale wavelet components. Then, 2-D discrete Fourier transform (DFT) spectral analysis is performed on components containing the noise. In the Fourier domain, the 2-D DFT spectrum of strip noise keeps its linear features and can be removed with a ‘targeted masking’ operation. Finally, inverse wavelet transforms are performed on all wavelet components, including strip-removed components, to restore the data with enhanced fidelity. Model tests and field-data processing demonstrate the method removes strip noise well and, incidentally, can remove the strong first reflector from the ice surface, thus improving the general quality of radar data.