Imperial College London

ProfessorMartinSiegert

Faculty of Natural SciencesThe Grantham Institute for Climate Change

Co-Director,Grantham Institute forClimate Change&Environment
 
 
 
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Contact

 

+44 (0)20 7594 9666m.siegert Website

 
 
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Assistant

 

Ms Gosia Gayer +44 (0)20 7594 9666

 
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Location

 

Grantham Directors OfficeSherfield BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Wang:2019:10.1017/aog.2019.4,
author = {Wang, B and Sun, B and Wang, J and Greenbaum, J and Guo, J and Lindzey, L and Cui, X and Young, DA and Blankenship, DD and Siegert, MJ},
doi = {10.1017/aog.2019.4},
journal = {Annals of Glaciology},
title = {Removal of 'strip noise' in radio-echo sounding data using combined wavelet and 2-D DFT filtering},
url = {http://dx.doi.org/10.1017/aog.2019.4},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - © 2019 The Author(s). 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.
AU - Wang,B
AU - Sun,B
AU - Wang,J
AU - Greenbaum,J
AU - Guo,J
AU - Lindzey,L
AU - Cui,X
AU - Young,DA
AU - Blankenship,DD
AU - Siegert,MJ
DO - 10.1017/aog.2019.4
PY - 2019///
SN - 0260-3055
TI - Removal of 'strip noise' in radio-echo sounding data using combined wavelet and 2-D DFT filtering
T2 - Annals of Glaciology
UR - http://dx.doi.org/10.1017/aog.2019.4
UR - http://hdl.handle.net/10044/1/67974
ER -