Imperial College London
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ProfessorMartinSiegert

Faculty of Natural Sciences, The Grantham Institute for Climate Change

Visiting Professor
 
 
 
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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:2020,
author = {Wang, B and Sun, B and Jiaxin, W and Greenbaum, J and Jingxue, G and Laura, L and Xiangbin, C and Young, D and Blankenship, D and Siegert, M},
journal = {Annals of Glaciology},
pages = {124--134},
title = {Removal of ‘strip noise’ in airborne radio-echo sounding data using combined wavelet and 2D DFT filtering},
url = {http://hdl.handle.net/10044/1/67974},
volume = {61},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 measurementand 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 2D Fourier filtering. First, we implement discrete  wavelet  decomposition  on  RES  data  to  obtain  multi-scale  wavelet  components.  Then,  2D  DFT  spectral analysis  is  performed  on  components  containing  the  noise.  In  the  Fourier  domain,  the  2D  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 drastically improving the general quality of radar data.
AU  - Wang,B
AU  - Sun,B
AU  - Jiaxin,W
AU  - Greenbaum,J
AU  - Jingxue,G
AU  - Laura,L
AU  - Xiangbin,C
AU  - Young,D
AU  - Blankenship,D
AU  - Siegert,M
EP  - 134
PY  - 2020///
SN  - 0260-3055
SP  - 124
TI  - Removal of ‘strip noise’ in airborne radio-echo sounding data using combined wavelet and 2D DFT filtering
T2  - Annals of Glaciology
UR  - http://hdl.handle.net/10044/1/67974
VL  - 61
ER  -
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