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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Cambridge University Press
2020
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Online Access: | https://doi.org/10.1017/aog.2019.4 https://doaj.org/article/1bf237a1e8dd4fad90b1c9f187ea8e8a |
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ftdoajarticles:oai:doaj.org/article:1bf237a1e8dd4fad90b1c9f187ea8e8a 2023-05-15T13:29:35+02:00 Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering Bangbing Wang Bo Sun Jiaxin Wang Jamin Greenbaum Jingxue Guo Laura Lindzey Xiangbin Cui Duncan A. Young Donald D. Blankenship Martin J. Siegert 2020-04-01T00:00:00Z https://doi.org/10.1017/aog.2019.4 https://doaj.org/article/1bf237a1e8dd4fad90b1c9f187ea8e8a EN eng Cambridge University Press https://www.cambridge.org/core/product/identifier/S0260305519000041/type/journal_article https://doaj.org/toc/0260-3055 https://doaj.org/toc/1727-5644 doi:10.1017/aog.2019.4 0260-3055 1727-5644 https://doaj.org/article/1bf237a1e8dd4fad90b1c9f187ea8e8a Annals of Glaciology, Vol 61, Pp 124-134 (2020) glaciological instruments and methods radio-echo sounding subglacial exploration geophysics subglacial processes Meteorology. Climatology QC851-999 article 2020 ftdoajarticles https://doi.org/10.1017/aog.2019.4 2023-03-12T01:31:55Z 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. Article in Journal/Newspaper Annals of Glaciology Ice Sheet Directory of Open Access Journals: DOAJ Articles Annals of Glaciology 61 81 124 134 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
glaciological instruments and methods radio-echo sounding subglacial exploration geophysics subglacial processes Meteorology. Climatology QC851-999 |
spellingShingle |
glaciological instruments and methods radio-echo sounding subglacial exploration geophysics subglacial processes Meteorology. Climatology QC851-999 Bangbing Wang Bo Sun Jiaxin Wang Jamin Greenbaum Jingxue Guo Laura Lindzey Xiangbin Cui Duncan A. Young Donald D. Blankenship Martin J. Siegert Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering |
topic_facet |
glaciological instruments and methods radio-echo sounding subglacial exploration geophysics subglacial processes Meteorology. Climatology QC851-999 |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Bangbing Wang Bo Sun Jiaxin Wang Jamin Greenbaum Jingxue Guo Laura Lindzey Xiangbin Cui Duncan A. Young Donald D. Blankenship Martin J. Siegert |
author_facet |
Bangbing Wang Bo Sun Jiaxin Wang Jamin Greenbaum Jingxue Guo Laura Lindzey Xiangbin Cui Duncan A. Young Donald D. Blankenship Martin J. Siegert |
author_sort |
Bangbing Wang |
title |
Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering |
title_short |
Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering |
title_full |
Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering |
title_fullStr |
Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering |
title_full_unstemmed |
Removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-D DFT filtering |
title_sort |
removal of ‘strip noise’ in radio-echo sounding data using combined wavelet and 2-d dft filtering |
publisher |
Cambridge University Press |
publishDate |
2020 |
url |
https://doi.org/10.1017/aog.2019.4 https://doaj.org/article/1bf237a1e8dd4fad90b1c9f187ea8e8a |
genre |
Annals of Glaciology Ice Sheet |
genre_facet |
Annals of Glaciology Ice Sheet |
op_source |
Annals of Glaciology, Vol 61, Pp 124-134 (2020) |
op_relation |
https://www.cambridge.org/core/product/identifier/S0260305519000041/type/journal_article https://doaj.org/toc/0260-3055 https://doaj.org/toc/1727-5644 doi:10.1017/aog.2019.4 0260-3055 1727-5644 https://doaj.org/article/1bf237a1e8dd4fad90b1c9f187ea8e8a |
op_doi |
https://doi.org/10.1017/aog.2019.4 |
container_title |
Annals of Glaciology |
container_volume |
61 |
container_issue |
81 |
container_start_page |
124 |
op_container_end_page |
134 |
_version_ |
1766001375277219840 |