The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals
<p>The grounded electrical source airborne transient electromagnetic (GREATEM) system is an important method for obtaining subsurface conductivity distribution as well as outstanding detection efficiency and easy flight control. However, there are the superposition of desired signals and vario...
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doaj-9823d854526e4b55a44ecce7f1c1653c2020-11-25T04:09:01ZengCopernicus PublicationsGeoscientific Instrumentation, Methods and Data Systems2193-08562193-08642020-11-01944345010.5194/gi-9-443-2020The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signalsY. Li0S. Gao1S. Gao2S. Zhang3S. Zhang4H. He5P. Xian6C. Yuan7College of Geophysics, Chengdu University of Technology, Chengdu, 610059, ChinaKey Laboratory of Earth Exploration and Information Techniques of Ministry of Education, Chengdu, 610059, ChinaCollege of Information Science and Technology, Chengdu University of Technology, Chengdu, 610059, ChinaCollege of Geophysics, Chengdu University of Technology, Chengdu, 610059, ChinaKey Laboratory of Earth Exploration and Information Techniques of Ministry of Education, Chengdu, 610059, ChinaCollege of Information Science and Technology, Chengdu University of Technology, Chengdu, 610059, ChinaCollege of Information Science and Technology, Chengdu University of Technology, Chengdu, 610059, ChinaCollege of Information Science and Technology, Chengdu University of Technology, Chengdu, 610059, China<p>The grounded electrical source airborne transient electromagnetic (GREATEM) system is an important method for obtaining subsurface conductivity distribution as well as outstanding detection efficiency and easy flight control. However, there are the superposition of desired signals and various noises for the GREATEM signal. The baseline wander caused by the receiving coil motion always exists in the process of data acquisition and affects measurement results. The baseline wander is one of the main noise sources, which has its own characteristics such as being low frequency, large amplitude, non-periodic, and non-stationary and so on. Consequently, it is important to correct the GREATEM signal for an inversion explanation. In this paper, we propose improving the method of ensemble empirical mode decomposition (EEMD) by adaptive filtering (EEMD-AF) based on EEMD to suppress baseline wander. Firstly, the EEMD-AF method will decompose the electromagnetic signal into multi-stage intrinsic mode function (IMF) components. Subsequently, the adaptive filter will process higher-index IMF components containing the baseline wander. Lastly, the de-noised signal will be reconstructed. To examine the performance of our introduced method, we processed the simulated and field signal containing the baseline wander by different methods. Through the evaluation of the signal-to-noise ratio (SNR) and mean-square error (MSE), the result indicates that the signal using the EEMD-AF method can get a higher SNR and lower MSE. Comparing correctional data using the EEMD-AF and the wavelet-based method in the anomaly curve profile images of the response signal, it is proved that the EEMD-AF method is practical and effective for the suppression of the baseline wander in the GREATEM signal.</p>https://gi.copernicus.org/articles/9/443/2020/gi-9-443-2020.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Y. Li S. Gao S. Gao S. Zhang S. Zhang H. He P. Xian C. Yuan |
spellingShingle |
Y. Li S. Gao S. Gao S. Zhang S. Zhang H. He P. Xian C. Yuan The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals Geoscientific Instrumentation, Methods and Data Systems |
author_facet |
Y. Li S. Gao S. Gao S. Zhang S. Zhang H. He P. Xian C. Yuan |
author_sort |
Y. Li |
title |
The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals |
title_short |
The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals |
title_full |
The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals |
title_fullStr |
The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals |
title_full_unstemmed |
The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals |
title_sort |
baseline wander correction based on the improved ensemble empirical mode decomposition (eemd) algorithm for grounded electrical source airborne transient electromagnetic signals |
publisher |
Copernicus Publications |
series |
Geoscientific Instrumentation, Methods and Data Systems |
issn |
2193-0856 2193-0864 |
publishDate |
2020-11-01 |
description |
<p>The grounded electrical source airborne transient
electromagnetic (GREATEM) system is an important method for obtaining
subsurface conductivity distribution as well as outstanding detection
efficiency and easy flight control. However, there are the superposition of
desired signals and various noises for the GREATEM signal. The baseline wander
caused by the receiving coil motion always exists in the process of data
acquisition and affects measurement results. The baseline wander is one of
the main noise sources, which has its own characteristics such as being low frequency, large amplitude, non-periodic, and non-stationary and so on.
Consequently, it is important to correct the GREATEM signal for an inversion explanation. In this paper, we propose improving the method of ensemble empirical mode decomposition (EEMD) by adaptive
filtering (EEMD-AF) based on EEMD to
suppress baseline wander. Firstly, the EEMD-AF method will decompose the
electromagnetic signal into multi-stage intrinsic mode function (IMF)
components. Subsequently, the adaptive filter will process higher-index IMF
components containing the baseline wander. Lastly, the de-noised signal will
be reconstructed. To examine the performance of our introduced method, we
processed the simulated and field signal containing the baseline wander by
different methods. Through the evaluation of the signal-to-noise ratio (SNR)
and mean-square error (MSE), the result indicates that the signal using
the EEMD-AF method can get a higher SNR and lower MSE. Comparing correctional data
using the EEMD-AF and the wavelet-based method in the anomaly curve profile
images of the response signal, it is proved that the EEMD-AF method is practical and effective for the suppression of the baseline wander in
the GREATEM signal.</p> |
url |
https://gi.copernicus.org/articles/9/443/2020/gi-9-443-2020.pdf |
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