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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Main Authors: Y. Li, S. Gao, S. Zhang, H. He, P. Xian, C. Yuan
Format: Article
Language:English
Published: Copernicus Publications 2020-11-01
Series:Geoscientific Instrumentation, Methods and Data Systems
Online Access:https://gi.copernicus.org/articles/9/443/2020/gi-9-443-2020.pdf
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spelling 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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