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Geoscientific Instrumentation, Methods and Data Systems An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gi-2020-16
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gi-2020-16
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Jul 2020

08 Jul 2020

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A revised version of this preprint was accepted for the journal GI and is expected to appear here in due course.

The baseline wander correction based on improved EEMD algorithm for grounded electrical source airborne transient electromagnetic signals

Yuan Li1, Song Gao2,3, Saimin Zhang1,2, Hu He3, Pengfei Xian3, and Chunmei Yuan3 Yuan Li et al.
  • 1College of Geophysics, Chengdu University of Technology, Chengdu, 610059, China
  • 2Key Laboratory of Earth Exploration and Information Techniques of Ministry of Education, Chengdu, 610059, China
  • 3College of Information Science and Technology, Chengdu University of Technology, Chengdu, 610059, China

Abstract. 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, the signals are the superposition of useful signals and various noise signals. The baseline wander caused by the receiving coil motion always exists in the process of data acquisition to affect the measurement results. The baseline wander is one of the main noise sources of data, which has the low frequency, large amplitude, non-periodic and non-stationary and so on. Consequently, it is important to correction baseline wander for inversion explanation of GREATEM. In this paper, we propose improving method EEMD-AF based on ensemble empirical mode decomposition (EEMD) to correction baseline wander. The EEMD-AF method will decompose the electromagnetic signal into multi-stage intrinsic mode function (IMF) components and adaptively filter high-order IMF component which containing the baseline wander. To examine the performance of our introduced method, we used the EEMD-AF method for the signal baseline correction and compared with sym8 wavelet with 10 decomposition levels and EEMD with deleted higher-order components directly. The various methods were applied to process the synthetic data and field data. Through the evaluation of the signal-to-noise ratio (SNR) and mean-square-error (MSE), the correction result indicates that the signal using EEMD-AF method can get higher SNR and lower MSE. Comparing correctional signal using the EEMD-AF and the wavelet-based method in the anomaly curves profile images of the response signal, it is proved that the EEMD-AF method is a practical and effective method for removal of the baseline wander on GREATEM signal.

Yuan Li et al.

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Yuan Li et al.

Yuan Li et al.

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Latest update: 31 Oct 2020
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Short summary
The baseline wander has special characteristics, such as low frequency, large amplitude, non-periodic and non-stationary. This phenomenon is causes by the receiving coil motion and always exists in the process of data acquisition. The proposed method can be used to solve similar problem. This paper has the following highlights: 1. The method can be used to process non-periodic and non-stationary signal. 2. The method own adaptive to satisfy stopping criterion based on measured signal.
The baseline wander has special characteristics, such as low frequency, large amplitude,...
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