The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals

Li, Yuan; Gao, Song; Zhang, Saimin; He, Hu; Xian, Pengfei; Yuan, Chunmei

doi:https://doi.org/10.5194/gi-9-443-2020

Articles | Volume 9, issue 2

https://doi.org/10.5194/gi-9-443-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gi-9-443-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 9, issue 2

Research article

| Highlight paper

|

16 Nov 2020

Research article | Highlight paper |

| 16 Nov 2020

The baseline wander correction based on the improved ensemble empirical mode decomposition (EEMD) algorithm for grounded electrical source airborne transient electromagnetic signals

Yuan Li, Song Gao, Saimin Zhang, Hu He, Pengfei Xian, and Chunmei Yuan

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Final revised paper (published on 16 Nov 2020)
Preprint (discussion started on 08 Jul 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'electromagnetic signals', Anonymous Referee #1, 14 Jul 2020
- AC1: 'Reply to 'electromagnetic signals' comments', Yuan LI, 25 Aug 2020
RC2: 'Comments for article gi-2020-16', Anonymous Referee #2, 06 Aug 2020
- AC2: 'Reply to Comments for article gi-2020-16', Yuan LI, 26 Aug 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Yuan LI on behalf of the Authors (09 Sep 2020) Author's response Manuscript

ED: Publish as is (26 Sep 2020) by Luis Vazquez

AR by Yuan LI on behalf of the Authors (28 Sep 2020) Author's response Manuscript

Short summary

The baseline wander has special characteristics, such as being low frequency, large amplitude, non-periodic, and non-stationary. It is caused by the receiving coil motion and always exists in the process of data acquisition. The proposed method can be used to solve similar problems. This paper has the following highlights: (1) the method can be used to process non-periodic and non-stationary signals; (2) the method is adaptive to satisfy the stopping criterion based on the measured signal.