Articles | Volume 15, issue 1
https://doi.org/10.5194/gi-15-183-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Enhanced removal of very low frequency and low frequency radio noise from transient electromagnetic data with modeling and adaptive filtering
Download
- Final revised paper (published on 21 May 2026)
- Preprint (discussion started on 25 Mar 2026)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2026-1141', Anonymous Referee #1, 30 Mar 2026
- AC1: 'Reply on RC1', Jakob Juul Larsen, 05 May 2026
-
RC2: 'Comment on egusphere-2026-1141', Anonymous Referee #2, 13 Apr 2026
- AC2: 'Reply on RC2', Jakob Juul Larsen, 05 May 2026
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Jakob Juul Larsen on behalf of the Authors (05 May 2026)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (06 May 2026) by Lev Eppelbaum
AR by Jakob Juul Larsen on behalf of the Authors (07 May 2026)
Manuscript
The work is devoted to the development of advanced algorithm for TEM data processing in the case when signal of standard (VLF, 3-30 kHz) and low frequency (LF, 30-300 kHz) radio stations are present.
Characteristics of VLF and LF radio signals encoded with minimum-shift keying methods are used to allow for a solution where the noise is modeled and subtracted. It has been shown that the addition of an adaptive filter can fine-tune the radio model and improve the signal-to-noise ratio.
Proposed algorithm has been checked on a synthetic noise data set and on a real field noise data.