A GPR 2D Teager-Kaiser energy operator based on the multivariate variational mode decomposition

ABSTRACT

To delineate the anomalies related to subsurface target bodies and the geophysical events, a novel method based on the effective combination of the multivariate variational mode decomposition (MVMD) and 2D Teager-Kaiser operator (2D-TKEO) is proposed for ground-penetrating radar (GPR) data processing in this letter. The proposed method takes advantage of the multi-channel decomposition scheme of MVMD and the multi-directional localization of 2D-TKEO for tracking energy attributes. The time-frequency spectrum can be generated based on the IMF-slices decomposed by the MVMD, on which the 2D-TKEO is introduced to focus the spectrum energy, then the common frequency slices are extracted to reveal the energy components of different frequency ranges. The forward model and GPR field data are applied here to demonstrate that the time-frequency spectrum and the subsequent common-frequency slices based on the proposed MVMD-2DTKEO approach can depict the subsurface target bodies (e.g., voids and pipes) and subsurface layers with higher resolution and better stratigraphic continuity, compared with that of the S-transform and the VMD-1DTKEO.

KEYWORDS:

• Ground penetrating radar (GPR)
• multivariate variational mode decomposition (MVMD)
• 2D Teager-Kaiser energy operator (2D-TKEO)
• common-frequency slices

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was funded by the National Natural Science Foundation of China under Grant 42004129; the Jilin Provincial Education Department under Grant JJKH20210251KJ, S202110191150 and the Jiangsu Education Department under Grant 20KJB170005.