Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

GPR Clutter Reflection Noise Filtering Through Singular Value Decomposition in the Bidimensional Spectral Domain

Version 1 : Received: 4 May 2021 / Approved: 6 May 2021 / Online: 6 May 2021 (17:12:05 CEST)

A peer-reviewed article of this Preprint also exists.

Oliveira, R.J.; Caldeira, B.; Teixidó, T.; Borges, J.F. GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain. Remote Sens. 2021, 13, 2005. Oliveira, R.J.; Caldeira, B.; Teixidó, T.; Borges, J.F. GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain. Remote Sens. 2021, 13, 2005.

Journal reference: Remote Sens. 2021, 13, 2005
DOI: 10.3390/rs13102005

Abstract

Usually, in ground-penetrating radar (GPR) datasets the user defines the limits between the useful signal and the noise through standard filtering to isolate the effective signal as much as possible. However, there are true reflections that mask the coherent reflectors that can be considered noise. In archaeological sites these clutter reflections are caused by scattering with origin in subsurface elements (e.g., isolated masonry, ceramic objects and archaeological collapses). Its elimination is difficult because the wavelet parameters similar to coherent reflections and there is a risk of creating artifacts. In this study a procedure to filtering the clutter reflection noise (CRN) from GPR datasets is presented. The CRN filter is a singular value decomposition-based method (SVD), applied in the 2D spectral domain. This CRN filtering was tested in a dataset obtained from a controlled laboratory environment, to establish a mathematical control of this algorithm. Also, it has been applied in a 3D-GPR dataset acquired in the Roman villa of Horta da Torre (Fronteira, Portugal), which is an uncontrolled environment. The results show an increase in the quality of archaeological-GPR planimetry that were verified via archaeological excavation.

Subject Areas

Applied Geophysics; Digital Signal Processing; Enhancement of GPR Datasets; Clutter Noise Removal; Spectral Filtering

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