A new approach to enhancement of ground penetrating radar target signals by pulse compression

Mahmoud Gaballah, Motoyuki Sato

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is applied to synthetic and field GPR data acquired over a buried pipe. The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a reference signal for pulse compression. For a pulse-compression filter, reference signal selection is an important issue, because as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is low. Analysis of the results obtained from simulated and field GPR data indicates a significant improvement in the GPR image, good discrimination between the target reflection and the ground surface reflection, and better performance with reliable separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.

Original languageEnglish
Pages (from-to)77-84
Number of pages8
JournalExploration Geophysics
Volume40
Issue number1
DOIs
Publication statusPublished - 2009 Jul 6

Keywords

  • Clutter
  • Deconvolution
  • GPR
  • Pulse compression
  • Reference signal
  • Wiener filter.

ASJC Scopus subject areas

  • Geophysics
  • Geology

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