Statistics – Applications
Scientific paper
Nov 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001spie.4491..111s&link_type=abstract
Proc. SPIE Vol. 4491, p. 111-119, Subsurface and Surface Sensing Technologies and Applications III, Cam Nguyen; Ed.
Statistics
Applications
Scientific paper
Migration is a common name for processing techniques that try to reconstruct, from the dat recorded at the surface, the reflecting structures in the sub-surface. Most of the existing migration techniques do not take into account the characteristics of the acquisition system and the ground characteristics. We propose a novel migration method, applicable on Ground Penetrating Radar (GPR) images, that integrates the time domain model of the GPR in the migration scheme. We calculate by forward modeling a synthetic 3D point spread function of the GPR, i.e. a synthetic C-scan of a small point scatterer. The 3D point spread function, containing system characteristics like the waveform of the excitation source, the combined antenna footprint and the impulse response (IR) of the antennas, is then used to deconvolve the recorded data. Results of this migration method on real data obtained by an ultra-wideband GPR system show that the migration method is able to reconstruct the top contour of small targets like AP mines, in some cases even the correct dimensions. The method is also capable of migrating oblique targets into their true position. The migration scheme is not computational intensive and can easily be implemented in real time.
Acheroy Marc P.
Scheers Bart
Vander Vorst Andre
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