Journal
GEOPHYSICAL JOURNAL INTERNATIONAL
Volume 202, Issue 2, Pages 1324-1338Publisher
OXFORD UNIV PRESS
DOI: 10.1093/gji/ggv208
Keywords
Image processing; Inverse theory; Electrical properties; Electromagnetic theory; Ground penetrating radar; Microstructures
Categories
Funding
- National Natural Science Foundation of China [41430322, 41202085]
- Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) [20130061110061]
- China Scholarship Council (CSC)
- 973 Program [2013CB429805]
- Jilin University Seed Foundation for Distinguished Young Scientists
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Polarization is a property of electromagnetic wave that generally refers to the locus of the electric field vector, which can be used to characterize surface properties by polarimetric radar. However, its use has been less common in the ground-penetrating radar (GPR) community. Full polarimetric GPR data include scattering matrices, by which the polarization properties can be extracted, at each survey point. Different components of the measured scattering matrix are sensitive to different types of subsurface objects, which offers a potential improvement in the detection ability of GPR. This paper develops a polarimetric migration imaging method. By merging the Pauli polarimetric decomposition technique with the Krichhoff migration equation, we develop a polarimetric migration algorithm, which can extract three migrated coefficients that are sensitive to different types of objects. Then fusing the three migrated coefficients, we can obtain subsurface colour-coded reconstructed object images, which can be employed to interpret both the geometrical information and the scattering mechanism of the subsurface objects. A 3-D full polarimetric GPR data set was acquired in a laboratory experiment and was used to test the method. In the laboratory experiment, four objects-a scatterer, a ball, a plate and a dihedral target-were buried in homogeneous dry sand under a flat ground surface. By merging the reconstructed image with polarization properties, we enhanced the subsurface image and improved the classification ability of GPR.
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