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22 August 2000 GPR imaging approaches for buried plastic land mine detection
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This paper explores new imaging approaches for detection of buried plastic mines using data from a ground penetrating radar array. The first approach is based on fine-resolution imaging of the perrnittivity contrast in the region of interest. We develop a model relating the collected data to the contrast generated by buried objects, using ray optics to represent the air/soil interface and Borrt weak scattering approximations. We use this model to develop inversion algorithms for image formation, using alternative regularization approaches to overcome modeling error and ill-posedness due to limited sensing geometries. The second approach is based on tomographic curve evolution techniques, which use object boundaries and a set of contrast coefficients to represent the underlying perrnittivity contrast field. The inversion method seeks to extract less information than a full image, concentrating on accurate estimation of object boundaries. The problem of determining the reduced parameters is formulated as a non-linear estimation problem, which is solved iteratively using level set techniques. The algorithms are tested on data generated by nonlinear finite difference time domain electromagnetic simulations, under conditions involving different ground roughness and object geometries.
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Haihua Feng, David A. Castanon, William Clement Karl, and Eric L. Miller "GPR imaging approaches for buried plastic land mine detection", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000);

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