Abstract
Recently the SERDP/ESTCP office under the UXO Discrimination Pilot Study Program acquired high-density data over hundreds of targets using time-domain EM-63 sensor at Camp Sibert. The data were inverted and analyzed by various research groups using a simple dipole model approach and different classification tools. The studies demonstrated high discrimination probability with a low false-alarm rate. However in order to further improve discrimination between UXO and non-UXO items a better understanding is needed of the limits of current and emerging processing approaches. In this paper, the simple dipole model and a physically complete model called the normalized surface magnetic source (NSMS) the Camp Sibert data sets. The simple, infinitesimal dipole representation is by far the most widely employed model for UXO modeling. In this model, one approximates a target's response when excited by a primary (transmitted) field using an induced infinitesimal dipole (in turn described by a single magnetic polarizability matrix). The greatest advantage of the dipole model is that it is simple and imposes low computation costs. However, researchers have recently begun to realize the limitations of the simple dipole model as an inherently coarse description of the EMI behavior of complex, heterogeneous targets like UXO. To address these limitations, here the NSMS is employed as a more powerful forward model for data inversion and object discrimination. This method is extremely fast and equally applicable to the time or frequency domains. The object's location and orientation are estimated by using a standard nonlinear inversion-scattering approach. The discrimination performance between the dipole and NSMS models are conducted by investigating model fidelity and data density issues, positional accuracy and geological noise effects.
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