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A metallic mine detector is one of the most effective pieces of equipment for detection of mines. Their main drawback is their extremely rate of up to 100 percent, but it can also produce a high false alarm rate in many environments. The high false alarm rate reduces the usefulness of the metal detector in the field. In order to keep a high detection rate with fewer false alarms, object/mine characterization or identification must be used. Several techniques have been implemented to reduce the false alarm rate of metal detectors. They are size discrimination, target imaging, and target signatures such as dipole moment characterization. These techniques are applied for large metallic objects/mines. P.V. Czipott and D.A. Waldron each used separate techniques to characterize smaller metallic objects and some anti-personnel mines, in work supported by US Army CECOM, Night Vision and Electronic Sensors Directorate. Dr. Czipott characterized objects/mines by measuring the frequency dependence of magnetic fields caused by electric currents induced in the target. The frequency responses were measured by using a fixture incorporating a solenoid excitation coil, a receiving coil wound as a gradiometer, and a HP 4195A network/spectrum analyzer. Ms. Waldron characterized small objects with different conductivities and orientations by measuring their phase differences using a search head with one transmitter and four receiver coils and a phase-lock analyzer. We believe that target discrimination and identification are the keys to reduce false alarm rates of metallic mine detectors. Thus, we continue to analyze and characterize small metallic targets/mines using a variety of methods.
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