Advanced Signal Processing for Reduction of False Alarm Rate of Metal Detectors for Humanitarian Mine Clearance

Today for clearing areas from landmines, beside dogs and searching needles, almost excluding metal detectors are used. Available metal detectors, specialised for mine clearance, are highly sensitive also on small metal parts. Nevertheless, they give no further information about the buried object (depth, size, shape, material). Besides, the high false alarm rate of the hand-held detectors makes the mine clearance a protracted and cost-intensive process. Reasons for the high false alarm rate (up to 1000 false alarms per mine) are "uncooperative" soils, harmless metallic objects like shell splinters, but also the low metal content in newer anti-personnel mines. In this paper a method is described which provides more information about the buried object by using image processing and signature classification, which works also in the presence of "uncooperative" soil. In many cases, there are only one or two different mines in a minefield. So it is possible to use a database with mine signatures for an automatic object classification in order to decrease the false alarm rate