Discrimination of metal land mines from metal clutter: results of field tests

Abstract

Metal land mines still account for a large percentage of land mines, even with the advent of the so-called plastic mines. The metal detector thus remains a viable tool in the mine detector's bag. The limitation of the metal detector is not in detection of the mines, but in the additional detection of metal clutter. A metal detector has been developed which can largely discriminate the mines from the clutter, thereby greatly reducing false alarm rates. This "mine detector" is designed to characterize the magnetic polarizability dyadic of the metal objects, and to use pattern recognition to determine the goodness-of-fit to the responses of known mines. Data are presented from test runs conducted for the US Army for buried metal mines. Data are also presented for some non-mine metal targets. The characterization of the mines as threats is performed in a totally autonomous system, with high probability-of-detection and low false alarm rate. We can also generally tell one mine type from another.

Statistical classification of buried objects from spatially sampled time or frequency domain electromagnetic induction data

“…[17] While the utility of the model described here has been validated using real sensor data [Das et al, 1990;Sower et al, 1999;Riggs et al, 2001] as described in section 1, generally objects do not behave exactly as dipoles. Moreover, one cannot practically use an infinite number of poles for each l i .…”

“…Aside from Bell et al [2001], classification algorithms have been concerned strictly with either time domain EMI sensors [Barrow and Nelson, 2001;Tantum and Collins, 2001] or frequency domain [Norton and Won, 2001;Riggs et al, 2001] but not both. Riggs et al [2001] and Tantum and Collins [2001] employ a parametric model for the PAPFs which takes the form of a sum of decaying exponentials [Sower et al, 1999;Collins et al, 2000;Carin et al, 2001] in the time domain or a sum of onepole rational system functions each with a zero at DC in frequency. The poles and/or decay constants are then used as the features for classification.…”

GSTAMIDS pulsed magnetic induction metal detector: hardware description and data processing algorithms

“…Previous reports have shown how these locations form patterns for given mine types that are largely distinguishable from those of other metal mines, and essentially totally distinguishable from non-mine metal clutter objects 6,7,8 . Results are overlaid for an aluminum disk, 6-inch diameter by 1/4" thick, which has only one significant pole, the amplitudes of the other two being essentially zero.…”

“…Results are overlaid for an aluminum disk, 6-inch diameter by 1/4" thick, which has only one significant pole, the amplitudes of the other two being essentially zero. The input data waveforms can be either composite averages of several data frames as the detector moves over the target 6 , or individual data frames that change pole locations slightly from frame-to-frame, giving additional information about target identity from the trajectories of the changes 7 . …”

“…A pulsed magnetic induction (PMI) technology has been developed that incorporates hardware and electronics specifically designed to measure these properties. Algorithms and software are implemented for real-time data processing and extraction of the pertinent features 6,7,8 . The electrodynamical and physical aspects of the technology is incorporated in a working mine detection platform that has a high probability of detection and a low false alarm rate.…”