Classification of landmine-like metal targets using wideband electromagnetic induction

In our previous work, we have shown that the detectability of landmines can be improved dramatically by the careful application of signal detection th eory to time-domain electromagnetic induction (EMI) data using a purely sta tistical approach. In this paper, classification of various metallic land-m ine-like targets via signal detection theory is investigated using a protot ype wideband frequency-domain EMI sensor. An algorithm that incorporates bo th a theoretical model of the response of such a sensor and the uncertainti es regarding the target/sensor orientation is developed. This allows the al gorithms to be trained without an extensive data collection. The performanc e of this approach is evaluated using both simulated and experimental data. The results show that this approach affords substantial classification per formance gains over a standard approach, which utilizes the signature obtai ned when the sensor is centered over the target and located at the mean exp ected target/sensor distance, and thus ignores the uncertainties inherent i n the problem. On the average, a 60% improvement is obtained.