Optimizing decision threshold and weighting parameter for UXO discrimination

Abstract

Establishing a decision threshold to separate unexploded ordnance (UXO) from clutter is a critical task in UXO discrimination procedures. It is, however, a difficult task because the decision threshold depends on many parameters such as local geology, distribution of UXO and clutter, and cultural and environmental noise at a given UXO cleanup site. Some discrimination algorithms also use site-dependent weighting factors. In practice, one determines these parameters empirically from calibration experiments. To facilitate this task, we introduce a simple function called the degree of discrimination, constructed from calibration plots at a UXO cleanup site. First, we compute the degree of discrimination for a representative set of thresholds and weighting factors using ground truth data from the calibration site. Then, we find the optimum decision threshold and weighting factors associated with the best degree of discrimination. Finally, we use these optimal parameters for the UXO site cleanup. We have conducted two experiments using the broadband electromagnetic (EM) sensor with a concentric coil configuration. Our experiments show that 92% of UXO is declared and 74% of clutter is rejected using our optimized threshold and weights. A blind test shows that optimizing the threshold and weights increases the degree of discrimination from 0 to 0.15. Our tests also show that the detection scheme with a collective threshold for all UXO types is easier to use and yields better discrimination than the scheme based on individual thresholds for each UXO type.