Area-based results for mine detection

The cost and the closely related length of time spent in searching for mines or unexploded ordnance (UXO) may well be largely determined by the numher of false alarms. False alarms can result in time consuming digging of soil or in additional multisensory tests in the minefield. In this paper, we consider two area-based methods for reducing false alarms. These are: a) the previously known "declaration'' technique [8], [10] and b) the new delta technique, which we introduce. We first derive expressions and lower bounds for false-alarm probabilities as a function of declaration area and discuss their impact on receiver operation characteristic (ROC) curves. Second, we exploit characteristics of the statistical distribution of sensory energy in the immediate neighborhood of targets and of false alarms from available calibrated data, to propose the delta technique, which significantly improves discrimination between targets and false alarms. The results are abundantly illustrated with statistical data and ROC curves using electromagnetic-induction sensor data made available through DARPA [8] from measurements at various calibrated sites.