The cost and the closely related length of time spent in searching for mine
s 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 co
nsider two area-based methods for reducing false alarms. These are: a) the
previously known "declaration'' technique [8], [10] and b) the new delta te
chnique, which we introduce. We first derive expressions and lower bounds f
or 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 i
n the immediate neighborhood of targets and of false alarms from available
calibrated data, to propose the delta technique, which significantly improv
es discrimination between targets and false alarms. The results are abundan
tly illustrated with statistical data and ROC curves using electromagnetic-
induction sensor data made available through DARPA [8] from measurements at
various calibrated sites.