Probability of Detection and Optimal Sensor Placement for Threshold Based Detection Systems

This paper provides a probabilistic analysis of simple detection systems which are based on thresholding feature values extracted from a sensor signal. For such systems, this paper explains how to calculate the probability of detection as a function of range from the sensor to the object of interest. This function is important in that it enables optimal positioning of a group of sensors, either maximizing detection rates for a given number of sensors or informing the minimum number of sensors necessary to achieve a desired probability of detection throughout an area. An example case study is presented, based on a novel approach to passive acoustic diver detection in noisy environments.