<div class="description">
<p>Among the many weapons currently used by terrorist organizations against public welfare and coalition forces in Iraq and Afghanistan, human-born Improvised Explosive Devices (IEDs) present a significant threat. Commonly referred to as \"suicide bombers,\" these individuals enter crowded public areas in order to detonate the IED, inflicting lethal damage to the surrounding individuals. Constructed of non-standard parts and hidden under layers of clothing, these humanborn IEDs go undetected until detonated. Currently, there are no detection systems that can identify suicide bombers at adequate standoff distances. The purpose of this research is to develop a methodology that combines current technologies to increase the probability of identifying a suicide bomber at a checkpoint or marketplace with an adequate standoff distance. The proposed methodology will employ each sensor technology incorporating unique detection threshold values. We will analyze our proposed methodology utilizing a simulation model that provides both the probability of detecting a bomber and the probability of a false detection. These simulations will allow us to determine the threshold values for each sensor that result in the best probability of detection of a suicide bomber and allows for a small probability of false detections.
</p>
<br>Subjects: Identification; Terrorism; Methodology</div>
<div class="fn value">
Minukas, Michael</div>
Internet Archive identifier