Modeling and Methodology for Incorporating Existing Technologies to Produce Higher Probabilities of Detecting Suicide Bombers

The article of record as published may be found at http://dx.doi.org/10.4018/joris.2013070101Among the many weapons currently used by terrorist organizations against public welfare and coalition forces, 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 their IED, inflicting lethal damage to the surrounding individuals. Constructed of non-standard parts and hidden under layers of clothing, these human-born IEDs go undetected until detonated. Currently, there are no detection systems that can identify suicide bombers at adequate standoff distances. The authors developed models and a methodology that examine current technologies to increase the probability of identifying a suicide bomber at a checkpoint or marketplace with an adequate standoff distance. The proposed methodology employs sensor technology incorporating unique detection threshold values. The authors 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. Using experimentally “good” threshold values, the authors were able to drastically increase the probability of detection with a combination of radar and thermal imagery. In this paper, the main sensor is the hand-held rada