Modeling and Methodology for Incorporating Existing Technologies to Produce Higher Probabilities of Detecting Suicide Bombers
Abstract
Among 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 radar
Description
The article of record as published may be found at http://dx.doi.org/10.4018/joris.2013070101
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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