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Surveillance of perimeters is essential, especially for critical infrastructure such as transportation hubs, power stations, chemical facilities and others. There are many approaches to perimeter surveillance, but most of these require large upfront investments. This investigation uses advanced electromagnetic modeling techniques with real human body geometries to establish the best set of detectable features using the Wireless Area Secure Perimeter (WASP) system geometry. Using the frequency, power level, network configuration, and antennas employed by WASP, predictions on limits to target recognition are presented, along with recommendations for system reconfiguration for improving target characterization.

The US Department of Homeland Security (DHS) has requirements for future explosives scanners that include dealing with a larger number of threats, higher probability of detection, lower false alarm rates and lower operating costs. One tactic that DHS is pursuing to achieve these requirements is to augment the capabilities of the established security vendors with third-party algorithm developers. The purposes of this presentation are to review DHS's objectives for involving third parties in the development of advanced algorithms and then to discuss how these objectives are achieved using workshops and grand challenges.