The effective detection of concealed handguns and knives in open spaces is a major challenge for police and security services round the world. Here an automated technique for the detection of concealed handguns that relies on active swept illumination of the target to induce both scattered fields and aspect independent responses from the concealed object is presented. The broad frequency sweep permits information about the object's size to be deduced from transformations into the time/distance domain. In our experiments we collect multiple sweeps across the frequency range at very high speed, which produces a time evolved response from the target, from both normal and cross polarized detectors. From this we extract characteristic signatures from the responses that allow those from innocent objects (e.g. mobile phones, keys etc) to be distinguished from handguns. Information about the optical depth separation of the scattering corners and the degree and shape of cross polarization allows a neural network to successfully concealed handguns. Finally this system utilizes a range of signal processing techniques ranging from correlation between cross and normally polarized scattering through to a neural network classifier to deduce whether a concealed weapon is present.

Date Published: 3 October 2008
PDF: 10 pages
Proc. SPIE 7117, Millimetre Wave and Terahertz Sensors and Technology, 711707 (3 October 2008); doi: 10.1117/12.800360

Published in SPIE Proceedings Vol. 7117:
Millimetre Wave and Terahertz Sensors and Technology
Keith A. Krapels; Neil A. Salmon, Editor(s)