Paper
3 October 2008 A multifaceted active swept millimetre-wave approach to the detection of concealed weapons
David A. Andrews, Nicholas Bowring, Nacer D. Rezgui, Matthew Southgate, Elizabeth Guest, Stuart Harmer, Ali Atiah
Author Affiliations +
Proceedings Volume 7117, Millimetre Wave and Terahertz Sensors and Technology; 711707 (2008) https://doi.org/10.1117/12.800360
Event: SPIE Security + Defence, 2008, Cardiff, Wales, United Kingdom
Abstract
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David A. Andrews, Nicholas Bowring, Nacer D. Rezgui, Matthew Southgate, Elizabeth Guest, Stuart Harmer, and Ali Atiah "A multifaceted active swept millimetre-wave approach to the detection of concealed weapons", Proc. SPIE 7117, Millimetre Wave and Terahertz Sensors and Technology, 711707 (3 October 2008); https://doi.org/10.1117/12.800360
Lens.org Logo
CITATIONS
Cited by 10 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Firearms

Neural networks

Weapons

Signal detection

Sensors

Scattering

Target detection

Back to Top