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Security applications of terahertz technology

Kemp, Michael C., Taday, P. F., Cole, Bryan E., Cluff, J. A., Fitzgerald, Anthony J., Tribe, William R.·2003·SPIE Proceedings

Abstract

Recent events have accelerated the quest for ever more effective security screening to detect an increasing variety of threats. Many techniques employing different parts of the electromagnetic spectrum from radio up to X- and gammaray are in use. Terahertz radiation, which lies between microwave and infrared, is the last part to be exploited for want, until recently, of suitable sources and detectors. This paper describes practical techniques for Terahertz imaging and spectroscopy which are now being applied to a variety of applications. We describe a number of proof-of-principle experiments which show that Terahertz imaging has the ability to use very low levels of this non-ionising radiation to detect hidden objects in clothing and common packing materials and envelopes. Moreover, certain hidden substances such as plastic explosives and other chemical and biological agents may be detected from their characteristic Terahertz spectra. The results of these experiments, coupled with availability of practical Terahertz systems which operate outside the laboratory environment, demonstrate the potential for Terahertz technology in security screening and counterterrorism.

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Metadata

Authors
Kemp, M. C., Taday, P. F., Cole, B. E., Cluff, J. A., Fitzgerald, A. J., & Tribe, W. R.
Venue
SPIE Proceedings
Publisher
SPIE
Published
2003-08-01
Volume
5070
Pages
44
ISSN
0277-786X (ISSN-L)
OpenAlex
W2042013197
Cited by
569
References
0
FWCI
20.36
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Security applications of terahertz technology. https://app.cochat.ai/papers/10.1117/12.500491
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Kemp, M. C., Taday, P. F., Cole, B. E., Cluff, J. A., Fitzgerald, A. J., & Tribe, W. R. (2003). Security applications of terahertz technology. SPIE Proceedings. https://doi.org/10.1117/12.500491

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.