RDX Detection with THz Spectroscopy
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RDX Detection with THz Spectroscopy Zoi-Heleni Michalopoulou & Suman Mukherjee & Yew Li Hor & Ke Su & Zhiwei Liu & Robert B. Barat & Dale E. Gary & John F. Federici
Received: 19 February 2010 / Accepted: 27 July 2010 / Published online: 6 August 2010 # Springer Science+Business Media, LLC 2010
Abstract Spectroscopic analysis in the Terahertz frequency range, providing characteristic “signatures” for explosive and non-explosive materials, is proposed as an efficient and powerful tool for explosive identification. It is demonstrated that spectral responses of materials can be used as fingerprints that distinguish cyclotrimethylenetrinitramine (RDX) from other materials even with simple detectors and a limited number of available frequencies. Detection is performed using a modified least squares approach and multilayer perceptrons that operate on smoothed reflectance spectra. The performance of the detectors is evaluated through application to spectra of RDX and several common materials. A Receiver Operating Characteristic curve analysis demonstrates that our detectors exhibit the desirable properties of high probability of detection and low probability of false alarm. Keywords THz spectroscopy . Explosive detection . Neural networks . ROC curves
1 Introduction The urgent need for extensive, reliable, and fast screening for the identification of explosives stemming from public safety and homeland security concerns has stimulated the search for efficient, quantitative, and reliable detectors and classifiers. Terahertz (THz) spectroscopy has been proposed as a valuable tool to this end [1–10]. It is a particularly useful approach because lethal agents have distinct spectral signatures in the THz frequency
Z.-H. Michalopoulou (*) Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ 07102, USA e-mail: [email protected] S. Mukherjee : Y. L. Hor : K. Su : Z. Liu : D. E. Gary : J. F. Federici Department of Physics, New Jersey Institute of Technology, Newark, NJ 07102, USA R. B. Barat Otto York Department of Chemical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
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J Infrared Milli Terahz Waves (2010) 31:1171–1181
range that can serve as “fingerprints” for their identification, while most common dielectric barriers are largely transparent to THz radiation. In [2], we applied multilayer perceptrons and Kohonen Self Organizing Maps to simulated images of RDX (cyclotrimethylenetrinitramine) and metal, synthesized with THz synthetic aperture / interferometric imaging. The networks successfully separated the two categories of materials in distinct classes. In [6], the presence or absence of agents such as RDX was detected by a least-squares difference calculation between measured and reference reflectance spectra in the THz range. The approach was supported by analysis of RDX spectra measured in the lab, clearly indicating a common spectroscopic behavior across several different scans of RDX. Classification of materials and identification of RDX was straightforward wh
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