RDX Detection with THz Spectroscopy
- 215 Downloads
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.
KeywordsTHz spectroscopy Explosive detection Neural networks ROC curves
The authors gratefully acknowledge the funding support by Rajen Patel and the U.S. Army - Picatinny Arsenal EWMTD through grants DAAE3003D1015-22 and DAAE3003D1015-33.
- 2.Bandyopadhyay, A., A. Sengupta, R.B. Barat, D.E. Gary, Z.-H. Michalopoulou, and J.F. Federici, Artificial neural network analysis in interferometric Terahertz imaging for detection of lethal agents. International Journal of Infrared and Millimeter Waves, 2006. 27(8): p. 1145–1158.CrossRefGoogle Scholar
- 5.Federici, J.F., D. Gary, R. Barat, Z.-H. Michalopoulou, Detection of Explosives by Terahertz Imaging, in -Terrorism Detection Techniques of Explosives, J. Yinon, Editor. 2007, Elsevier.Google Scholar
- 6.Zorych, I., A. Sinyukov, Z.-H. Michalopoulou, R. Barat, D. Gary, J. F. Federici. Explosive identification with Terahertz spectroscopy: a model based approach. in SAFE 2007. 2007. Washington, D.C.Google Scholar
- 7.Kemp, M.C., P. F. Taday, B. E. Cole, J. A. Cluff, A. J. Fitzgerald, W. R. Tribe, Security applications of Terahertz technology, in Terahertz for Military and Security Applications, D.L.W. R. J. Hwu, Editor. 2003, SPIE. p. 44–52.Google Scholar
- 10.Wang, Y., Z. Zhao, Z. Chen, K. Kang, B. Feng, Y. Zhang, Terahertz absorbance spectrum fitting method for quantitative detection of concealed contraband. Journal of Applied Physics, 2007. 102(11): p. 1131081–1131086.Google Scholar
- 11.Lippmann, R.P., An introduction to computing with neural nets. IEEE ASSP, 1987: p. 4–22.Google Scholar
- 12.Zorych, I., Yew Li Hor, Alexander M. Sinyukov, Zoi-Heleni Michalopoulou, Robert B. Barat, Dale E. Gary, and John F. Federici A Statistical Approach to RDX Detection with THz Reflection Spectra, in CAMS Techical Report Series 2008–2009. 2008, New Jersey Institute of Technology.Google Scholar
- 13.Mittleman, D.M., Terahertz Imaging, in Sensing with Terahertz Radiation, D.M. Mittleman, Editor. 2003, Springer. p. 117–153.Google Scholar
- 14.Liu, Z., Ke Su, Dale E. Gary. John F. Federici, Robert B. Barat, Zoi-Heleni Michalopoulou, Video-rate terahertz interferometric and synthetic aperture imaging. Applied Optics, 2008: p. 3788–3795.Google Scholar
- 15.Hastie, T., R. Tibshirani, J. Friedman, The Elements of Statistical Learning. 2001: Springer.Google Scholar
- 16.Huang, Y.S., C. Y. Chen, A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals. IEEE Transactions on Pattern Analysis and Machine Intelligence. 17: p. 90–94.Google Scholar