Abstract

The development of techniques for reliable stand-off detection of explosives and their precursors is still an ongoing challenge. Apart from Raman spectroscopy [1], imaging mid-infrared (MIR) backscattering spectroscopy has shown to be a particularly promising technique for non-contact detection of residues of explosives and precursor materials on various surfaces [2]. This technique relies on active imaging using wavelength-tunable MIR laser illumination. Recording the backscattered light with an MIR camera at each illumination wavelength, the MIR backscattering spectrum can be extracted from the three-dimensional data set for each pixel within the laser illuminated area. This way, contaminated areas can be clearly identified on the basis of characteristic fingerprint backscattering spectra and separated from the corresponding spectra of the underlying material. To achieve high selectivity, a large spectral coverage is a key requirement. Using wavelength-tunable external-cavity quantum cascade lasers (EC-QCL) emitting in the MIR, different explosives such as TNT, PETN and RDX residing on different background materials, such as painted metal sheets, cloth and polyamide, could be clearly detected and identified using customized hyperspectral data analysis algorithms [3]. Over short-to-medium stand-off detection distances (<3 m), residues of explosives equivalent to a finger print with a total of 10-to-100 µg of material residing on a surface could be detected. Stand-off detection over distances of up to 28 m has already been demonstrated for larger concentrations of explosives.

© 2015 IEEE