Trace quantities of particles are generally left behind during the transport of explosive materials or from fingerprints of their handlers. We use a Deep-ultraviolet resonance Raman explosive detection (DURRED) sensor developed at the High Technology Foundation to study explosive trace samples with varying fill factors. In this study we show high sensitivity detection of very low-fill factor traces of KNO3, KClO3 and PETN. Receiver operating characteristics generated from samples (>20% fill) at a moderate signal-to-noise ratio of ~7 showed a probability of detection greater than >99.9%, a false acceptance rate of less than 2×10-4.
Proc. SPIE. 10183, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XVIII
KEYWORDS: Signal to noise ratio, Standoff detection, Detection and tracking algorithms, Deep ultraviolet, Sensors, Spectroscopy, Raman spectroscopy, Directed energy weapons, Spectral resolution, Explosives
Deep-ultraviolet Raman spectroscopy is a very useful approach for standoff detection of explosive traces. Using two simultaneous excitation wavelengths improves the specificity and sensitivity to standoff explosive detection. The High Technology Foundation developed a highly compact prototype of resonance Raman explosives detector. In this work, we discuss the relative performance of a dual-excitation sensor compared to a single-excitation sensor. We present trade space analysis comparing three representative Raman systems with similar size, weight, and power. The analysis takes into account, cost, spectral resolution, detection/identification time and the overall system benefit.