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Detection of explosives on surfaces could potentially be achieved using handheld standoff optical sensors, providing rapid intelligence and safety to the warfighter or first responder. Recent work has shown the capability to discriminate various chemical vapors using a bioinspired or biomimetic detection system modeled on human color vision. This biomimetic system utilizes three overlapping broadband infrared optical filters to discriminate between various chemicals. Preliminary reflectance data of chemicals on surfaces indicate a capability for discrimination of target chemicals and interferents by analysis of biomimetic sensor output using novel analytical methods such as “Comparative Discrimination Spectral Detection” (CDSD). Transitioning this detection method to threats on surfaces at proximate standoff distances (~1 m) requires additional considerations including surface characteristics and angle of detection. This work explores sensor detection parameters for ammonium nitrate residue on aluminum surfaces of various roughnesses. Samples of the explosives component ammonium nitrate, NH4NO3, diluted at 10%, 5%, and 1% in DI water, were prepared by dropcasting onto aluminum coupons with four surface finishes: polished, brushed, extruded, and sandblasted. Surface roughnesses were measured. Single beam reflectance spectra (2 – 20 μm) were collected using a FTIR spectrometer over multiple independent angles of incidence and collection (15° - 80°). Multiple factors were analyzed including albedo, and potential sensor configurations. Characteristics for future MWIR and LWIR sensors, such as illumination power and detector sensitivity, are evaluated which enable chemical spectral identification across range of aluminum surface roughness for proximate standoff distances and different angles of incidence.
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