Paper
22 February 2002 Airborne passive FT-IR spectrometry
Robert T. Kroutil, Roger J. Combs, Robert B. Knapp, Gary W. Small
Author Affiliations +
Proceedings Volume 4577, Vibrational Spectroscopy-based Sensor Systems; (2002) https://doi.org/10.1117/12.455739
Event: Environmental and Industrial Sensing, 2001, Boston, MA, United States
Abstract
Rapid airborne identification and quantification of vapor hazards is an environmentally important capability for a variety of open-air scenarios. This study demonstrates the use of a commercially available passive Fourier transform IR (FT-IR) spectrometer to detect, identify, and quantify ammonia and ethanol vapor signatures depending on the appropriate signal processing strategy. The signal- processing strategy removes the need for a representative background spectrum and it consists of three steps to extract the spectral information associated with the target vapor. The first step is optimal interferogram segment selection which depends on the bandwidth of the target spectral feature. The second step applies the statistically signicant finite impulse responses matrix filter to the optimal interferogram segment to attenuate spectral interferences. The third step quantifies the FIRM filter results with a discriminant analysis. The signal processing results prove that low-altitude airborne passive FT-IR spectrometry allows rapid quantitative detection of ammonia and ethanol vapor generated plumes. This effort also documents the direct interferogram analysis of data from the fast scanning airborne passive FT-IR spectrometer.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert T. Kroutil, Roger J. Combs, Robert B. Knapp, and Gary W. Small "Airborne passive FT-IR spectrometry", Proc. SPIE 4577, Vibrational Spectroscopy-based Sensor Systems, (22 February 2002); https://doi.org/10.1117/12.455739
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KEYWORDS
Spectroscopy

Bioalcohols

Sensors

Optical filters

FT-IR spectroscopy

Digital filtering

Infrared signatures

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