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Proceedings Paper

Signal processing strategies for passive FT-IR sensors
Author(s): Ronald E. Shaffer; Roger J. Combs
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Paper Abstract

Computer-generated synthetic single-beam spectra and interferograms are used to study signal processing strategies for passive Fourier transform IR (FTIR) sensor. Synthetic data are generated for one-, two-, and four- component mixtures of organic vapors in two passive FTIR remote sensing scenarios. The single-beam spectra are processed using Savitsky-Golay smoothing, first derivative, and second derivative filters of various orders and widths. Interferogram data are processed by Fourier filtering using Gaussian-shaped bandpass digital filters. Pattern recognition of the target analyte spectral signature is performed using soft independent modeling of class analogy. Quantitative models for the target gas integrated concentration-path length product are built using partial least-squares regression and locally weighted regression. Pattern recognition and calibration models of the filtered spectra and interferograms produced similar results. Chemical detection is possible for complex mixtures if the temperature difference between the source and analyte cloud is sufficiently large. Quantitative analysis is possible if the temperature of the analyte cloud is stable or known and is sufficiently different from the background temperature.

Paper Details

Date Published: 6 August 1998
PDF: 12 pages
Proc. SPIE 3383, Electro-Optical Technology for Remote Chemical Detection and Identification III, (6 August 1998); doi: 10.1117/12.317639
Show Author Affiliations
Ronald E. Shaffer, Naval Research Lab. (United States)
Roger J. Combs, U.S. Army Edgewood Research, Development, and Engineering Ctr. (United States)


Published in SPIE Proceedings Vol. 3383:
Electro-Optical Technology for Remote Chemical Detection and Identification III
Mahmoud Fallahi; Ellen A. Howden, Editor(s)

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