Paper
23 November 1999 Signal processing strategies for passive FT-IR remote sensing
Ronald E. Shaffer
Author Affiliations +
Abstract
Computer-generated synthetic single-beam spectra and interferograms are used to study signal processing strategies for passive Fourier transform IR (FTIR) remote sensing. Four-component mixtures of ethanol, methanol, methyl ethyl ketone, and acetone vapors in two passive FTIR remote sensing scenarios are studied. Interferogram and spectral processing strategies are compared based on the ability to generate accurate pattern recognition and multivariate calibration models. Chemical detection and quantitative analysis is further assessed based on analyte band characteristics and spectral overlap. Temperature differential between the analyte cloud and the IR source is found to be the critical factor determining classification performance. Calibration model performance is further dependent upon the ability to reliably assess analyte plume temperature. Calibration model performance is shown to degrade significantly as the uncertainty in plume temperature increases or as the temperature difference decreases. These results suggest that in order to quantify passive FTIR spectra remotely either there must be either a large temperature difference or an accurate assessment of plume temperature.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ronald E. Shaffer "Signal processing strategies for passive FT-IR remote sensing", Proc. SPIE 3856, Internal Standardization and Calibration Architectures for Chemical Sensors, (23 November 1999); https://doi.org/10.1117/12.371281
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Calibration

Signal processing

Clouds

Filtering (signal processing)

FT-IR spectroscopy

Bioalcohols

Optical filters

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