1991
DOI: 10.1016/0165-9936(91)85117-a
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Rapid signal processing techniques for Fourier transform infrared remote sensing

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Cited by 31 publications
(3 citation statements)
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“…In recent literature, background subtraction methods have been shown to be of limited use for passive infrared spectral measurements. 5,6 Detection of gases is complicated by the fact that the absorptivities of a molecule may be low, and the change in radiant energy impinging on the sensor varies significantly. In many openpath passive experiments, it has been very difficult to obtain accurate background reference spectra.…”
Section: Infrared Interferogram Analysis Of Passive Ft-ir Datamentioning
confidence: 99%
“…In recent literature, background subtraction methods have been shown to be of limited use for passive infrared spectral measurements. 5,6 Detection of gases is complicated by the fact that the absorptivities of a molecule may be low, and the change in radiant energy impinging on the sensor varies significantly. In many openpath passive experiments, it has been very difficult to obtain accurate background reference spectra.…”
Section: Infrared Interferogram Analysis Of Passive Ft-ir Datamentioning
confidence: 99%
“…These considerations dictate that an ideal data analysis algorithm for use with passive FT-IR remote sensing data must be insensitive to changes in the background radiance and must facilitate rapid data collection. To address both issues, our laboratory has developed an analysis strategy based on the use of short segments of the interferogram data collected by the FT-IR spectrometer. By optimal selection of the interferogram segment location, a significant amount of information representing the infrared background can be removed. Application of band-pass digital filters to the selected segment then allows extraction of analyte information on the basis of characteristic spectral frequencies.…”
mentioning
confidence: 99%
“…Research in our laboratory is focused on overcoming this limitation by use of novel data analysis strategies for suppressing the contributions of the infrared background without performing an actual background measurement. This methodology is based on the direct analysis of short segments of FT-IR interferogram data and combines bandpass digital filtering and pattern recognition techniques to achieve the detection of VOCs. The filtering step extracts the analyte signature from collected interferograms, while the pattern recognition procedure uses the filtered interferogram data as unique patterns to determine the presence or absence of targeted VOCs.…”
mentioning
confidence: 99%