• Media type: E-Article
  • Title: Toxic cloud imaging by infrared spectrometry: A scanning FTIR system for identification and visualization
  • Contributor: Harig, Roland; Matz, Gerhard
  • imprint: Wiley, 2001
  • Published in: Field Analytical Chemistry & Technology
  • Language: English
  • DOI: 10.1002/fact.1008
  • ISSN: 1086-900X; 1520-6521
  • Keywords: General Environmental Science ; Instrumentation ; Environmental Chemistry ; Analytical Chemistry
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>Passive remote sensing by Fourier‐transform infrared (FTIR) spectrometry allows detection and identification of toxic clouds in the atmosphere. However, the probability of detection is dependent upon the background of the field of view of the spectrometer because the signal is a function of the difference between the temperature of the cloud and the brightness temperature of the background. For small temperature differences the signal is proportional to this difference. Thus, it is possible to enhance the probability of detection by aiming the spectrometer in a direction that yields a high temperature difference between the cloud and the background. If this alignment is performed manually, the probability of detection is strongly influenced by the operator. By scanning all fields of view within the area in which a cloud is expected the probability of detection is maximized. Moreover, it is possible to visualize the cloud. An imaging passive remote‐sensing system comprised of an FTIR spectrometer, an azimuth‐elevation–scanning mirror, a data‐acquisition and control system with a digital signal processor (DSP), and a personal computer has been developed. The DSP system controls the scanning mirror, collects the interferograms of the FTIR spectrometer, and performs the Fourier transformation. The spectra are transferred to the personal computer and analyzed by a real‐time identification algorithm that does not require background spectra for the analysis. The results of the identification algorithm are visualized in false color images. The system has a high selectivity and low noise‐equivalent spectral radiance, and it allows localization of clouds and their sources. The automatic identification algorithm, the scanner system, the software for real‐time identification and imaging, and the results of field measurements are presented. © 2001 Field Analyt Chem Technol 5: 75–90, 2001</jats:p>