Computer Science
Scientific paper
May 1995
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995spie.2365..374p&link_type=abstract
Proc. SPIE Vol. 2365, p. 374-388, Optical Sensing for Environmental and Process Monitoring, Orman A. Simpson; Ed.
Computer Science
Scientific paper
Progress on the developement of a nonlinear curve fitting computer algorithm for data reduction of optical remote sensing Fourier transform spectrometer (FTS) data is presented. This new algorithm is an adaptation of an existing algorithm employed at the Arnold Engineering Development Center for the analysis of infrared plume signature and optical gas diagnostic data on rocket and turbine engine exhaust. Because it is a nonlinear model, the algorithm can be used to determine parameters not readily determined by linear methods such as classical least squares. Unlike linear methods this procedure can simultaneously determine atmospheric gas concetrations, spectral resolution, spectral shift, and the background or (Io(omega) spectrum. Additionally, species which possess spectra that are strongly masked by atmospheric absorption features such as BTX can also be incorporated into the procedure. The basic theory behind the algorithm is presented as well as test results on FTS data and synthetic data containing benzene and toluene spectral features.
Lay Lori T.
Moyers Rick
Phillips Bill
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