ABSTRACT
A method for interpretation of remote sensing FTIR spectra was set up based on ANN model. Considering long training time and over-fitting problem of ANN, two methods, partial least squares (PLS) and principal component analysis (PCA), were utilized to extract principal components of spectra, process time decrease from about 30 minutes to a few seconds. Meanwhile, the idea of calibration transfer was used to overcome the limitation of calibration model in remote sensing FTIR spectra analysis. With the optimization of ANN model, four-component mixtures of acetone, benzene, chloroform and methanol were predicted in a remote sensing and real-time way while the calibration model was built with EPA data. The best performance was yielded with PLS-ANN model, and the root mean square error (RMSE) of acetone, benzene, chloroform and methanol were 0.043, 0.031, 0.034 and 0.051 respectively, which confirm the real-time, correct and quick analysis of remote sensing FTIR in air monitoring.
ABSTRACT
In order to obtain infrared spectral radiance distribution of some infrared sources, such as spectral radiant flux density, spectral radiant intensity, spectral radiance and spectral irradiance, the instrument response function under different conditions must be known. In the present paper, the calibration of instrument response function during passive FTIR measurement has been discussed. The experimental results illustrate that under different experimental conditions, the instrument response function varies not only with the temperature of the blackbody but also with the signal amplitude received by the infrared instrument. So, during passive FTIR measurement, the temperature and the emission signal amplitude of the source must be observed carefully in order to get satisfactory instrument response function.
