Line Shape Effect Modeling and Compensation for Passive Remote Sensing Signals of Fourier Transform Infrared Spectrometers
WU Jun1, CUI Fang-xiao1*, YUAN Xiao-chun2, LI Da-cheng1, LI Yang-yu1, WANG An-jing1, GUO Teng-xiao3
1.Key Laboratory of General Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
2. Kunming Institute of Physics, Kunming 650032, China
3.State Key Laboratory of Nuclear, Chemical and Biological Disaster Protection, Beijing 102205, China
Abstract:Accurate quantification of infrared remote sensing signal is important for acquisition of pollutant cloud’s information, but spectral distortions occurred in measurement may hinder the achievement of such purpose. An adaptive method based on instrumental line shape (ILS) model was established in order to compensate the contributions due to ILS distortion. Through analysis of the sources of ILS function, the ideal, inherent function as well as phase error contribution were modeled based on design parameters of a real infrared spectrometer. Furthermore, an algorithm which reconstructs ILS function from measurement was developed by using iterative optimization method, which takes root mean square between differences of simulation and measurement spectrum as cost function. The compensation result by using reconstructed ILS function on simulated spectrum suggests that differences between simulation and measurement were effectively eliminated. The analysis showed that inherent ILS may cause spectral feature broadening toward low frequency, and phase error is responsible for spectral feature asymmetry. All three sources of ILS distortion must be considered simultaneously to get accurate pollutant cloud parameter from measured spectrum. The acquisition of distortion parameters and the corresponding compensation method may be helpful for the recognition and quantification of infrared remote sensing signals.
吴 军,崔方晓,袁小春,李大成,李扬裕,王安静,郭腾霄. FTIR被动遥测信号中的线形函数建模及补偿方法[J]. 光谱学与光谱分析, 2019, 39(11): 3321-3325.
WU Jun, CUI Fang-xiao, YUAN Xiao-chun, LI Da-cheng, LI Yang-yu, WANG An-jing, GUO Teng-xiao. Line Shape Effect Modeling and Compensation for Passive Remote Sensing Signals of Fourier Transform Infrared Spectrometers. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(11): 3321-3325.
[1] Tremblay P, Savary S, Rolland M, et al. Standoff Gas Identification and Quantification from Turbulent Stack Plumes with an Imaging Fourier-Transform Spectrometer. Advanced Environmental, Chemical, and Biological Sensing Technologies Ⅶ, 2010. 1.
[2] Harig R, Gerhard M. Field Analytical Chemistry and Technology, 2001, 5(1-2): 75.
[3] De donato P, Barres O, Sausse J, et al. Remote Sensing of Environment, 2016, 175(1): 301.
[4] Raspollini P, Ade P, Carli B, et al. Applied Optics, 1998, 37(17): 3697.
[5] Hase F, Blumenstock T, Paton-walsh C. Applied Optics, 1999, 38(15): 3417.
[6] Kauppinen J, Saarinen P. Applied Optics, 1992, 31(13): 2353.
[7] Harig R. Applied Optics, 2004, 43(23): 4603.
[8] Genest J, Tremblay P. Applied Optics, 1999, 38(25): 5438.
[9] Griffiths R P, James A H. Fourier Transform Infrared Spectrometry. New Jersey: John Wiley & Sons, 2007.