FTIR被动遥测信号中的线形函数建模及补偿方法

被动遥测红外信号的精确解译，对远距离、非接触获取污染云团信息具有重要意义。然而，测量过程中的光谱畸变阻碍了这一目的的达成。针对遥测信号中的谱线畸变问题，提出了一种利用线形函数模型自适应补偿傅里叶变换红外光谱仪光谱线形函数的方法。通过对傅里叶变换光谱仪线形函数的成因分析，结合实际仪器设计参数，从理想线形函数、固有线形函数和相位误差三个方面构建线形函数模型；在此基础上，以实测畸变光谱与理论仿真光谱的均方误差作为代价函数，利用迭代优化方法实现了对实际线形函数关键参数进行估算的算法流程；将重构得到的线形函数应用于理论光谱补偿，显著减少了理论仿真光谱与实测光谱之间的差异。分析结果表明，理想线形函数主要影响谱线展宽及旁瓣幅值；固有线形函数造成向低频方向的非对称展宽；而相位误差则会造成谱峰非对称。必须在理论仿真光谱中综合考虑三种来源线形函数的贡献，才能有效建立测量光谱和待反演云团参数之间的联系。实际线形函数畸变参数的获取和补偿应用，有助于提高红外遥测信号的定量解译水平。

Line Shape Effect Modeling and Compensation for Passive Remote Sensing Signals of Fourier Transform Infrared Spectrometers

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.