复杂背景下被动FTIS定量遥感污染云团光谱

本文提出复杂背景下定量遥感污染云团光谱的算法。利用被动傅里叶变换红外光谱仪（ＦＴＩＳ）遥测目标气体和背景光谱数据及最小平方误差拟合方法，成功地解决了探测目标气体柱数密度和目标气体等效辐射温度。该处理方法不仅可用于特定污染云团的定量处理，而且可用于多种污染地区如发电厂、机场、城市交叉路口、垃圾处理站等对ＣＯ，ＣＯ２，ＮＯ，ＮＯ２，Ｎ２Ｏ，ＮＨ３，ＣＨ４，ＳＯ２，Ｈ２Ｏ，ＨＣＩ和ＨＣＨＯ等气体浓度的监测。最后，详细讨论了用该算法对模拟剂的处理结果。

Quantitatively Remote Sensing Detection of the Polluted Cloud Spectra the Complicated Environments by Passive Fourier Transform Infrared Spectrometer

A model of simulated spectra for pollution cloud in a complicated environment is proposed. Using large background and target-gas spectra which are measured by passive Fourier transform infrared spectrometer (FTIS) and least-squares fitting procedures, we have simulated successfully the spectra of pollution gas. Simultaneously, the feature Parameters for pollution cloud, column density and effective radiative temperature of gas are given. The system can be operated in many different air pollution locations, e.g., industrial plants, airports, crossroads, garbage-disposal sites, to determine passively the gas molecules concentrations of CO, CO2, NO, NO2, N2O, NH3, CH4, SO2, H2O, HCl and HCHO in plumes. Finally, we discuss in detail the simulated results for simulant.