污染气体扫描成像红外被动遥测系统实时数据处理研究

使用红外被动遥测技术可实现污染气体的远程监控和预警. 该技术应用过程中, 获取背景辐射是进行定量解析的关键, 在已有的应用中, 多采用同条件测量法和上风口测量方法获取背景光谱和环境光谱, 但这些方法均需要提前或者同时测量无目标物的背景光谱, 难以在实际应用中满足快速响应的需求. 本文基于红外辐射传输模型分析, 通过研究在800–1200 cm^-1波段内的实测光谱中同时包含目标、背景和环境辐射的基本原理, 采用了一种不需要事先测量背景的目标特征的背景光谱实时提取算法, 通过将该方法应用于自主研制的污染气体扫描成像红外被动遥测系统, 以六氟化硫为示踪气体, 开展了遥测验证实验. 将获取的浓度数据与应用同条件测量法获取的数据进行了比较, 结果显示两者的相关系数平方值达到0.99, 表明该方法切实可行, 可有效提高系统的响应速度和适用范围. 关键词： 傅里叶变换红外光谱 被动遥测 实时光谱提取算法

Real-time data processing of remote measurement of air pollution by infrared passive scanning imaging system

Infrared passive remote sensing allows remote monitoring and early warning of air pollution. The key to the quantitative resolution is to obtain the background radiation in application process. The existing methods (such as measuring the background and atmosphere radiance spectrum in the same condition or uptake) need in advance or at the same time to measure the background spectrum without target. So, they are difficult to satisfy the demand for rapid response in the practical application. According to the infrared radiation transmission model analysis and by studying the principle of measured spectrum in the 800-1200 cm^-1 band containing the target, background and environmental radiation, we propose a real-time spectrum extraction algorithm that does not require to measure the background target feature. The method is applied to the developed polluting gas scanning imaging passive FTIR system. The remote sensing of SF₆ is done. Concentration data and the data obtained by the method at the same condition are compared, and the results show that the correlation coefficient squared value reaches 0.99, indicating that the method is feasible, which can effectively improve the response speed of the system and the scope of application.
Keywords： Fourier transform infrared spectroscopy passive remote sensing real-time spectrum extraction algorithm