摘要
自然地物的红外特征数据在伪装、遥感等领域有着重要的作用。由于仪器所采集的信号种类繁多,自然地物表面性质复杂,热传导能力较差,难以直接准确获得自然地表物体光谱发射率曲线,需要特殊的算法通过自然地物的辐射亮度曲线间接得到其表面温度和发射率曲线。分离算法主要有最大发射率法、黑体拟合法以及光谱平滑法。光谱平滑法由于操作简单,计算准确,是目前应用最广泛的分离算法。在光谱平滑法的基础上,利用美国D&P公司的Model 102F快速傅立叶变换红外光谱分析仪对3种典型自然地物(裸露的土壤、草地、树木)进行红外特征数据采集。结果表明,自然地物的表面温度随时间变化产生显著的变化,而其发射率水平则近似保持恒定。
The character infrared data of natural objects plays an important role in the fields of camouflage and remote sensing. As the various signal and the complicated property of natural objects＇ surface and its bad ability of heat exchange, acquiring the surface temperature and emissivity direct and correctly is difficult, and special separate algorithms should be needed to computer the surface temperature and emissivity using the data of objects＇ radiance. The separate algorithms include maximal emissivity method, blackbody fixing method and spectra smoothing method. Spectra smoothing method is used widely at present because of its simple operation and exact result. Based on the spectra smooth method, we have utilized the FT-IR Spectrometers of D＆P instruments to collect the character infrared data of three typical natural objects （soil, meadow and trees）. The result shows that, accompanying with the change of temperature, the surface temperature changed remarkably whereas the emissivity almost keeps constantly.
出处
《红外技术》
CSCD
北大核心
2009年第4期210-214,共5页
Infrared Technology
关键词
自然地物
表面温度
发射率
光谱平滑法
natural objects
surface temperature
emissivity
spectra smoothing method
