基于辐亮度匹配的无人机载成像光谱仪外场光谱定标研究

针对可见光与近红外波段无人机载成像光谱仪,在保证精度的前提下,提出了一种快速优化二维反演算法,利用大气吸收特征作为参照,采用辐亮度匹配的方法,在不需要测量地面反射率数据的情况下,反演了成像光谱仪的重要光谱参数中心波长的偏移量和带宽变化量。利用2010年11月14日于内蒙古乌拉特前旗开展的无人机遥感载荷综合验证场科学实验数据,在实验室光谱定标基础上进行了外场光谱定标。算法时间、成本大大减少,反演效率比常规二维反演算法提高了近100倍。通过地面光谱靶标对定标结果进行验证,对带宽为7 nm左右的成像光谱仪外场定标精度可达到0.1nm,一般优于0.5 nm。

In-flight spectral calibration of UAV hyperspectral imager based on Radiance Matching

This paper proposes an optimized method for in-flight spectral calibration of UAV (Unmaned Aerial Vehicle) hyperspectral imager covering visible and near infrared band. Taking simulated radiance as reference spectrum, the method uses spectrum matching technique to retrieve the most important spectral parameters center wavelength and bandwidth. With the data in Urad Front Banner, Inner Mongolia on November 14th, 2010, hyper-spectral camera on UAV was calibrated based on the laboratory spectral calibration result. The efficiency of data process was 100 times that of normal algorithm. A method of accuracy evaluation with ground targets was also developed. The in-flight spectral calibration accuracy for a sensor with bandwidth of 7nm was proved to be better than 0.5nm.