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利用模拟数据,评价Autonomous Atmospheric Compensation(AAC)算法的抗噪性,认为AAC算法的抗噪性较弱。基于TASI实测数据,利用AAC算法开展反演计算时,计算结果呈现出多样性问题。结合In-scene Atmospheric Compensation(ISAC)算法中黑体像元的标定方法,提出了一种复合改进算法。首先,利用ISAC算法反演的大气透过率和路径辐射,重新计算AAC算法中大气透过率之比(Tr)和相邻两强弱吸收通道的路径辐射之差(Pd),再次,运用经验公式获得稳定的大气反演结果(大气透过率和路径辐射),有效解决了计算结果多样性的问题。利用复合改进算法,开展的温度与发射率分离实验,证明反演得到的发射率波谱更接近野外实测波谱。
Using the simulation data, we evaluate the noise immunity of the AAC algorithm, and consider the noise immunity of the AAC algorithm as weak. Based on the measured data of TASI, the calculation results show the diversity problems when using the AAC algorithm to carry out inversion calculation. Combined with the calibration method of blackbody pixels in In-scene Atmospheric Compensation (ISAC) algorithm, a composite improved algorithm is proposed. First, the atmospheric transmittance and path radiation retrieved by the ISAC algorithm are used to recalculate the difference (Tr) between the atmospheric transmittance and the path radiation of the two adjacent strong and weak absorption channels in the AAC algorithm. Thirdly, Empirical formula to obtain a stable atmospheric inversion results (atmospheric transmittance and path radiation), effectively solve the problem of the diversity of the results. Using the composite improved algorithm, the experiments of temperature and emissivity separation are carried out to prove that the retrieved emissivity spectrum is closer to the field measured spectrum.