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地基望远镜对空间目标的长焦距红外成像能够得到空间目标的温度区域分布信息,然而成像过程的未知参量将降低传统的双波段比色测温法正向求解精度。未知参量包括目标发射率、大气透过率、地球热辐射等。文中建立了基于多波段红外探测器测量电子数的贝叶斯估计评价函数模型,能够比较精确地反向求解空间目标的真实温度分布;并推导了目标参量估计函数的克拉美.罗界,能够预测一系列不确定因素对其温度和发射率等参数求解精度的影响;最后进行了算法的仿真实验与分析。
However, the unknown parameters of the imaging process will reduce the accuracy of the forward analysis of the traditional dual-band colorimetric pyrometry method. However, the long-distance infrared imaging of the space target by the ground-based telescope can obtain the temperature distribution information of the spatial target. Unknown parameters include the target emissivity, atmospheric transmittance, the earth’s thermal radiation and so on. In this paper, a Bayesian estimation evaluation function model based on multi-band infrared detector for measuring the number of electrons is established, which can reverse the true temperature distribution of the space target accurately and derive the Kramera-Rao boundary of the target parameter estimation function. Predict the influence of a series of uncertain factors on the accuracy of parameters such as temperature and emissivity. Finally, the simulation experiment and analysis of the algorithm are carried out.