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北京跟踪与通信技术研究所 北京,100094
收稿日期:2015-03-06,
修回日期:2015-05-07,
纸质出版日期:2015-08-25
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战永红, 刘卿, 杨迪等. 表面粗糙材质的复折射率反演[J]. 光学精密工程, 2015,23(8): 2178-2184
ZHAN Yong-hong, LIU Qing, YANG Di etc. Inversion of complex refractive index for rough-surface objects[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2178-2184
战永红, 刘卿, 杨迪等. 表面粗糙材质的复折射率反演[J]. 光学精密工程, 2015,23(8): 2178-2184 DOI: 10.3788/OPE.20152308.2178.
ZHAN Yong-hong, LIU Qing, YANG Di etc. Inversion of complex refractive index for rough-surface objects[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2178-2184 DOI: 10.3788/OPE.20152308.2178.
由于目标偏振特性研究中表面粗糙材质的复折射率很难准确反演
本文对常用的Vimal-Milo反演法进行了改进。分析了粗糙表面的偏振二向反射特性
指出了Vimal-Milo法采用的"偏振度-角度相关"反演模式的不足。然后
提出了基于"相对偏振分量-角度相关"的反演方法
推导出复折射率的反演公式
并设计了对应的全局搜索算法。最后
利用绿漆及铝板的偏振特性测试数据
对提出的复折射率反演算法进行了验证
并基于此对偏振二向反射特性进行了正向推演验证。反演数据表明:使用本文提出的复折射率反演方法
表面粗糙铝板的复折射率的反演精度较Vimal-Milo法有了显著提高
实部和虚部与真值的误差均在 0.01以内
且评价因子小于0.07;推演数据表明:表面相对光滑的绿漆的偏振二向反射亮度的推演结果为Vimal-Milo法得到的均方根误差的1/5
与测试数据的误差在0.01以内。得到的结果证明本文所提复折射率反演方法可用于光滑及粗糙表面材质的复折射率反演。
As the complex refractive index of a rough-surface object is difficult to be inverted precisely
the current Vimal-Milo method for inversion was improved in this paper. The characteristics of the polarimatic bidirectional reflection from the rough surface were analyzed
and the defects of current Vimal-Milo method with a mode of "polarization ratio-angle correlation" were pointed out. Then
a improved Vimal-Milo inversion method was proposed based on the model of "relative polarization component-angle correlation". The inversion formula for the complex index was derived and a global searching was designed. According to the measurement data of polarization characteristics from green paint and aluminum
the inversion algorithm for the complex index was verified and the polarimatic bidirectional reflection characteristics of materials were also verified by the forward deducing and inverting. The inversion data with proposed method show that the inversion precision of the complex index of rough-surface aluminum has more improved than that of the Vimal-Milo method and the parameter errors for real and imaginary parts are within 0.01 with the assessment index less-than 0.07. The inversion data by the forward deducing and inverting show that the error of radiance intensity of green paint has decreased 5 times that of Vimal-Milo method
and the difference from measuring data is within 0.01. These results all demonstrate that proposed inverting method can be used in the inversion for complex indexes of rough-surface objects and flat-surface objects.
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