各向异性介质辐射特性参数联合反演

本文基于BP神经网络方法结合蒙特卡洛和BEER定律辐射传输模拟方法建立了联合反演各向异性散射介质的辐射特性参数模型。首先采用半球透射率结合半球反射率反演模型反演了各向同性介质的吸收系数和散射系数,在此基础上增加准直透射率,建立了联合反演各向异性介质的吸收系数、散射系数和散射不对称因子三参数联合反演模型。反演结果表明该模型能准确反演出介质辐射特性参数,具有实用意义。此外,为了检验测量误差对模型的反演准确性的影响,分别在不同程度测量误差情况下进行反演,结果显示测量误差对散射不对称因子反演值影响较大。

Joint Inversion of Radiative Properties of Anisotropic Medium

The joint inverse model of radiative characteristic parameters of anisotropic scattering medium was established used BP neural network method combined with the Monte Carlo method and BEER law.Firstly,the scattering and absorption coefficients of the isotropic medium were inversed by the combination of the hemispherical transmittance and reflectance,then the collimated transmittance was added to the measurement pa rameters.The absorption coefficient,scattering coefficient and scattering asymmetry factor of anisotropic medium were inversed by the joint inverse model based on the hemispherical transmittance,reflectance and collimated transmittance.The inverse results show that this model,which has practical significance,can inverse three radiative characteristic parameters of anisotropic medium accurately.What's more,the measurement error was taken into account.In the case of different degree of measurement error,the results show that the measurement error has a great influence on the inversion of the scattering asymmetry factor.