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Study on Inverse Estimation of Radiative Properties from Directional Radiances by using Statistical RPSO Algorithm

机译:基于统计RPSO算法的定向辐射辐射特性逆估计研究

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Infrared signals are widely used to discriminate objects against the background. Prediction of infrared signal from an object surface is essential in evaluating the detectability of the object. Appropriate and easy method of procurement of the radiative properties such as the surface emissivity, bidirectional reflectivity is important in estimating infrared signals. Direct measurement can be a good choice but a costly and time consuming way of obtaining the radiative properties for surfaces coated with many different newly developed paints. Especially measurement of the bidirectional reflectivity usually expressed by the bidirectional reflectance distribution function (BRDF) is the most costly job. In this paper we are presenting an inverse estimation method of the radiative properties by using the directional radiances from the surface of concern. The inverse estimation method used in this study is the statistical repulsive particle swarm optimization (RPSO) algorithm which uses the randomly picked directional radiance data emitted and reflected from the surface. In this paper, we test the proposed inverse method by considering the radiation from a steel plate surface coated with different paints at a clear sunny day condition. For convenience, the directional radiance data from the steel plate within a spectral band of concern are obtained from the simulation using the commercial software, RadthermIR, instead of the field measurement. A widely used BRDF model called as the Sandford-Robertson(S-R) model is considered and the RPSO process is then used to find the best fitted model parameters for the S-R model. The results obtained from this study show an excellent agreement with the reference property data used for the simulation for directional radiances. The proposed process can be a useful way of obtaining the radiative properties from field measured directional radiance data for surfaces coated with or without various kinds of paints of unknown radiative properties.
机译:红外信号被广泛用于区分背景物体。来自物体表面的红外信号的预测对于评估物体的可检测性至关重要。适当,简便的方法来获取辐射特性,例如表面发射率,双向反射率,对于估算红外信号很重要。直接测量可能是一个不错的选择,但要获得涂有许多新近开发的涂料的表面的辐射性能,则是一种昂贵且费时的方法。特别是通常由双向反射率分布函数(BRDF)表示的双向反射率的测量是最昂贵的工作。在本文中,我们提出了一种使用来自关注表面的方向辐射率的辐射特性的逆估计方法。本研究中使用的逆估计方法是统计排斥粒子群优化(RPSO)算法,该算法使用从表面发射和反射的随机选择的方向辐射数据。在本文中,我们通过在晴朗的晴天条件下考虑涂有不同涂料的钢板表面的辐射来测试所提出的逆方法。为方便起见,使用商业软件RadthermIR代替现场测量从仿真中获得了所关注光谱带中来自钢板的定向辐射数据。考虑了广泛使用的称为Sandford-Robertson(S-R)模型的BRDF模型,然后使用RPSO过程为S-R模型找到最佳拟合模型参数。从这项研究中获得的结果表明,与用于定向辐射度模拟的参考特性数据非常吻合。所提出的方法可以是从现场测量的定向辐射数据获得辐射特性的有用方法,该表面辐射的表面涂覆或不涂覆各种未知辐射特性的涂料。

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