随机惯性权重微粒群算法的BRDF参数反演  

BRDF parameter inversion based on the Stochastic Inertia Weight Particle Swarm Optimization algorithm

作　　者：孙建平 齐宏[1] 王申领 赵松庆[2,3] 郝燕云 吴根水 SUN Jianping;QI Hong;WANG Shenling;ZHAO Songqing;HAO Yanyun;WU Genshui(School of energy science and engineering,Harbin Institute of Technology,Harbin 150001,China;China air to Air Missile Research Institute,Luoyang Henan 471009,China;Key Laboratory of aviation guidance weapons,Luoyang Henan 471009,China)

机构地区：[1]哈尔滨工业大学能源与科学工程学院,哈尔滨150001 [2]中国空空导弹研究院,河南洛阳471009 [3]航空制导武器航空重点实验室,河南洛阳471009

出　　处：《激光杂志》2021年第2期5-9,共5页Laser Journal

基　　金：航空科学基金(No.20170177002)。

摘　　要：材料表面的反射特性一般由双向反射分布函数(BRDF)表征,其理论计算模型已大体满足实际需要。随着计算机计算速度与效率的提升,结合实验数据利用智能优化算法反演BRDF理论计算模型的未知参数,以此获得材料表面BRDF分布的方法逐渐成为研究主流。对于BRDF理论计算模型中的Schlick计算模型和Cook-Torrance计算模型,基于实验数据利用随机惯性权重微粒群算法分别对铝合金和钛合金的未知参数进行反演计算,并与实验数据进行了比较。结果表明,Schlick计算模型可以更好地表征铝合金与钛合金材料的表面反射特性。The material surface’s reflection characteristics are generally characterised by bidirectional reflectance distribution function(BRDF),and its theoretical calculation model has generally met the practical needs.With the improvement of computer computing speed and efficiency,using an intelligent optimisation algorithm to retrieve the unknown parameters of the BRDF theoretical calculation model combined with experimental data has gradually become the mainstream of research.In this paper,based on the experimental data,the alloy’s weight was calculated by using the theoretical data of the particle model and the experimental data.The results show that Schlick calculation model can better characterise the surface reflection characteristics of aluminium alloy and titanium alloy.

关 键 词：双向反射分布函数(BRDF) 随机惯性权重微粒群算法 参数反演 铝合金 钛合金 

分 类 号：TN209[电子电信—物理电子学]