Volume 17 Issue 3
May  2024
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ZHANG LU, FAN Jin-hao, LU Yu-xuan, ZHANG Lei, FU Li. Infrared reflection characteristics of the wall solved by improved whale optimization algorithm[J]. Chinese Optics, 2024, 17(3): 595-604. doi: 10.37188/CO.2023-0095
Citation: ZHANG LU, FAN Jin-hao, LU Yu-xuan, ZHANG Lei, FU Li. Infrared reflection characteristics of the wall solved by improved whale optimization algorithm[J]. Chinese Optics, 2024, 17(3): 595-604. doi: 10.37188/CO.2023-0095

Infrared reflection characteristics of the wall solved by improved whale optimization algorithm

doi: 10.37188/CO.2023-0095
Funds:  Supported by National Natural Science Foundation of China (No. 61074090); Liaoning Provincial Department of Education Series Projects (No. JYT2020107)
More Information
  • Corresponding author: ffulli@163.com
  • Received Date: 13 Jul 2023
  • Rev Recd Date: 25 Aug 2023
  • Accepted Date: 16 Nov 2023
  • Available Online: 16 Jan 2024
  • The infrared reflection characteristics of the wall are characterized and solved by the bidirectional reflectance distribution function (BRDF). BRDF measurement currently has two problems to be addressed: it requires much experimental data and accuracy is not high enough. By constructing the reflection characteristic test platform of the wall target, an MR170 Fourier infrared spectroradiometer was used to obtain the target radiance at the incident angle and each reflection angle in the 2−15 μm band. For the stealth target, the RBF network was used to fit the radiance at the bands of 3−5 μm and 8−14 μm to eliminate atmospheric interference. Then, the BRDF values of the stealth targets in the above two bands were obtained. To improve the accuracy of the BRDF model, an improved whale optimization algorithm (IWOA) was proposed to invert BRDF model parameters, and a reflectivity-solving method based on BRDF was designed. The IWOA has a good effect on the parameter inversion of the BRDF calculation model. According to the reflection method and applying the obtained BRDF data, the reflectance 0.5496 and the relative error 6.17% are obtained, which meet the engineering requirements.

     

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  • [1]
    NICODEMUS F E. Reflectance nomenclature and directional reflectance and emissivity[J]. Applied Optics, 1970, 9(6): 1474-1475. doi: 10.1364/AO.9.001474
    [2]
    宿德志, 刘亮, 吴世永, 等. 辐射耦合效应对目标红外偏振特性的影响[J]. 中国光学(中英文),2023,16(2):318-328. doi: 10.37188/CO.2022-0035

    SU D ZH, LIU L, WU SH Y, et al. Influence of radiation coupling effect on polarization characteristics of targets[J]. Chinese Optics, 2023, 16(2): 318-328. doi: 10.37188/CO.2022-0035
    [3]
    SCHLICK C. A customizable reflectance model for everyday rendering[C]. Proceedings of the Fourth Eurographics Workshop on Rendering, 1993.
    [4]
    PHONG B T. Illumination for computer generated pictures[J]. Communications of the ACM, 1975, 18(6): 311-317. doi: 10.1145/360825.360839
    [5]
    COOK R L, TORRANCE K E. A reflectance model for computer graphics[C]. Proceedings of the 8th Annual Conference on Computer Graphics and Interactive Techniques, ACM, 1981: 307-316,doi: 10.1145/800224.806819.
    [6]
    李铁, 王航宇, 王宏军. 目标表面BRDF统计建模中的遗传模拟退火算法[J]. 量子电子学报,2008,25(4):489-492. doi: 10.3969/j.issn.1007-5461.2008.04.019

    LI T, WANG H Y, WANG H J. Application of genetic simulated annealing algorithm in BRDF statistical modelling[J]. Chinese Journal of Quantum Electronics, 2008, 25(4): 489-492. doi: 10.3969/j.issn.1007-5461.2008.04.019
    [7]
    吴振森, 谢东辉, 谢品华, 等. 粗糙表面激光散射统计建模的遗传算法[J]. 光学学报,2002,22(8):897-901. doi: 10.3321/j.issn:0253-2239.2002.08.001

    WU ZH S, XIE D H, XIE P H, et al. Genetic algorithm for statistical modeling of laser scattering on rough surface[J]. Acta Optica Sinica, 2002, 22(8): 897-901. doi: 10.3321/j.issn:0253-2239.2002.08.001
    [8]
    杨玉峰, 吴振森, 曹运华. 一种实用型粗糙面六参数双向反射分布函数模型[J]. 光学学报,2012,32(2):0229001. doi: 10.3788/AOS201232.0229001

    YANG Y F, WU ZH S, CAO Y H. Practical six-parameter bidirectional reflectance distribution function model for rough surface[J]. Acta Optica Sinica, 2012, 32(2): 0229001. (in Chinese). doi: 10.3788/AOS201232.0229001
    [9]
    杨敏, 方勇华, 吴军, 等. 基于Kubelka-Munk理论的涂层表面多参量偏振双向反射分布函数模型[J]. 光学学报,2018,38(1):0126002. doi: 10.3788/AOS201838.0126002

    YANG M, FANG Y H, WU J, et al. Multiple-component polarized bidirectional reflectance distribution function model for painted surfaces based on Kubelka-Munk theory[J]. Acta Optica Sinica, 2018, 38(1): 0126002. (in Chinese). doi: 10.3788/AOS201838.0126002
    [10]
    李明哲, 赵继广, 杨帆. 基于统计与遗传算法的Cook-Torrance模型研究[J]. 装备学院学报,2016,27(1):116-121. doi: 10.3783/j.issn.2095-3828.2016.01.024

    LI M ZH, ZHAO J G, YANG F. Analysis on cook-Torrance model based on genetic algorithm and statistical method[J]. Journal of Equipment Academy, 2016, 27(1): 116-121. doi: 10.3783/j.issn.2095-3828.2016.01.024
    [11]
    孙建平, 齐宏, 王申领, 等. 随机惯性权重微粒群算法的BRDF参数反演[J]. 激光杂志,2021,42(2):5-9. doi: 10.14016/j.cnki.jgzz.2021.02.005

    SUN J P, QI H, WANG SH L, et al. BRDF parameter inversion based on the stochastic inertia weight particle swarm optimization algorithm[J]. Laser Journal, 2021, 42(2): 5-9. doi: 10.14016/j.cnki.jgzz.2021.02.005
    [12]
    LIU Y Y, DAI J J, ZHAO S S, et al. Optimization of five-parameter BRDF model based on hybrid GA-PSO algorithm[J]. Optik, 2020, 219: 164978. doi: 10.1016/j.ijleo.2020.164978
    [13]
    MIRJALILI S, LEWIS A. The whale optimization algorithm[J]. Advances in Engineering Software, 2016, 95: 51-67. doi: 10.1016/j.advengsoft.2016.01.008
    [14]
    罗一甲, 祝赫, 李潇涵, 等. 赤霞珠酿酒葡萄总酚含量的近红外光谱定量分析[J]. 光谱学与光谱分析,2021,41(7):2036-2042. doi: 10.3964/j.issn.1000-0593(2021)07-2036-07

    LUO Y J, ZHU H, LI X H, et al. Quantitative analysis of total phenol content in cabernet sauvignon grape based on near-infrared spectroscopy[J]. Spectroscopy and Spectral Analysis, 2021, 41(7): 2036-2042. doi: 10.3964/j.issn.1000-0593(2021)07-2036-07
    [15]
    DING H Q, WU ZH Y, ZHAO L CH. Whale optimization algorithm based on nonlinear convergence factor and chaotic inertial weight[J]. Concurrency and Computation:Practice and Experience, 2020, 32(24): e5949. doi: 10.1002/cpe.5949
    [16]
    ADITYA SHASTRY K, SANJAY H A. A modified genetic algorithm and weighted principal component analysis based feature selection and extraction strategy in agriculture[J]. Knowledge-Based Systems, 2021, 232: 107460. doi: 10.1016/j.knosys.2021.107460
    [17]
    ZHANG X M, LIN Q Y. Three-learning strategy particle swarm algorithm for global optimization problems[J]. Information Sciences, 2022, 593: 289-313. doi: 10.1016/j.ins.2022.01.075
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