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粗糙目标表面红外偏振特性研究

柳祎 史浩东 姜会林 李英超 王超 刘壮 李冠霖

柳祎, 史浩东, 姜会林, 李英超, 王超, 刘壮, 李冠霖. 粗糙目标表面红外偏振特性研究[J]. , 2020, 13(3): 459-471. doi: 10.3788/CO.2019-0123
引用本文: 柳祎, 史浩东, 姜会林, 李英超, 王超, 刘壮, 李冠霖. 粗糙目标表面红外偏振特性研究[J]. , 2020, 13(3): 459-471. doi: 10.3788/CO.2019-0123
LIU Yi, SHI Hao-dong, JIANG Hui-lin, LI Ying-chao, WANG Chao, LIU Zhuang, LI Guan-lin. Infrared polarization properties of targets with rough surface[J]. Chinese Optics, 2020, 13(3): 459-471. doi: 10.3788/CO.2019-0123
Citation: LIU Yi, SHI Hao-dong, JIANG Hui-lin, LI Ying-chao, WANG Chao, LIU Zhuang, LI Guan-lin. Infrared polarization properties of targets with rough surface[J]. Chinese Optics, 2020, 13(3): 459-471. doi: 10.3788/CO.2019-0123

粗糙目标表面红外偏振特性研究

doi: 10.3788/CO.2019-0123
基金项目: 国家重点研发计划(No. 2017YFC0803806);国家自然基金青年基金(No. 61805027,No. 61805028)
详细信息
    作者简介:

    柳 祎(1995—),女,吉林长春人,硕士研究生,2017年于长春理工大学获得学士学位,主要从事光学系统设计方面的研究。E-mail:452414737@qq.com

    姜会林(1945—),男,辽宁辽中人,博士,教授,博士生导师,中国工程院院士,应用光学专家。E-mail: hljiang@cust.edu.cn

  • 中图分类号: O436.3

Infrared polarization properties of targets with rough surface

Funds: Supported by National Key Research and Development Program (No. 2017YFC0803806); National Natural Science Foundation of China Youth Fund (No. 61805027, No. 61805028)
More Information
  • 摘要: 红外偏振成像可突显目标、识别真伪,准确掌握目标红外辐射偏振特性可有效提高目标的探测识别概率。针对现有目标红外辐射偏振特性模型未考虑粗糙表面导致的遮蔽效应的问题,本文基于微面元双向反射分布函数模型,利用穆勒矩阵构建出含有遮蔽函数的粗糙表面红外辐射偏振度的斯托克斯解析模型。针对光线表面粗糙度和入射角对金属和非金属目标红外辐射偏振度的影响进行定量分析。分析结果表明:无论是金属还是非金属,其红外自发辐射偏振度都随粗糙度的增大而减小,非金属自发辐射偏振度下降的幅度大于金属偏振度;当粗糙度及温度相同时,金属的红外辐射偏振度始终大于非金属;红外辐射偏振度先随入射角的增加而增加,而后在特定入射角下达到峰值,超过一定入射角后,偏振度大幅下降,金属和非金属的红外辐射偏振度间的差异在一定入射角度范围内将达到最大,这有助于区分金属与非金属。最后,利用长波红外微偏振成像系统和近红外偏振成像系统进行不同场景目标的图像采集,获取目标的红外辐射偏振特性,实验结果与理论分析结果基本吻合。本文对研究目标偏振特性、优化设计红外偏振系统以及后续偏振图像处理均具有重要意义。

     

  • 图 1  微面元双向反射分布函数模型几何关系示意图

    Figure 1.  Schematic diagram of geometric relationship for bidirectional reflection distribution function model of microelement

    图 2  同时发生掩饰-遮蔽效果示意图

    Figure 2.  Schematic diagram of simultaneous shadowing masking effect

    图 3  随入射角与散射角变化的遮蔽函数曲线

    Figure 3.  Shadowing function varying with incident and reflective angles

    图 4  金属铝与玻璃板的自发辐射偏振度随粗糙度的变化曲线

    Figure 4.  Changes of spontaneous emission polarization degree of aluminum and glass plate as roughness

    图 5  有无遮蔽函数模型时金属铝偏振度随入射角变化曲线

    Figure 5.  Changes of polarization degree of metal aluminum with different surface roughnesses as incident angle with and without shadowing function

    图 6  有无遮蔽函数模型时玻璃板偏振度随入射角变化曲线

    Figure 6.  Changes of polarization degree curve of glass plate with different surface roughnesses as incident angle with and without shadowing function

    图 7  不同粗糙度下两种材质的偏振度变化曲线

    Figure 7.  Degrees of polarization of two materials with different roughnesses varying with incident angle

    图 8  铝(a)和玻璃(b)的红外偏振度实际测量值与仿真对比图

    Figure 8.  Comparison diagrams of actual measured values and simulation values of infrared polarization degree for (a) aluminum and (b) glass

    图 9  不同粗糙度的铝片和玻璃的长波红外偏振度图像(a)铝片 (b)玻璃板

    Figure 9.  Long-wave infrared polarization images of aluminum sheets (a) and glass plates (b) with different roughnesses

    图 10  室外景物图像(a) 及长波红外强度图像 (b) 的长波红外偏振度图像

    Figure 10.  Long wave infrared polarization images of outdoor scenes (a) and long wave infrared intensity image (b)

    图 11  具有不同粗糙度铝片的灰度图像(a)与近红外偏振度图像(b)

    Figure 11.  Gray image (a) and near infrared polarization image (b) of aluminum sheets with different roughnesses

    图 12  不同粗糙度的玻璃板灰度图像(a)与近红外偏振度图像(b)

    Figure 12.  Gray image (a) and near infrared polarization image (b) of glass plates with different roughnesses

    图 13  室外景物拍摄的图像。(a)红外强度图像;(b)入射角为80°时红外偏振度图像;(c)入射角为70°时红外偏振度图像;(d)入射角为20°时红外偏振度图像

    Figure 13.  Outdoor scenes. (a) Infrared intensity image; infrared polarized image at incident angles of 80° (b), 70° (c), 20° (d)

    图 14  不同入射角下的屋顶偏振度

    Figure 14.  Polarization degrees of the roof at different incident angles

    表  1  成像系统主要技术参数

    Table  1.   Main technical parameters of the imaging system

    Long-wave infrared
    micro-polarization camera
    Near infrared detector
    Wavelength/μm8~120.9~1.7
    Focal length/mm6050
    F11.4
    Pixel number640×512640×512
    Pixel size/μm1715
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出版历程
  • 收稿日期:  2019-06-10
  • 修回日期:  2019-08-09
  • 刊出日期:  2020-06-01

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