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摘要: 基于激光散斑的目标探测技术是一种长期以来被人们忽略的激光探测技术，该技术将传统激光探测技术中视为噪声的激光散斑视为新的信息来源，通过分析激光散斑形成机理探究散斑统计特性与目标物理特性间的关系，并结合行之有效的分析反演方法来获得包括目标形状、尺寸、表面粗糙度以及动力学参数等信息。与传统激光探测技术相比，基于激光散斑的目标探测技术具有结构简单，对光学系统要求低，对目标表面物理特性及微动特性敏感等特点，目前已广泛应用于航天、医学、工业、军事等多个领域。本文对近年来各类基于激光散斑的目标探测技术进行了分类总结，对各类探测方法的用途和优缺点以及适用环境进行了对比分析，对未来基于激光散斑的目标探测方法的发展趋势加以分析。Abstract: Target detection technology based on laser speckles is a kind of laser detection technology that has been ignored for a long time. In this technology, the laser speckle, which is regarded as noise in the traditional laser detection technology, is used as a new source of information. By analyzing the formation mechanism of a laser speckle pattern, the relationship between the statistical characteristics and the physical characteristics of the target is explored, and the effective analysis and inversion methods are combined to obtain the target’s shape, size, surface roughness and dynamic parameters. Compared with traditional laser detection technology, target detection technology based on laser speckles has a simple structure, has low optical system requirements, is sensitive to the physical and fretting characteristics of the target’s surface, and has been widely used in aerospace, medicine, industry, military and other fields. This paper classifies and summarizes the various kinds of speckle-based target detection technologies from recent years, compares and analyzes their applications, advantages and disadvantages, as well as the environmental restrictions. Finally, this paper prospects the trend for the future development of target detection methods based on laser speckles.
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Key words:
- laser speckle /
- target detection /
- three-dimensional imaging /
- target recognition
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图 3 阶梯模型波长去相关示意图
Figure 3. Schematic diagram of wavelength decorrelation of the step model
图 4 激光经过（a）圆孔和（b）散射位相屏时所成图像
Figure 4. Images obtained when lasers passing through (a) a circular aperture and (b) a scattering phase screen
图 5 基于散斑相关的透过强散射介质的非侵入成像[48] 。（a）实验原理示意图；（b）初始散斑图像；（c）初始散斑图像的自相关；（d）重构图像；（e-g）理想的衍射极限自由空间成像
Figure 5. Non-invasive imaging through strong scattering media based on speckle correlation[48]. (a) Schematic diagram of experimental principle; (b) raw speckle image; (c) autocorrelation of raw speckle image; (d) reconstructed image; (e-g) ideal diffraction-limited free-space imaging
图 7 10个训练对象的（a）原始图像[51]及（b）对应的散斑图案。10个测试图像的（c）原始图像及（d）对应的散斑图案。基于（e）SVR方法和（f）模式匹配方法重构的目标像。
Figure 7. (a) Object images and (b) their measured speckle patterns for ten training examples. (c) Object images and (d) their measured speckle patterns for ten test examples. Reconstruction images obtained by (e) the SVR method and (f) the pattern matching method.
表 1 基于散斑的表面粗糙度探测方法对比
Table 1. Comparison of the surface roughness detection methods based on speckles
方法 优势 特点 缺陷 散斑对比度法 ------- 快速,非接触，非破坏性，光学装置简单，
可在线测量测量精度受限于被测表面的相关长度 镜像强度分量法 克服了对比度方法中
存在的精度极限问题更快的速度，更高的精度，依赖于镜像光分量 仅适用于测量有镜像回波的微粗糙表面 相关方法(角度相关和
光谱相关)更高的测量精度 更高的测量精度,对角度变化敏感 需要精确的角度校准，在非合作情况以及有机加工振动情况下探测精度差 散斑分形 更少的计算资源需求，
更简洁的光学装置对机加工过程敏感，可用于对材料和
机加工方式的识别探测精度还不能满足现有需求 
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