Chapters 2, 3, and 4 have concentrated on the relationship between scatter and smooth-surface topography. However, another extremely useful application of light-scatter metrology is the detection and mapping of component defects that do not meet the smooth, clean, reflective conditions of mirror surfaces. Examples of such defects are surface contaminants, particulates, scratches, digs, coating globs, and residues. If a smooth surface is contaminated with very many defects, their combined scatter can dominate the surface BRDF as shown by Young (1976a, 1976b) in his study of particulate-contaminated mirrors. Nahm and Wolf (1986, 1987) also studied this problem, using a modified Mie theory. In measurement situations where scatter is being used to detect defects, surface scatter is considered background noise and the defect scatter is signal. Although defects often scatter more light per unit area than the surrounding surface topography, they may sometimes scatter considerably less total light because they have cross-sectional area much smaller than the illuminated spot, or because they are buried just beneath a reflective surface. In such cases, a low signal-to-noise ratio results. If it can be established that nontopographic defects scatter light differently than surface topography, then these differences can be exploited to improve signal to noise and map the defects, using the raster techniques described in Sec. 6.9. This chapter discusses the differences in topographic and defect scatter and outlines techniques that have been used to enhance defect detection.
One way that has been used to improve discrete-defect signal to noise is to cross-polarize the source and receiver. This technique has been employed successfully for a variety of applications. It has been used to separate the specular and diffuse return of radar signals from the moon (Mathis 1963) to infer the relative amounts of moon rock and dust. The cross-polarization technique is used as a standard scan to check for Lambertian scatter and subsurface scatter, as part of the Maxwell-Beard model for obtaining material signatures (Maxwell 1973; see Sec. 7.4.2).
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