Surface texture optimization for low infrared-glint coatings Baker... · 2017-09-29 · Visible...
Transcript of Surface texture optimization for low infrared-glint coatings Baker... · 2017-09-29 · Visible...
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Surface texture optimization for low infrared-glint coatingsShape, SHINE, shadow, sound, silhouette spacing, sudden movement (singing, smoking, smell, etc. )
IOM3 DSSC Advances in Camouflage Science and Engineering
London, March 15th 2016
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Mr. Chris Baker |
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Dr. Eoin O’Keefe |
Presented by
STAAR lab External integrating sphere and hot stage mounted on Nicolet 6700 FTIR
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Why is ‘SHINE’ still important?
• Planar ‘manmade’ surfaces exhibit strong specular reflection under near-grazing illumination and observation geometries, causing ‘glint’ from point sources and ‘glare’ from extended sources.
• Naturally occurring organic and terrain materials are typically non-planar, and do not exhibit significant glint or glare.
• Glint is a strong indicator to the presence of manmade surfaces in a natural scene and are often the first detection feature - visible from long ranges.
• Glare causes colours to lighten and loose chroma until ‘almost white’ – not ideal if you are hiding against a dark background.
• Glint and glare both occur at all wavelengths across the Electro Optic spectrum, including the thermal infrared.
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Outline
• Determine the minimum possible surface ‘roughness’ to minimize the effects of glint and specular reflections at Thermal IR wavelengths.
• Explore surface structure parameters that have a dominant impact on the reflection of light.
• Identify reflection models, both for the generation of reflected data with respect to surface structure, and generalized / parameterised BRDF models.
• A field study using low glint/glare painted panels to obtain data from a real-world situation containing both positive and negative contrast reflections.
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Coatings and Glint / Glare
• Dominated by the texture or shape of the first air-solid interface and refractive index change at the interface.
• Surfaces that are locally smooth with respect to illumination wavelength – ‘specular’ or ’gloss’ (e.g. glass windscreens).
• Surfaces that are locally rough with respect to illumination wavelength – ‘diffuse’ or ‘matt’ (e.g. painted steel).
• ‘Gloss’ paints contain small particulates in an excess of binder that forms a smooth surface on cure.
• ‘Matt’ paints contain larger particles in less binder that conforms to the surface particles, resulting in a micro-or macro-scopically rough first air-solid interface.
Gloss paint Matt paint
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Surface roughness
• RMS surface roughness (σrms) can have the same value for very different surfaces and doesn’t consider the spatial distribution. Combining σrms with correlation length (τ, the point at which a change in height is no longer related to nearest neighbours) gives a surface roughness ‘slope’ - denoted ‘effective roughness’ in this presentation.
• Wavelength dependence of scatter on ‘surface roughness’:
• Where the wavelength >> “roughness” the surface is optically specular.
• Where wavelength << “roughness”, the surface is treated as rough and reflections can be estimated as a function of the geometrical surface.
• Where wavelength ~ “roughness”, physical optics must be used and estimation becomes more challenging due to diffractive effects.
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Diffuse low glint /glare
• A ‘perfect’ diffuse or ‘Lambertian’ surface reflects an incident ray equally over all angles over 2πsr. This can be achieved for a Normal illuminated surface with a homogeneous distribution of all instantaneous reflection or diffracted angles up to π/4 sr.
• ‘Diffuse’ could be an undulating mirror surface which will glint and glare at low angles of illumination.
• Consider a paint that contains a number of angular particles, with the larger particles proud of the mean surface.
• As the illumination approaches grazing, peaks will cast shadows over the area between the peaks, and then the lower slopes of the large particles, until the radiation only impinges the tallest peaks.
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Specular reflection:exemplar surfaces
• Aluminium coated abrasive papers with different particle sizes. Characterised on SOC 100 HDR.
• Rapid drop in the specular componentof reflection as a function of surfaceroughness.
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• Micro-structured abrasive film samples have provided a more consistent material set to allow the effects of surface roughness on specular/diffuse IR reflectance to be observed.
• This data set shows again that surface roughness is not consistent in describing a surfacestructure and that other parameters are required. The abrasive films achieve low glint properties with a finer surface texture.
• It would be beneficial to reproduce this performance in paints and applique treatments.
Abrasive film roughness vs. IR reflectance
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Surface topography and scatter
• Paints with different surface roughnesses were characterised on a ZeMetrics ZeScope white light interferometer to estimate the RMS roughness and correlation length.
• HDR characterised on a SOC-100; specular and diffuse components of reflection calculated at a range of reflection angles.
Sample with RMS roughness 3.98µm
Sample with RMS roughness 74.52µm
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Relating topography and scatter
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Painted panels:preparation and experiment
• Fibreglass panels were spray-painted at QinetiQ in a conventional dark green shade (left, 1) and 3 textured paints (2-4), formulated by PPG Aerospace (Shildon) in the same dark green shade.
1 2 3 4
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2
3
4
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Visible band Beckmann Spizzichino fit to BRDF data using model.
BRDF modelling
• IR BRDF (SOC 200) measurement data set collected and used in combination with the HDR data (SOC 100).
• Comparison of existing reflection models for use in the IR domain.
• The Beckmann Spizzichino model aims to predict BRDF using wave optics –generally a poor fit to measurements, and exhibits inconsistencies at grazing angles.
• The Torrance–Sparrow model can be used to parameterise BRDF data, using a micro-facet approach to describing the surface.
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Painted panels : analysis (VIS)
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4
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Painet panels: analysis (MWIR)
• The BRDF (solid line) shows an increase in the specular lobe as the wavelength increases.
• Torrance-Sparrow fit (dashed line).
MWIR (3-5 micron)
Fit optimised for all 3 incident angles, not individual angles.
𝑇𝑆𝐵𝑅𝐷𝐹 = 𝑘𝑑 ∗ cos 𝜃𝑖 + 𝑘𝑠 ∗𝐹
4𝜋∗
𝐷
cos 𝜃𝑖∗
𝐺
cos 𝜃𝑅Where F is the Fresnel term, D is the slope distribution and G is the shadowing/masking term. 𝑘𝑑 and 𝑘𝑠 are free parameters, along with the slope distribution 𝑚 which is used in the calculation of D and the refractive index 𝑛 used in the calculation of F. As such, 𝑘𝑑, 𝑘𝑠, 𝑚 and 𝑛 are the Torrance-Sparrow parameters.
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Painted panels: analysis (LWIR)
• BRDF increasingly specular, however:
– LWIR images show less glint
– Glare and self-radiation dominate glint
LWIR (8-12 micron)
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4
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Any Questions?