Paper
5 May 2005 UAV visual signature suppression via adaptive materials
Ron Barrett, Joris Melkert
Author Affiliations +
Abstract
Visual signature suppression (VSS) methods for several classes of aircraft from WWII on are examined and historically summarized. This study shows that for some classes of uninhabited aerial vehicles (UAVs), primary mission threats do not stem from infrared or radar signatures, but from the amount that an aircraft visually stands out against the sky. The paper shows that such visual mismatch can often jeopardize mission success and/or induce the destruction of the entire aircraft. A psycho-physioptical study was conducted to establish the definition and benchmarks of a Visual Cross Section (VCS) for airborne objects. This study was centered on combining the effects of size, shape, color and luminosity or effective illumance (EI) of a given aircraft to arrive at a VCS. A series of tests were conducted with a 6.6ft (2m) UAV which was fitted with optically adaptive electroluminescent sheets at altitudes of up to 1000 ft (300m). It was shown that with proper tailoring of the color and luminosity, the VCS of the aircraft dropped from more than 4,200cm2 to less than 1.8cm2 at 100m (the observed lower limit of the 20-20 human eye in this study). In laypersons terms this indicated that the UAV essentially "disappeared". This study concludes with an assessment of the weight and volume impact of such a Visual Suppression System (VSS) on the UAV, showing that VCS levels on this class UAV can be suppressed to below 1.8cm2 for aircraft gross weight penalties of only 9.8%.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ron Barrett and Joris Melkert "UAV visual signature suppression via adaptive materials", Proc. SPIE 5762, Smart Structures and Materials 2005: Industrial and Commercial Applications of Smart Structures Technologies, (5 May 2005); https://doi.org/10.1117/12.599056
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Unmanned aerial vehicles

Visualization

Virtual colonoscopy

Electroluminescence

Fourier transforms

Infrared signatures

Clouds

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