Paper
6 September 2011 Detection of aircraft exhaust in hyperspectral image data
Sarah E. Lane, Leanne L. West, Gary G. Gimmestad, William L. Smith Sr., Edward M. Burdette
Author Affiliations +
Abstract
The use of a hyperspectral imaging system for the detection of gases has been investigated, and algorithms have been developed for various applications. Of particular interest here is the ability to use these algorithms in the detection of the wake disturbances trailing an aircraft. A dataset of long wave infrared (LWIR) hyperspectral datacubes taken with a Telops Hyper-Cam at Hartsfield-Jackson International Airport in Atlanta, Georgia is investigated. The methodology presented here assumes that the aircraft engine exhaust gases will become entrained in wake vortices that develop; therefore, if the exhaust can be detected upon exiting the engines, it can be followed through subsequent datacubes until the vortex disturbance is detected. Gases known to exist in aircraft exhaust are modeled, and the Adaptive Coherence/Cosine Estimator (ACE) is used to search for these gases. Although wake vortices have not been found in the data, an unknown disturbance following the passage of the aircraft has been discovered.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sarah E. Lane, Leanne L. West, Gary G. Gimmestad, William L. Smith Sr., and Edward M. Burdette "Detection of aircraft exhaust in hyperspectral image data", Proc. SPIE 8158, Imaging Spectrometry XVI, 81580O (6 September 2011); https://doi.org/10.1117/12.894078
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Cited by 1 scholarly publication.
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KEYWORDS
Detection and tracking algorithms

Gases

Digital filtering

Hyperspectral imaging

Image filtering

Algorithm development

Data modeling

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