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Proceedings Paper

Detection of aircraft exhaust in hyperspectral image data
Author(s): Sarah E. Lane; Leanne L. West; Gary G. Gimmestad; William L. Smith; Edward M. Burdette
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Paper 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.

Paper Details

Date Published: 7 September 2011
PDF: 8 pages
Proc. SPIE 8158, Imaging Spectrometry XVI, 81580O (7 September 2011); doi: 10.1117/12.894078
Show Author Affiliations
Sarah E. Lane, Georgia Tech Research Institute (United States)
Leanne L. West, Georgia Tech Research Institute (United States)
Gary G. Gimmestad, Georgia Tech Research Institute (United States)
William L. Smith, Hampton Univ. (United States)
Edward M. Burdette, Georgia Tech Research Institute (United States)


Published in SPIE Proceedings Vol. 8158:
Imaging Spectrometry XVI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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