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Proceedings Paper

High-resolution spectral analysis and modeling of infrared ocean surface radiometric clutter
Author(s): John D. McGlynn; Kenneth K. Ellis; David Kryskowski
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Paper Abstract

The power or variance spectral properties of the ocean surface, in the infrared, have been investigated by a number of workers in the past. This paper summarizes the results of an analysis which extends previous results, obtained at spatial resolutions measured in tens of meters, to centimeter scale spatial wavelengths. The data were obtained with a common module HgCdTe FLIR radiometer with high spatial resolution (< 0.25 milliradians) and moderately high thermal sensitivity (<< 0.1 degree(s) C). The spatial resolution of the FLIR and large number of available scan lines per scene, for ensemble spectral averaging, permit computation of power spectra at centimeter scales with extremely low estimation variance. Prior to computation of the power spectra, the data were radiometrically corrected for instrument effects, atmospheric path radiance and transmission losses, and the OTF of the sensor. Both one- and two-dimensional power spectra were computed and parametrically evaluated by spectral factorization and characterized via linear predictive coding (LPC) to multipole autoregressive (AR) linear system models. This type of spectral characterization facilitates (1) correlation to dominant spectral components (i.e., system poles) with specific wavenumber regimes and ocean surface models; (2) simple characterization of large numbers of ocean surface spectra with a few parameters; and (3) generation of two-dimensional radiance map simulations by inversion of the linear system model. The results of this analysis are presented along with conclusions regarding agreement with previous studies, utility of the technique, and model validity.

Paper Details

Date Published: 1 July 1991
PDF: 10 pages
Proc. SPIE 1486, Characterization, Propagation, and Simulation of Sources and Backgrounds, (1 July 1991); doi: 10.1117/12.45757
Show Author Affiliations
John D. McGlynn, Environmental Research Institute of Michigan (United States)
Kenneth K. Ellis, Environmental Research Institute of Michigan (United States)
David Kryskowski, Environmental Research Institute of Michigan (United States)

Published in SPIE Proceedings Vol. 1486:
Characterization, Propagation, and Simulation of Sources and Backgrounds
Wendell R. Watkins; Dieter Clement, Editor(s)

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