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Proceedings Paper

Refined algorithms for star-based monitoring of GOES Imager visible-channel responsivities
Author(s): I-Lok Chang; Charles Dean; Zhenping Li; Michael Weinreb; Xiangqian Wu; P. A. V. B. Swamy
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Paper Abstract

Monitoring the responsivities of the visible channels of the Imagers on GOES satellites is a continuing effort at the National Environmental Satellite, Data and Information Service of NOAA. At this point, a large part of the initial processing of the star data depends on the operationalGOES Sensor Processing System(SPS) and GOES Orbit and AttitudeTracking System (OATS) for detecting the presence of stars and computing the amplitudes of the star signals. However, the algorithms of the SPS and the OATS are not optimized for calculating the amplitudes of the star signals, as they had been developed to determine pixel location and observation time of a star, not amplitude. Motivated by our wish to be independent of the SPS and the OATS for data processing and to improve the accuracy of the computed star signals, we have developed our own methods for such computations. We describe the principal algorithms and discuss their implementation. Next we show our monitoring statistics derived from star observations by the Imagers aboard GOES-8, -10, -11, -12 and -13. We give a brief introduction to a new class of time series that have improved the stability and reliability of our degradation estimates.

Paper Details

Date Published: 15 October 2012
PDF: 10 pages
Proc. SPIE 8510, Earth Observing Systems XVII, 85100R (15 October 2012); doi: 10.1117/12.928892
Show Author Affiliations
I-Lok Chang, Earth Resources Technology, Inc. (United States)
Charles Dean, Earth Resources Technology, Inc. (United States)
Zhenping Li, SGT, Inc. (United States)
Michael Weinreb, Riverside Technology, Inc., NOAA/NESDIS/OSD (United States)
Xiangqian Wu, NOAA/NESDIS/STAR (United States)
P. A. V. B. Swamy, Federal Reserve Board (United States)

Published in SPIE Proceedings Vol. 8510:
Earth Observing Systems XVII
James J. Butler; Xiaoxiong Xiong; Xingfa Gu, Editor(s)

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