Comparison of Model Predicted and Observed Light Curves of GEO Satellites

Although the amount of light received by sensors on the ground from Resident Space Objects (RSOs) in geostationary orbit (GEO) is small, information can still be extracted in the form of light curves (temporal brightness or apparent magnitude). Previous research has shown promising results in determ...

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Main Author: Ceniceros, Angelica
Other Authors: Gaylor, David
Language:en_US
Published: The University of Arizona. 2017
Online Access:http://hdl.handle.net/10150/625339
http://arizona.openrepository.com/arizona/handle/10150/625339
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spelling ndltd-arizona.edu-oai-arizona.openrepository.com-10150-6253392017-08-26T03:00:35Z Comparison of Model Predicted and Observed Light Curves of GEO Satellites Ceniceros, Angelica Ceniceros, Angelica Gaylor, David Gaylor, David Furfaro, Roberto Reddy, Vishnu Although the amount of light received by sensors on the ground from Resident Space Objects (RSOs) in geostationary orbit (GEO) is small, information can still be extracted in the form of light curves (temporal brightness or apparent magnitude). Previous research has shown promising results in determining RSO characteristics such as shape, size, reflectivity, and attitude by processing simulated light curve data with various estimation algorithms. These simulated light curves have been produced using one of several existing analytic Bidirectional Reflectance Distribution Function (BRDF) models. These BRDF models have generally come from researchers in computer graphics and machine vision and have not been shown to be realistic for telescope observations of RSOs in GEO. While BRDFs have been used for Space Situational Awareness (SSA) analysis and characterization, there is a lack of research on the validation of BRDFs with real data. This research is focused on comparing telescope data provided by Applied Defense Solutions, as processed by their Efficient Photometry In-Frame Calibration (EPIC) software, with predicted light curves based on the Ashikhmin-Premoze BRDF and two additional popular illumination models, Ashikhmin-Shirley and Cook-Torrance. I computed predicted light curves based on two line mean elements (TLEs), shape model, attitude profile, observing ground station location, observation time and BRDF. The selected BRDFS provided accurate apparent magnitude trends and behavior, but uncertainties due to lack of attitude information and deficiencies in our satellite model prevented us from obtaining a better match to the real data. 2017 text Electronic Thesis http://hdl.handle.net/10150/625339 http://arizona.openrepository.com/arizona/handle/10150/625339 en_US Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. The University of Arizona.
collection NDLTD
language en_US
sources NDLTD
description Although the amount of light received by sensors on the ground from Resident Space Objects (RSOs) in geostationary orbit (GEO) is small, information can still be extracted in the form of light curves (temporal brightness or apparent magnitude). Previous research has shown promising results in determining RSO characteristics such as shape, size, reflectivity, and attitude by processing simulated light curve data with various estimation algorithms. These simulated light curves have been produced using one of several existing analytic Bidirectional Reflectance Distribution Function (BRDF) models. These BRDF models have generally come from researchers in computer graphics and machine vision and have not been shown to be realistic for telescope observations of RSOs in GEO. While BRDFs have been used for Space Situational Awareness (SSA) analysis and characterization, there is a lack of research on the validation of BRDFs with real data. This research is focused on comparing telescope data provided by Applied Defense Solutions, as processed by their Efficient Photometry In-Frame Calibration (EPIC) software, with predicted light curves based on the Ashikhmin-Premoze BRDF and two additional popular illumination models, Ashikhmin-Shirley and Cook-Torrance. I computed predicted light curves based on two line mean elements (TLEs), shape model, attitude profile, observing ground station location, observation time and BRDF. The selected BRDFS provided accurate apparent magnitude trends and behavior, but uncertainties due to lack of attitude information and deficiencies in our satellite model prevented us from obtaining a better match to the real data.
author2 Gaylor, David
author_facet Gaylor, David
Ceniceros, Angelica
Ceniceros, Angelica
author Ceniceros, Angelica
Ceniceros, Angelica
spellingShingle Ceniceros, Angelica
Ceniceros, Angelica
Comparison of Model Predicted and Observed Light Curves of GEO Satellites
author_sort Ceniceros, Angelica
title Comparison of Model Predicted and Observed Light Curves of GEO Satellites
title_short Comparison of Model Predicted and Observed Light Curves of GEO Satellites
title_full Comparison of Model Predicted and Observed Light Curves of GEO Satellites
title_fullStr Comparison of Model Predicted and Observed Light Curves of GEO Satellites
title_full_unstemmed Comparison of Model Predicted and Observed Light Curves of GEO Satellites
title_sort comparison of model predicted and observed light curves of geo satellites
publisher The University of Arizona.
publishDate 2017
url http://hdl.handle.net/10150/625339
http://arizona.openrepository.com/arizona/handle/10150/625339
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