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Proceedings Paper

Approaches for processing spectral measurements of reflected sunlight for space situational awareness
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Paper Abstract

The proliferation of small, lightweight, 'micro-' and 'nanosatellite' (largest dimension < 1m ) has presented new challenges to the space surveillance community. The small size of these satellites makes them unresolvable by ground-based imaging systems. The core concept of using Non-Imaging Measurements (NIM) to gather information about these objects comes from the fact that after reflection on a satellite surface, the reflected light contains information about the surface materials of the satellite. This approach of using NIM for satellite evaluation is relatively new. In this paper, we discuss the accuracy of using these spectral measurements to match an unknown spectrum to a database containing known spectra. Several approaches have been developed and are presented in this paper. The first method is an artificial neural network designed to process central moments of real measured spectra. This spectrum database is the Spica database provided by the Maui Surveillance Site (MSSS), Hawaii USA and consists in spectra from more than 100 different satellites. The average rate of correct identification is 84%. The second approach is based on the ability of spectral signal processing to estimate relative abundances of materials from the measurement of a single spectrum; this method is called spectral unmixing. Material spectra were provided by the NASA Johnson Space Center (JSC) to create synthetic spectra. An approach based on the Expectation Maximization (EM) algorithm was used to estimate relative abundances and presence of materials in a synthetic spectrum. The results for material identification and abundance estimation are presented as a function of signal-to-noise ratio. For the EM method, the overall correct estimation rate is 95.1% and the average error on the fractional composition estimation is 19.7%.

Paper Details

Date Published: 25 August 2004
PDF: 10 pages
Proc. SPIE 5428, Signal and Data Processing of Small Targets 2004, (25 August 2004); doi: 10.1117/12.540919
Show Author Affiliations
Marie-Astrid A Cauquy, Michigan Technological Univ. (United States)
Michael C Roggemann, Michigan Technological Univ. (United States)
Timothy J Schulz, Michigan Technological Univ. (United States)


Published in SPIE Proceedings Vol. 5428:
Signal and Data Processing of Small Targets 2004
Oliver E. Drummond, Editor(s)

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