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

Marie-Astrid A Cauquy; Michael C Roggemann; Timothy J Schulz

doi:10.1117/12.540919

25 August 2004 Approaches for processing spectral measurements of reflected sunlight for space situational awareness

Marie-Astrid A Cauquy, Michael C Roggemann, Timothy J Schulz

Proceedings Volume 5428, Signal and Data Processing of Small Targets 2004; (2004) https://doi.org/10.1117/12.540919
Event: Defense and Security, 2004, Orlando, Florida, United States

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%.

Citation Download Citation

Marie-Astrid A Cauquy, Michael C Roggemann, and Timothy J Schulz "Approaches for processing spectral measurements of reflected sunlight for space situational awareness", Proc. SPIE 5428, Signal and Data Processing of Small Targets 2004, (25 August 2004); https://doi.org/10.1117/12.540919

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available