Surface Material Characterization from Non-resolved Multi-band Optical Observations

Abstract

Ground-based optical and radar sites routinely acquire resolved images of satellites. These images provide the means to construct accurate wire-frame models of the observed body, as well as an understanding of its orientation as a function of time. Unfortunately, because such images are typically acquired at a single wavelength, this kind of analysis provides little or no information on the types of materials covering the satellite s various surfaces. Detailed surface material characterization generally requires multi-band radiometric and/or spectrometric measurements. Many widely-available instruments provide such multi-band information (e.g., spectrographs and multi-channel photometers). However, these sensors typically measure the brightness of sunlight reflected from the entire satellite, with no spatial resolution at all. Because such whole-body measurements represent a summation of contributions from many reflecting surfaces, an un-mixing analysis must be employed to characterize the reflectance of the satellite s individual sub-components. The objective of this paper is to outline the theory required for such an unmixing process, focusing on two newly-developed analysis methods. Both methods retrieve satellite surface properties from temporal sequences of whole-body brightness measurements.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2012
Accession Number
ADA574711

Entities

People

  • Doyle Hall
  • Kris Hamada
  • Paul Kervin
  • Thomas Kelecy

Organizations

  • Air Force Research Laboratory

Tags

DTIC Thesaurus Topics

  • Artificial Satellites
  • Brightness
  • Directional
  • Distribution Functions
  • Ground Based
  • Images
  • Low Earth Orbits
  • Measurement
  • Observation
  • Optical Properties
  • Orientation (Direction)
  • Reflectance
  • Reflection
  • Solar Panels
  • Spacecraft
  • Specular Reflection
  • Surface Properties

Readers

  • Astronomy and Astrophysics.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Image Processing and Computer Vision.

Technology Areas

  • Space