Computer Science
Scientific paper
Sep 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010amos.confe...6h&link_type=abstract
Proceedings of the Advanced Maui Optical and Space Surveillance Technologies Conference, held in Wailea, Maui, Hawaii, September
Computer Science
Scientific paper
Ground-based optical and radar sites routinely acquire resolved images of satellites. These resolved 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 in a single spectral band, they provide little information on the types of materials covering the satellite's various surfaces. Detailed surface material characterization generally requires spectrometric and/or multi-band photometric measurements. Fortunately, many instruments provide such multi-band information (e.g., spectrographs and multi-channel photometers). However, these sensors often measure the brightness of 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‖ or inversion process must be employed to determine the materials covering each of the satellite's individual sub-components. The first section of this paper describes the inversion theory required to retrieve satellite surface material properties from temporal sequences of whole-body multi-band brightness measurements. The inversion requires the following as input: 1) a set of multi-band measurements of a satellite's reflected-sunlight brightness, 2) the satellite's wire-frame model, including each major component capable of reflecting sunlight, 3) the satellite's attitude, specifying the body’s orientation at the time of each multi-band measurement, and 4) a database of bi-directional reflection distribution functions for a set of candidate surface materials. As output, the inversion process yields estimates of the fraction of each major satellite component covered by each candidate material. The second section of the paper describes several tests of the method by applying it to simulated multi-band observations of a cubical satellite with different materials on each of its six faces. The tests indicate that the inversion method successfully retrieves the six known materials when provided a complete noise-free scan of the cube as input. The method also performs reasonably well when confronted with the adverse effects of measurement noise, superfluous or unknown candidate materials, and incomplete observations.
No associations
LandOfFree
Surface Material Characterization from Multi-band Optical Observations does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Surface Material Characterization from Multi-band Optical Observations, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Surface Material Characterization from Multi-band Optical Observations will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1555548