Computer Science – Performance
Scientific paper
Dec 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994aifo.reptr....c&link_type=abstract
M.S. Thesis Air Force Inst. of Tech., Wright-Patterson AFB, OH. School of Engineering.
Computer Science
Performance
Composition (Property), Estimates, Fourier Transformation, Interferometers, Interferometry, Linear Arrays, Statistical Analysis, Surface Layers, Classifications, Errors, Estimating, Neural Nets, Reflectance, Signal To Noise Ratios, Telescopes
Scientific paper
The objective of this research was to determine if measurements from a Sagnac interferometer could provide reliable estimates of satellite material composition. The Sagnac interferometer yields a spatial interferogram that can be sampled by a linear detector array. The interferogram is related to the spectrum of the source through a Fourier transform. Here, spectral reflectivities of nine common satellite materials were used to simulate the spectrum on obtains from an ideal Sagnac interferometer in the beam-train of a ground-based telescope whose mission is to view satellites. The signal-to-noise ratio of the spectrum was varied to simulate the effect of range variation between the sensor and the satellite. The simulated spectra consisted of a linear mixture of spectra from two of the nine materials. Three different architectures were developed and their performances compared. One of the three architectures consisted of nine artificial neural networks (ANN's), one for each material, and a linear estimator that estimated the satellite surface area attributable to each material. This method estimates the material composition by using a classifier to identify the materials contributing to the mixture, then eliminating unlikely contributors to the mixture before performing a constrained linear estimate. It is shown that due to high classification errors, the system using solely a linear estimator provides the estimate with the lowest errors.
No associations
LandOfFree
Satellite surface material composition from synthetic spectra 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 Satellite surface material composition from synthetic spectra, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Satellite surface material composition from synthetic spectra will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1325074