Date of Award:
5-2013
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Electrical and Computer Engineering
Advisor/Chair:
Jacob H. Gunther
Abstract
Removing the effects of the atmosphere from remote sensing data requires accurate knowledge of the physical properties of the atmosphere during the time of measurement. There is a nonlinear relationship that maps atmospheric composition to emitted spectra, but it cannot be easily inverted. The time evolution of atmospheric composition is approximately Markovian, and can be estimated using hyperspectral measurements of the atmosphere with particle filters. The difficulties associated with particle filtering high-dimension data can be mitigated by incorporating future measurement data with the proposal density.
Recommended Citation
Rawlings, Dustin, "Extracting Atmospheric Profiles from Hyperspectral Data Using Particle Filters" (2013). All Graduate Theses and Dissertations. 1533.
https://digitalcommons.usu.edu/etd/1533
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