Estimation of Intrinsic Gravity Wave Parameters From Multiple, Ground-Based Observations of a Single Mesopheric Airglow Emission
Anderson, David Scott
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/81087
Description
Title
Estimation of Intrinsic Gravity Wave Parameters From Multiple, Ground-Based Observations of a Single Mesopheric Airglow Emission
Author(s)
Anderson, David Scott
Issue Date
2008
Doctoral Committee Chair(s)
Swenson, Gary R.
Department of Study
Electrical and Computer Engineering
Discipline
Electrical and Computer Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
Abstract
This dissertation addresses the problem of using multiple, simultaneous observations of mesospheric airglow emissions to estimate key intrinsic parameters of atmospheric gravity waves (AGWs). As AGWs propagate through the mesosphere, they spatially and temporally perturb mesospheric airglow emissions, which, from the ground, can be imaged using large-format CCD cameras retrofitted with spectroscopic optics. By observing the emission perturbations from different vantage points, information can be inferred about the vertical wave structure using tomographic and parameter estimation techniques. In this dissertation, the problem is analyzed using standard tomography techniques to produce a reconstruction that can be used to estimate vertical wave structure. Next, a tomography scheme that works in the Fourier domain is developed to take advantage of the wave perturbation's Fourier sparseness. Then, a parameter estimation (PE) technique is developed to infer the key AGW parameters directly from the data, followed by an in-depth analysis of the error from this estimation method. Finally, the PE method is applied to real data collected by the University of Illinois remote sensing team in June 2007.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
