{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/81087"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/81087","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Estimation of Intrinsic Gravity Wave Parameters From Multiple, Ground-Based Observations of a Single Mesopheric Airglow Emission","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Anderson, David Scott"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Swenson, Gary R."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T20:09:32Z","date_published":"2015-09-25T20:09:32Z","updated_at":"2026-07-22T22:26:15Z","subjects":["Engineering, Electronics and Electrical"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3337685"],"render_values":[{"text":"(MiAaPQ)AAI3337685","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/81087","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Swenson, Gary R."]},{"key":"dc:creator","label":"Author","values":["Anderson, David Scott"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T20:09:32Z","10000-01-01","2008"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Electronics and Electrical"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/81087","(MiAaPQ)AAI3337685"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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. 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