{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/81174"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/81174","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Computing Two-Dimensional Unambiguous Horizontal Wave Number Spectra From OH Airglow Images","abstract":"There is an inherent 180$\\sp\\circ$ ambiguity in the derived wave propagation direction when using conventional spectral analysis techniques on OH imager observations. A processing technique for computing the unambiguous two-dimensional (2-D) horizontal wave number spectrum from images of gravity wave perturbations in OH emission intensities is presented. The technique involves computing the $(\\omega,\\ k,\\ l)=(\\omega,\\ h, \\phi)$ spectrum of OH images collected over a period of several hours, where k is the zonal wave number, l is the meridional wave number, $h=(k\\sp2+l\\sp2)\\sp{1/2},\\ \\phi={\\rm tan}\\sp{-1}(k/l),$ and $\\omega$ is the temporal frequency. Before computing the spectra, the all-sky images are processed by first flat fielding each image, then removing stars using a median filter, subtracting an estimate of the background continuum, and finally, computing the relative OH intensity perturbations. Each pixel is then mapped onto a 256 x 256 rectilinear grid of geographic coordinates using a 9 x 9 Hamming-weighted sinc interpolation function. In practice, the choice of the image field-of-view (FOV) to be processed depends upon the region of interest in the spectrum. Accurate spectral magnitudes can be computed at horizontal wavelengths between twice the pixel spacing at the edge of the image (i.e., the Nyquist wavelength) and image FOV. Spatial and temporal prewhitening is employed prior to computing spectra to minimize artifacts in the derived unambiguous spectrum. We illustrate the method with real images acquired on 3 February 1995 at the Starfire Optical Range (SOR) near Albuquerque, New Mexico. The predominant direction of wave propagation is determined and the $m,\\ k,\\ l,\\ \\omega,\\ h,$ and $\\phi$ spectra presented, where m is the vertical wave number. The unambiguous 2-D phase speed spectrum is also obtained and the associated 1-D spectra are presented.","abstract_html":"There is an inherent 180$\\sp\\circ$ ambiguity in the derived wave propagation direction when using conventional spectral analysis techniques on OH imager observations. A processing technique for computing the unambiguous two-dimensional (2-D) horizontal wave number spectrum from images of gravity wave perturbations in OH emission intensities is presented. The technique involves computing the <span class=\"etd-inline-math\">(&omega;, k, l)=(&omega;, h, \\phi)</span> spectrum of OH images collected over a period of several hours, where k is the zonal wave number, l is the meridional wave number, <span class=\"etd-inline-math\">h=(k\\sp2+l\\sp2)\\sp{1/2}, \\phi={\\rm tan}\\sp{-1}(k/l),</span> and <span class=\"etd-inline-math\">&omega;</span> is the temporal frequency. Before computing the spectra, the all-sky images are processed by first flat fielding each image, then removing stars using a median filter, subtracting an estimate of the background continuum, and finally, computing the relative OH intensity perturbations. Each pixel is then mapped onto a 256 x 256 rectilinear grid of geographic coordinates using a 9 x 9 Hamming-weighted sinc interpolation function. In practice, the choice of the image field-of-view (FOV) to be processed depends upon the region of interest in the spectrum. Accurate spectral magnitudes can be computed at horizontal wavelengths between twice the pixel spacing at the edge of the image (i.e., the Nyquist wavelength) and image FOV. Spatial and temporal prewhitening is employed prior to computing spectra to minimize artifacts in the derived unambiguous spectrum. We illustrate the method with real images acquired on 3 February 1995 at the Starfire Optical Range (SOR) near Albuquerque, New Mexico. The predominant direction of wave propagation is determined and the <span class=\"etd-inline-math\">m, k, l, &omega;, h,</span> and $\\phi$ spectra presented, where m is the vertical wave number. The unambiguous 2-D phase speed spectrum is also obtained and the associated 1-D spectra are presented.","abstract_has_math":true,"creators":["Coble, Mark Ray"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":["George C. Papen"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T20:09:54Z","date_published":"2015-09-25T20:09:54Z","updated_at":"2026-07-22T22:26:15Z","subjects":["Remote Sensing"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI9737078"],"render_values":[{"text":"(MiAaPQ)AAI9737078","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/81174","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["George C. Papen"]},{"key":"dc:creator","label":"Author","values":["Coble, Mark Ray"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T20:09:54Z","10000-01-01","1997"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical 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":["Remote Sensing"]}]},{"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/2142/81174","(MiAaPQ)AAI9737078"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["There is an inherent 180$\\sp\\circ$ ambiguity in the derived wave propagation direction when using conventional spectral analysis techniques on OH imager observations. A processing technique for computing the unambiguous two-dimensional (2-D) horizontal wave number spectrum from images of gravity wave perturbations in OH emission intensities is presented. The technique involves computing the $(\\omega,\\ k,\\ l)=(\\omega,\\ h, \\phi)$ spectrum of OH images collected over a period of several hours, where k is the zonal wave number, l is the meridional wave number, $h=(k\\sp2+l\\sp2)\\sp{1/2},\\ \\phi={\\rm tan}\\sp{-1}(k/l),$ and $\\omega$ is the temporal frequency. Before computing the spectra, the all-sky images are processed by first flat fielding each image, then removing stars using a median filter, subtracting an estimate of the background continuum, and finally, computing the relative OH intensity perturbations. Each pixel is then mapped onto a 256 x 256 rectilinear grid of geographic coordinates using a 9 x 9 Hamming-weighted sinc interpolation function. In practice, the choice of the image field-of-view (FOV) to be processed depends upon the region of interest in the spectrum. Accurate spectral magnitudes can be computed at horizontal wavelengths between twice the pixel spacing at the edge of the image (i.e., the Nyquist wavelength) and image FOV. Spatial and temporal prewhitening is employed prior to computing spectra to minimize artifacts in the derived unambiguous spectrum. We illustrate the method with real images acquired on 3 February 1995 at the Starfire Optical Range (SOR) near Albuquerque, New Mexico. The predominant direction of wave propagation is determined and the $m,\\ k,\\ l,\\ \\omega,\\ h,$ and $\\phi$ spectra presented, where m is the vertical wave number. The unambiguous 2-D phase speed spectrum is also obtained and the associated 1-D spectra are presented.","Made available in DSpace on 2015-09-25T20:09:54Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 9737078.pdf: 3372140 bytes, checksum: 0966595936ed63c6fabe1255c6327f1d (MD5) Previous issue date: 1997","Embargo set by: Seth Robbins for item 82455 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","75 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997."]},{"key":"dc:title","label":"Title","values":["Computing Two-Dimensional Unambiguous Horizontal Wave Number Spectra From OH Airglow Images"]}]}],"canonical_facts":{"dc:contributor":["George C. Papen"],"dc:creator":["Coble, Mark Ray"],"dc:date":["2015-09-25T20:09:54Z","10000-01-01","1997"],"dc:description":["There is an inherent 180$\\sp\\circ$ ambiguity in the derived wave propagation direction when using conventional spectral analysis techniques on OH imager observations. A processing technique for computing the unambiguous two-dimensional (2-D) horizontal wave number spectrum from images of gravity wave perturbations in OH emission intensities is presented. The technique involves computing the $(\\omega,\\ k,\\ l)=(\\omega,\\ h, \\phi)$ spectrum of OH images collected over a period of several hours, where k is the zonal wave number, l is the meridional wave number, $h=(k\\sp2+l\\sp2)\\sp{1/2},\\ \\phi={\\rm tan}\\sp{-1}(k/l),$ and $\\omega$ is the temporal frequency. Before computing the spectra, the all-sky images are processed by first flat fielding each image, then removing stars using a median filter, subtracting an estimate of the background continuum, and finally, computing the relative OH intensity perturbations. Each pixel is then mapped onto a 256 x 256 rectilinear grid of geographic coordinates using a 9 x 9 Hamming-weighted sinc interpolation function. In practice, the choice of the image field-of-view (FOV) to be processed depends upon the region of interest in the spectrum. Accurate spectral magnitudes can be computed at horizontal wavelengths between twice the pixel spacing at the edge of the image (i.e., the Nyquist wavelength) and image FOV. Spatial and temporal prewhitening is employed prior to computing spectra to minimize artifacts in the derived unambiguous spectrum. We illustrate the method with real images acquired on 3 February 1995 at the Starfire Optical Range (SOR) near Albuquerque, New Mexico. The predominant direction of wave propagation is determined and the $m,\\ k,\\ l,\\ \\omega,\\ h,$ and $\\phi$ spectra presented, where m is the vertical wave number. The unambiguous 2-D phase speed spectrum is also obtained and the associated 1-D spectra are presented.","Made available in DSpace on 2015-09-25T20:09:54Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 9737078.pdf: 3372140 bytes, checksum: 0966595936ed63c6fabe1255c6327f1d (MD5) Previous issue date: 1997","Embargo set by: Seth Robbins for item 82455 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","75 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997."],"dc:identifier":["http://hdl.handle.net/2142/81174","(MiAaPQ)AAI9737078"],"dc:language":["eng"],"dc:subject":["Remote Sensing"],"dc:title":["Computing Two-Dimensional Unambiguous Horizontal Wave Number Spectra From OH Airglow Images"],"dc:type":["text"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:15Z"}