{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108203"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108203","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Inversion of Arecibo incoherent scatter radar coded long pulse backscatter spectra","abstract":"Incoherent scatter radar (ISR) at Arecibo Observatory measures the scattering of electromagnetic waves from random density fluctuations of ionospheric plasma particles (electrons and ions). Information about particle temperatures, ion concentrations, and Doppler shifts caused by particle motions can be estimated by inverting the power spectra of received scatter signals to the numerially implemented ISR forward spectral model in the frequency domain. Power spectrum estimates are derived by taking FFT of signal samples and averaging the magnitude square of the FFTs. Power spectra include both statistical estimation errors due to the use of finite length data sets and a characteristic shape that depends on ionospheric parameters via a known non-linear relationship that is exploited during the inversion process. This thesis first describes the numerical implementation of the complete collisional ISR spectral model using chirp-z algorithm, and mainly focuses on Arecibo coded long pulse (CLP) data analysis, including spectrum generation and inversion of raw voltage data from two receivers of Arecibo Observatory. Regular FFT method and the multi-level chirp-z algorithm for speeding up spectrum computation are presented. Weighted least-square spectrum inversion of the spectral estimates to double-humped spectral model of ionospheric incoherent scatter signals using various inversion techniques including the inversion of ion drift velocity using measured spectra ACF are discussed.","abstract_html":"Incoherent scatter radar (ISR) at Arecibo Observatory measures the scattering of electromagnetic waves from random density fluctuations of ionospheric plasma particles (electrons and ions). Information about particle temperatures, ion concentrations, and Doppler shifts caused by particle motions can be estimated by inverting the power spectra of received scatter signals to the numerially implemented ISR forward spectral model in the frequency domain. Power spectrum estimates are derived by taking FFT of signal samples and averaging the magnitude square of the FFTs. Power spectra include both statistical estimation errors due to the use of finite length data sets and a characteristic shape that depends on ionospheric parameters via a known non-linear relationship that is exploited during the inversion process. This thesis first describes the numerical implementation of the complete collisional ISR spectral model using chirp-z algorithm, and mainly focuses on Arecibo coded long pulse (CLP) data analysis, including spectrum generation and inversion of raw voltage data from two receivers of Arecibo Observatory. Regular FFT method and the multi-level chirp-z algorithm for speeding up spectrum computation are presented. Weighted least-square spectrum inversion of the spectral estimates to double-humped spectral model of ionospheric incoherent scatter signals using various inversion techniques including the inversion of ion drift velocity using measured spectra ACF are discussed.","abstract_has_math":false,"creators":["Wu, Yulun"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Kudeki, Erhan"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-26T23:58:50Z","date_published":"2020-08-26T23:58:50Z","updated_at":"2026-07-22T22:24:48Z","subjects":["Incoherent scatter radar","inversion","signal processing"],"languages":["en"],"rights":["Copyright 2020 Yulun Wu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108203","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kudeki, Erhan"]},{"key":"dc:creator","label":"Author","values":["Wu, Yulun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-08-26T23:58:50Z","2022-08-26T23:58:55Z","2020-05-15","2020-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["Incoherent scatter radar","inversion","signal processing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Yulun Wu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108203"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Incoherent scatter radar (ISR) at Arecibo Observatory measures the scattering of electromagnetic waves from random density fluctuations of ionospheric plasma particles (electrons and ions). Information about particle temperatures, ion concentrations, and Doppler shifts caused by particle motions can be estimated by inverting the power spectra of received scatter signals to the numerially implemented ISR forward spectral model in the frequency domain. Power spectrum estimates are derived by taking FFT of signal samples and averaging the magnitude square of the FFTs. Power spectra include both statistical estimation errors due to the use of finite length data sets and a characteristic shape that depends on ionospheric parameters via a known non-linear relationship that is exploited during the inversion process. This thesis first describes the numerical implementation of the complete collisional ISR spectral model using chirp-z algorithm, and mainly focuses on Arecibo coded long pulse (CLP) data analysis, including spectrum generation and inversion of raw voltage data from two receivers of Arecibo Observatory. Regular FFT method and the multi-level chirp-z algorithm for speeding up spectrum computation are presented. Weighted least-square spectrum inversion of the spectral estimates to double-humped spectral model of ionospheric incoherent scatter signals using various inversion techniques including the inversion of ion drift velocity using measured spectra ACF are discussed.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Yulun Wu, accepted the attached license on 2020-05-15 at 16:26.","The student, Yulun Wu, submitted this Thesis for approval on 2020-05-15 at 16:28.","This Thesis was approved for publication on 2020-05-15 at 16:35.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15404 on 2020-08-25 at 17:31:27","Made available in DSpace on 2020-08-26T23:58:50Z (GMT). No. of bitstreams: 2 WU-THESIS-2020.pdf: 4307604 bytes, checksum: c8f39fcebbd3d1ce9cf61307f3495908 (MD5) LICENSE.txt: 4205 bytes, checksum: 35c94967c4b3a36e4a4631f6d1f62ba6 (MD5) Previous issue date: 2020-05-15","Embargo set by: Seth Robbins for item 115816 Lift date: 2022-08-26T23:58:55Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","U of I Only"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Inversion of Arecibo incoherent scatter radar coded long pulse backscatter spectra"]}]}],"canonical_facts":{"dc:contributor":["Kudeki, Erhan"],"dc:creator":["Wu, Yulun"],"dc:date":["2020-08-26T23:58:50Z","2022-08-26T23:58:55Z","2020-05-15","2020-05"],"dc:description":["Incoherent scatter radar (ISR) at Arecibo Observatory measures the scattering of electromagnetic waves from random density fluctuations of ionospheric plasma particles (electrons and ions). Information about particle temperatures, ion concentrations, and Doppler shifts caused by particle motions can be estimated by inverting the power spectra of received scatter signals to the numerially implemented ISR forward spectral model in the frequency domain. Power spectrum estimates are derived by taking FFT of signal samples and averaging the magnitude square of the FFTs. Power spectra include both statistical estimation errors due to the use of finite length data sets and a characteristic shape that depends on ionospheric parameters via a known non-linear relationship that is exploited during the inversion process. This thesis first describes the numerical implementation of the complete collisional ISR spectral model using chirp-z algorithm, and mainly focuses on Arecibo coded long pulse (CLP) data analysis, including spectrum generation and inversion of raw voltage data from two receivers of Arecibo Observatory. Regular FFT method and the multi-level chirp-z algorithm for speeding up spectrum computation are presented. Weighted least-square spectrum inversion of the spectral estimates to double-humped spectral model of ionospheric incoherent scatter signals using various inversion techniques including the inversion of ion drift velocity using measured spectra ACF are discussed.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Yulun Wu, accepted the attached license on 2020-05-15 at 16:26.","The student, Yulun Wu, submitted this Thesis for approval on 2020-05-15 at 16:28.","This Thesis was approved for publication on 2020-05-15 at 16:35.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15404 on 2020-08-25 at 17:31:27","Made available in DSpace on 2020-08-26T23:58:50Z (GMT). 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