{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/110761"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/110761","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Estimation of ion drift velocity vector in F region ionosphere based on incoherent scattered pulse data using machine learning technique","abstract":"This thesis presents work on estimating the vector drift velocities of the plasma at different altitudes in the F region of the ionosphere using machine learning techniques. The computation is based on the radar data acquired with the ALTAIR (Automatic Radar Plotting Aid (ARPA) Long-Range Tracking and Instrumentation Radar) incoherent scatter radar (ISR). The line-of-sight (LOS) Doppler velocity of radar backscattered echoes can be obtained by estimating the phase slope of the auto-correlation function (ACF) of backscattered signals. In order to improve accuracy, a machine learning algorithm, DBSCAN (density-based spatial clustering of applications with noise), is used to distinguish the data segments from the noise segments. The LOS velocities of backscattered pulses are projections of the drift velocity vectors on LOS direction unit vector. A system of linear equations based on geometry will be established to estimate the velocity vectors. This thesis will also describe the procedure of formulating the linear equations at each height and include a rank 2 regularization to solve the system of linear equations on a realistic basis.","abstract_html":"This thesis presents work on estimating the vector drift velocities of the plasma at different altitudes in the F region of the ionosphere using machine learning techniques. The computation is based on the radar data acquired with the ALTAIR (Automatic Radar Plotting Aid (ARPA) Long-Range Tracking and Instrumentation Radar) incoherent scatter radar (ISR). The line-of-sight (LOS) Doppler velocity of radar backscattered echoes can be obtained by estimating the phase slope of the auto-correlation function (ACF) of backscattered signals. In order to improve accuracy, a machine learning algorithm, DBSCAN (density-based spatial clustering of applications with noise), is used to distinguish the data segments from the noise segments. The LOS velocities of backscattered pulses are projections of the drift velocity vectors on LOS direction unit vector. A system of linear equations based on geometry will be established to estimate the velocity vectors. This thesis will also describe the procedure of formulating the linear equations at each height and include a rank 2 regularization to solve the system of linear equations on a realistic basis.","abstract_has_math":false,"creators":["Ye, Bingqian"],"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":2021,"date_issued":"2021-09-17T02:34:52Z","date_published":"2021-09-17T02:34:52Z","updated_at":"2026-07-22T22:24:52Z","subjects":["plasma drift velocity","incoherent scatter radar","machine learning"],"languages":["en"],"rights":["Copyright 2021 Bingqian Ye"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/110761","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":["Ye, Bingqian"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-09-17T02:34:52Z","2023-09-17T02:34:57Z","2021-04-30","2021-05"]},{"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":["plasma drift velocity","incoherent scatter radar","machine learning"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Bingqian Ye"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/110761"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis presents work on estimating the vector drift velocities of the plasma at different altitudes in the F region of the ionosphere using machine learning techniques. The computation is based on the radar data acquired with the ALTAIR (Automatic Radar Plotting Aid (ARPA) Long-Range Tracking and Instrumentation Radar) incoherent scatter radar (ISR). The line-of-sight (LOS) Doppler velocity of radar backscattered echoes can be obtained by estimating the phase slope of the auto-correlation function (ACF) of backscattered signals. In order to improve accuracy, a machine learning algorithm, DBSCAN (density-based spatial clustering of applications with noise), is used to distinguish the data segments from the noise segments. The LOS velocities of backscattered pulses are projections of the drift velocity vectors on LOS direction unit vector. A system of linear equations based on geometry will be established to estimate the velocity vectors. This thesis will also describe the procedure of formulating the linear equations at each height and include a rank 2 regularization to solve the system of linear equations on a realistic basis.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-05-01","The student, Bingqian Ye, accepted the attached license on 2021-04-30 at 15:01.","The student, Bingqian Ye, submitted this Thesis for approval on 2021-04-30 at 16:17.","This Thesis was approved for publication on 2021-04-30 at 16:39.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16632 on 2021-09-16 at 17:07:00","Made available in DSpace on 2021-09-17T02:34:52Z (GMT). No. of bitstreams: 2 YE-THESIS-2021.pdf: 8742712 bytes, checksum: e0aa298e2554f656cacfe13d680e5485 (MD5) LICENSE.txt: 4208 bytes, checksum: c3db3734136e3f3f186a64f38ec7a828 (MD5) Previous issue date: 2021-04-30","Embargo set by: Seth Robbins for item 118604 Lift date: 2023-09-17T02:34:57Z 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":["Estimation of ion drift velocity vector in F region ionosphere based on incoherent scattered pulse data using machine learning technique"]}]}],"canonical_facts":{"dc:contributor":["Kudeki, Erhan"],"dc:creator":["Ye, Bingqian"],"dc:date":["2021-09-17T02:34:52Z","2023-09-17T02:34:57Z","2021-04-30","2021-05"],"dc:description":["This thesis presents work on estimating the vector drift velocities of the plasma at different altitudes in the F region of the ionosphere using machine learning techniques. The computation is based on the radar data acquired with the ALTAIR (Automatic Radar Plotting Aid (ARPA) Long-Range Tracking and Instrumentation Radar) incoherent scatter radar (ISR). The line-of-sight (LOS) Doppler velocity of radar backscattered echoes can be obtained by estimating the phase slope of the auto-correlation function (ACF) of backscattered signals. In order to improve accuracy, a machine learning algorithm, DBSCAN (density-based spatial clustering of applications with noise), is used to distinguish the data segments from the noise segments. The LOS velocities of backscattered pulses are projections of the drift velocity vectors on LOS direction unit vector. A system of linear equations based on geometry will be established to estimate the velocity vectors. This thesis will also describe the procedure of formulating the linear equations at each height and include a rank 2 regularization to solve the system of linear equations on a realistic basis.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-05-01","The student, Bingqian Ye, accepted the attached license on 2021-04-30 at 15:01.","The student, Bingqian Ye, submitted this Thesis for approval on 2021-04-30 at 16:17.","This Thesis was approved for publication on 2021-04-30 at 16:39.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16632 on 2021-09-16 at 17:07:00","Made available in DSpace on 2021-09-17T02:34:52Z (GMT). No. of bitstreams: 2 YE-THESIS-2021.pdf: 8742712 bytes, checksum: e0aa298e2554f656cacfe13d680e5485 (MD5) LICENSE.txt: 4208 bytes, checksum: c3db3734136e3f3f186a64f38ec7a828 (MD5) Previous issue date: 2021-04-30","Embargo set by: Seth Robbins for item 118604 Lift date: 2023-09-17T02:34:57Z 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"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/110761"],"dc:language":["en"],"dc:rights":["Copyright 2021 Bingqian Ye"],"dc:subject":["plasma drift velocity","incoherent scatter radar","machine learning"],"dc:title":["Estimation of ion drift velocity vector in F region ionosphere based on incoherent scattered pulse data using machine learning technique"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:52Z"}