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dc.contributor.advisorChao, Haiyang
dc.contributor.authorTian, Pengzhi
dc.date.accessioned2022-03-18T16:11:15Z
dc.date.available2022-03-18T16:11:15Z
dc.date.issued2020-08-31
dc.date.submitted2020
dc.identifier.otherhttp://dissertations.umi.com/ku:17281
dc.identifier.urihttp://hdl.handle.net/1808/32610
dc.description.abstractThis dissertation focuses on development of new sensing, estimation, and analysis methods for unmanned aerial vehicle (UAV) operations in dynamic wind fields. Three main problems are studied, including airflow angle estimation, 3D wind estimation, and UAV wake encounter identification, simulation, and validation. A thorough survey is performed first on wind sensing and estimation methods using fixed-wing UAVs. Four flow angle estimation filters are then proposed and validated for accurate UAV flow angle estimation at low cost. Furthermore, two 3D wind estimation filters are proposed for small fixed-wing UAVs and validated by utilizing different wind models. Finally, a novel UAV wake encounter simulation platform is developed to simulate UAV response during wake encounters and compared with results from close formation wake encounter flight.
dc.format.extent144 pages
dc.language.isoen
dc.publisherUniversity of Kansas
dc.rightsCopyright held by the author.
dc.subjectAerospace engineering
dc.subjectFlight Test
dc.subjectFlow Angle
dc.subjectFormation Flight
dc.subjectUAV
dc.subjectWake Encounter
dc.subjectWind Estimation
dc.titleSensing and Estimation of Airflow Angles and Atmospheric Winds for Small Unmanned Aerial Vehicles
dc.typeDissertation
dc.contributor.cmtememberKeshmiri, Shawn
dc.contributor.cmtememberPasik-Duncan, Bozenna
dc.contributor.cmtememberMcLaughlin, Craig
dc.contributor.cmtememberZheng, Zhongquan
dc.thesis.degreeDisciplineAerospace Engineering
dc.thesis.degreeLevelPh.D.
dc.identifier.orcid


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