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dc.contributor.authorGümüşboğa, İlkay
dc.contributor.authorKıyak, Emre
dc.date.accessioned2019-10-20T19:32:45Z
dc.date.available2019-10-20T19:32:45Z
dc.date.issued2015
dc.identifier.isbn978-1-4673-7175-9
dc.identifier.urihttps://hdl.handle.net/11421/18634
dc.descriptionSensor Data Fusion: Trends, Solutions, Applications (SDF) -- OCT 06-08, 2015 -- Bonn, GERMANYen_US
dc.descriptionWOS: 000380442500007en_US
dc.description.abstractIn this work, a particle filter based integrated navigation system is designed and tested with real quadrotor systems. Conventionally, Kalman filter based algorithms is used for navigation systems which is highly non-linear. Kalman filter has significant assumptions such as linearity of system and measurement models and Gaussian distributions. This situation causes that Kalman filter does not work effective with navigation systems. Nowadays, particle filter based algorithms take over with respect to other estimation algorithms because of progression of computer's processors capability. Within the scope of this study, a particle filter based integrated navigation system is designed. This designed navigation system is tested on real quadrotor system. As a result of the real flight tests, the error margin is reduced a quarter according to the most trusted navigation aid.en_US
dc.description.sponsorshipAESS, ISIFen_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNavigationen_US
dc.subjectParticle Filteren_US
dc.subjectQuadrotor Systemen_US
dc.subjectEstimationen_US
dc.titleAn Integrated Navigation System Design For Quadrotorsen_US
dc.typeconferenceObjecten_US
dc.relation.journal2015 Workshop On Sensor Data Fusion - Trends, Solutions, Applications (Sdf)en_US
dc.contributor.departmentAnadolu Üniversitesi, Havacılık ve Uzay Bilimleri Fakültesi, Uçak Gövde Motor Bakım Bölümüen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US]
dc.contributor.institutionauthorKıyak, Emre


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