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Extended Kalman Filter for Robust UAV Attitude Estimation
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Extended Kalmanfilter för robust estimering av UAV-attityd (Swedish)
Abstract [en]

Attitude estimation of unmanned aerial vehicles is of great importance as it enables propercontrol of the vehicles. Attitude estimation is typically done by an attitude-heading refer-ence system (ahrs) which utilises different kind of sensors. In this thesis these include agyroscope providing angular rates measurements which can be integrated to describe the at-titude as well as an accelerometer and a magnetometer, both of which can be compared withknown reference vectors to determine the attitude. The sensor measurements are fused usinga gps augmented 7-state Extended Kalman filter (ekf) with a quaternion and gyroscope bi-ases as state variables. It uses differentiated gps velocity measurements to estimate externalaccelerations as reference vector to the accelerometer, which significantly raises robustnessof the solution. The filter is implemented in MatlabTM and in c on an ARM microprocessor.It is compared with an explicit complementary filter solution and is evaluated with flightsusing a fixed-wing uav with satisfactory results.

Place, publisher, year, edition, pages
2015. , 86 p.
Keyword [en]
Kalman, autonomous, UAV, EKF, attitude, INS, IMU
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-119097ISRN: LiTH-ISY-EX–15/4835–SEOAI: oai:DiVA.org:liu-119097DiVA: diva2:818704
External cooperation
UAS Europe
Subject / course
Automatic Control
Supervisors
Examiners
Available from: 2015-06-09 Created: 2015-06-09 Last updated: 2015-06-09Bibliographically approved

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CiteExportLink to record
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  • apa
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