Embedded avionics with Kalman state estimation for a novel micro-scale unmanned aerial vehicle
Name
871037454-MIT.pdf
Description
Full printable version
Size
12.69 MB
Format
Adobe PDF
Checksum (MD5)
6eea6bcc858e54c43d7799d77e0c2385
Author(s)
Tzanetos, Theodore
Advisor(s)
James K. Roberge and Ryan D. Eubank.
Date Issued
2013
Publisher
Massachusetts Institute of Technology
Abstract
An inertial navigation system leveraging Kalman estimation techniques and quaternion dynamics is developed for deployment to a micro-scale unmanned aerial vehicle (UAV). The capabilities, limitations, and requirements of existing navigation solutions motivate the need for an integrated solution that can be readily applied to small embedded systems and still provide reasonably accurate results. Methods to calibrate and compensate systemic inaccuracies in microelectromechanical systems (MEMS) sensors, commonly used in micro-scale UAV applications, are also developed. The problems associated with attitude determination and system localization are analyzed in isolation with incremental simulation and field testing. Performance is evaluated against commercially available inertial navigation system solutions. The result is a capable navigation system that, by its structure, trades a small measure of accuracy in order to be easily adapted to the embedded computing constraints of unmanned vehicles in the micro-scale.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis. "June 2013."
Includes bibliographical references (pages 107-109).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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