The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Attitude estimation for an aerial vehicle using the Kalman Filter - KF- with experimental validation is presented in this paper. The data fusion is made using simplified representations of the kinematics of the aerial vehicle and the accelerometer measurement model. The resulting algorithm is computationally efficient as it can be run at up to 500 Hz on a low-cost microcontroller. The observer is improved by choosing the appropriate covariance and noise matrices. Numerical and in-flight validation are carried out using an experimental platform and a quadrotor prototype. The experimental results are compared online with the measurements coming from a commercial IMU -Inertial Measurement Unit.