Master of Science
Hart, Terry J.
The aim of this paper is to estimate the attitude of the quadcopter using the sensors: 3-axesaccelerometer, 3-axes gyroscope, 2-axes compass.At first I introduce some basic conception of quadcopter, such as the three main factor: roll, pitch,yaw, and the coordinate system that are used to implement the next calculations. Then according tothe mathematical model, I simulated the quadcopter in Simulink. The sensors are also modeled usingthe real sensor measurements to correctly estimate the measurement noise.After finished the model, I gave it a step input and get the output from the scope. Then I add theGaussian noise on to it and use this as the input of Extended Kalman Filter. And compare somedifferent type of Kalman Filter to conclude that the EKF is the best strategy.Finally we can conclude that the standard extended Kalman filter is the best estimator. If allof the parameters can be set correctly, The EKF can have a better result. But since it is notimplement on the embedded system, it can be used only as a reference and provide satisfyingresult in most situations.Keywords: Quadcopter, Extended Kalman Filter, Eular angle
Liang, Wenjing, "Attitude Estimation of Quadcopter through Extended Kalman Filter" (2017). Theses and Dissertations. 2685.