Extended and Unscented Kalman Filters for Attitude Estimation of an Unmanned Aerial Vehicle

A. Kallapur, S. Anavatti, and M. Garratt (Australia)


Filtering, UAV, EKF, UKF, Monte Carlo, Attitude Estima tion


Precise position and attitude estimation is necessary for guidance, navigation and control of small Unmanned Aerial Vehicles (UAVs). With limited payload capabilities and low-cost sensors it becomes necessary to implement robust estimation techniques that can handle varied amount of system nonlinearities and noise. With limited accuracy of such sensors, the need for ef´Čücient and accurate estima tion methods become vital. This paper compares and con trasts Monte Carlo simulation results as obtained for an Ex tended Kalman Filter (EKF) and an Unscented Kalman Fil ter (UKF), towards the attitude estimation of a small UAV.

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