A simplified approach to motion estimation in a UAV using two filters

:Considering the requirement of precision positioning of Unmanned Aerial Vehicles in applications like in flights formations and flights with collision avoidance, this paper presents the proposal of a composition of a Complementary Filter used in orientation estimation and a Linear Kalman Filter (KF) in position estimation of the UAVs. The data evaluated in the experiments were acquired post flight from the flight controller embedded in a UAV. An Inertial Measurement Unit is used to provide the essentials datasets to the implementation of the Complementary Filter, which is modelled by Euler Angles referenced in a North-East-Down (NED) Coordinate System. The position estimation is obtained using the data from Global Positioning System (GPS) allied to a barometer applied in a Position-Velocity-Acceleration (PVA) model with Linear Kalman Filter. The acquired results provide evidence of the suitability and soundness of the proposed approach.