Unmanned Aerial Vehicles Position and Attitude Estimation Using Tightly Coupled Sensor Fusion of Low-cost GNSS, Inertial and Magnetic Sensors

Abstract

This paper presents a tightly coupled sensor fusion method based on low-cost GNSS, inertial (IMU) and magnetic sensors. This method is used to estimate UAVs position and attitude. Different coordinate systems and transformations are presented. The used GNSS, accelerometer, gyroscope, magnetometer sensor model equations are described in details. The estimation is based on an Extended Kalman Filter (EKF), which equations are also explained. The algorithm is tested on a real UAV flight data, and the results of the post-processing are compared to the reference data.