3D orientation tracking based on unscented Kalman filtering of accelerometer and magnetometer data

Orientation estimation can be executed by comparing the output of a 3D accelerometer and a 3D magnetometer with respectively gravity and local magnetic field vectors. For this purpose, an unscented Kalman filter was designed and tested. However, accelerometers also measure motion other than gravity, resulting in an error when estimating orientation directly from their output signals. Therefore, extra filters are added and the input parameters of the Kalman filter are dynamically varied, in order to reduce the effect of motion. Simulations are performed to tune the filter parameters for minimal motion influence without hampering actual orientation tracking. Satisfactory orientation tracking is performed with the filter using actual sensor nodes.