A quaternion-based unscented Kalman filter for orientation tracking

Abstract

This paper describes a Kalman filter for the real-time estimation of a rigid body orientation from mea- surements of acceleration, angular velocity and magnetic field strength. A quaternion representation of the orienta- tion is computationally effective and avoids problems with singularities. The nonlinear relationship between estimated Orientation and expected measurement prevent the usage of a classical Kalman filter: This problem is solved by an Un- scented Kalman filter which allows nonlinear process and measurement models and is more accurate and less costly than the common Extended Kalman filter: Several exten- sions to the original Unscented Kalman filter are necessary to treat the inherent properties of unit quaternions. Results with simulated and measured data are discussed.