A Quaternion-based Unscented Kalman Filter for Orientation Tracking

نویسنده

  • Edgar Kraft
چکیده

This paper describes a Kalman filter for the real-time estimation of a rigid body orientation from measurements of acceleration, angular velocity and magnetic field strength. A quaternion representation of the orientation 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 Unscented Kalman filter which allows nonlinear process and measurement models and is more accurate and less costly than the common Extended Kalman filter. Several extensions to the original Unscented Kalman filter are necessary to treat the inherent properties of unit quaternions. Results with simulated and measured data are discussed.

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تاریخ انتشار 2003