BADGER Lab graduate Weixin Wang, M.S., published a paper on the theoretical and practical benefits of the Bingham Filter in inertial orientation sensing. The Bingham Filter has a more accurate statistical propagation of uncertainty that respects the structure of the quaternion spaces that paramaterize rotations. Weixin’s paper used simulated and experimental data to assess the accuracy and convergence time of the Bingham Filter in comparison to the common Multiplicative Extended Kalman Filter (MEKF). The Bingham Filter showed small improvements in accuracy and convergence time in certain scenarios of low sampling rate and high uncertainty. However, it proved very computationally heavy. The paper will provide an evidence base for those considering how to make inertial sensing and navigation more accurate and robust with the Bingham Filter.
The paper appears in IEEE Sensors: Comparison of Bingham Filter and Extended Kalman Filter in IMU Attitude Estimation