Robust Orientation Estimation with TRIAD-aided Manifold EKF

Abstract-- The manifold extended Kalman filter (Manifold EKF) has found extensive application for attitude determination. Magnetometers employed as sensors for such attitude determination are easily prone to disturbances by their sensitivity to calibration and external magnetic fields. The TRIAD (Tri-Axial Attitude Determination) algorithm is well-known as a sub-optimal attitude estimator . In this article, we incorporate this sub-optimal feature of the TRIAD in mitigating the influence of the magnetometer reading in the pitch and roll axis determination in the Manifold EKF algorithm. We substantiate our results with experiments. Accurate orientation estimation is critical for a wide range of applications, such as in Unmanned Aerial V ehicles (UA Vs), mobile devices and robotics. Numerous studies have been dedicated to improving sensor orientation estimation.