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The article discusses a study which modified an unscented quaternion estimator (USQUE) with the averaging algorithm for an attitude-estimation problem. Topics covered include other parametizations that can be used to represent the attitude such as Euler angles, direct cosine matrix and generalized Rodrigues parameters (GRP), nonlinear filtering methods such as unscented Kalman filter, and USQUE modification procedures. Also provided are simulation examples.

The article discusses a study which focused on the robust state estimation problem with outliers using the unscented Kalman filter (UKF). The quadratic cost function in the KF framework is modified by the robust cost function to robustify the KF based on a generalized maximum likelihood (GM) perspective. It explored how the robust estimate methodology can be embedded into the UKF framework without linear approximation. Also presented are simulation results and comparisons.