LAUSR

This article focuses on the orthogonal vector-based linear Kalman filter (LKF) and provides a systematic design guideline. To optimize the steady-state performance, a parameter tuning algorithm and a decoupling method are proposed. In this way, one can tune the Kalman gains individually and reduce the coupling between harmonic models. A stability analysis is also conducted in this part, which helps to properly design the steady state of the LKF. To optimize the dynamic performance and take the maximum benefit out of the adaptive mechanism of the LKF, a dynamic tracking algorithm is proposed in this article. Compared with the conventional filtering/synchronization methods, the proposed LKF can achieve a relatively fast dynamic response, small overshoot/peak errors, and good filtering capability. These advantages are verified by experiments.