Secondary Filtering Update Algorithm for Nonlinear Systems—Based on Extended Kalman Filter

Based on the fixed point theory, in this paper, a novel extended Kalman filtering algorithm with secondary filtering update is proposed for nonlinear systems. As we all known, the traditional extended Kalman filter which based on the Taylor series expansion of nonlinear system function, only retains the first-order approximation term, and omits the second-order and higher order terms. It is inevitable to reduce the estimation accuracy. This paper compensates and updates it by constructing a secondary filtering update algorithm. The secondary filtering algorithm constructs the filtering state estimation equation into a fixed point equation and updates the state estimate by solving the fixed point equation. The final simulation results verify the effectiveness and feasibility of the proposed method.