An EKF-Based Fixed-Point Iterative Filter for Nonlinear Systems
AbstractIn this paper, a fixed-point iterative filter developed from the classical extended Kalman filter (EKF) was proposed for general nonlinear systems. As a nonlinear filter developed from EKF, the state estimate was obtained by applying the Kalman filter to the linearized system by discarding the higher-order Taylor series items of the original nonlinear system. In order to reduce the influence of the discarded higher-order Taylor series items and improve the filtering accuracy of the obtained state estimate of the steady-state EKF, a fixed-point function was solved though a nested iterative method, which resulted in a fixed-point iterative filter. The convergence of the fixed-point function is also discussed, which provided the existing conditions of the fixed-point iterative filter. Then, Steffensen’s iterative method is presented to accelerate the solution of the fixed-point function. The final simulation is provided to illustrate the feasibility and the effectiveness of the proposed nonlinear filtering method. View Full-Text
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Feng, X.; Feng, Y.; Wen, C. An EKF-Based Fixed-Point Iterative Filter for Nonlinear Systems. Sensors 2019, 19, 1893.
Feng X, Feng Y, Wen C. An EKF-Based Fixed-Point Iterative Filter for Nonlinear Systems. Sensors. 2019; 19(8):1893.Chicago/Turabian Style
Feng, Xiaoliang; Feng, Yuxin; Wen, Chenglin. 2019. "An EKF-Based Fixed-Point Iterative Filter for Nonlinear Systems." Sensors 19, no. 8: 1893.
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