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An EKF-Based Fixed-Point Iterative Filter for Nonlinear Systems

Authors :
Xiaoliang Feng
Yuxin Feng
Chenglin Wen
Source :
Sensors, Vol 19, Iss 8, p 1893 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

In 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.

Details

Language :
English
ISSN :
14248220
Volume :
19
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.35a906d80f324a6e9acfe4079929d5cf
Document Type :
article
Full Text :
https://doi.org/10.3390/s19081893