Performance evaluation of iterated extended Kalman filter with variable step-length

12th European Workshop on Advanced Control and Diagnosis

Havlík, Jindich^1 ; Straka, Ondej^1

Department of Cybernetics, European Center of Excellence: New Technologies for Information Society, University of West Bohemia, Univerzitní 8, Plze

30614, Czech Republic^1

关键词: Design parameters;    Iterated extended Kalman filter;    Nonlinear stochastic dynamic systems;    Performance evaluations;    Root mean square errors;    State estimates;    Step length;    Variable step;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/659/1/012022/pdf
DOI  :  10.1088/1742-6596/659/1/012022

来源: IOP

【 摘 要 】

The paper deals with state estimation of nonlinear stochastic dynamic systems. In particular, the iterated extended Kalman filter is studied. Three recently proposed iterated extended Kalman filter algorithms are analyzed in terms of their performance and specification of a user design parameter, more specifically the step-length size. The performance is compared using the root mean square error evaluating the state estimate and the noncredibility index assessing covariance matrix of the estimate error. The performance and influence of the design parameter, are analyzed in a numerical simulation.