An unknown input extended Kalman filter for nonlinear stochastic systems - Université d'Évry
Journal Articles European Journal of Control Year : 2020

An unknown input extended Kalman filter for nonlinear stochastic systems

Abstract

This paper proposes an Unknown Input Extended Kalman Filter (UIEKF) for stochastic non linear systems affected by Gaussian noises and Unknown Inputs (UI) in both state and measurement equations. The proposed approach is based on a total decoupling of the UI, in spite of the presence of nonlinearities in the measurement equation. The UI is decoupled under some structural constraints, and a state estimator is provided. Besides an UI estimator is also proposed. Finally, the proposed filter is applied on a classical navigation example, illustrating its advantages.
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Dates and versions

hal-02513621 , version 1 (20-03-2020)

Identifiers

Cite

Luc Meyer, Dalil Ichalal, Vincent Vigneron. An unknown input extended Kalman filter for nonlinear stochastic systems. European Journal of Control, 2020, 56, pp.51--61. ⟨10.1016/j.ejcon.2020.01.009⟩. ⟨hal-02513621⟩
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