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Title: Convergence analysis of the unscented Kalman filter for filtering noisy chaotic signals
Authors: Feng, J
Fan, H
Tse, CKM 
Keywords: Chaotic systems
Computational efficiency
Convergence of numerical methods
Gain measurement
Nonlinear systems
Spurious signal noise
Issue Date: 2007
Publisher: IEEE
Source: ISCAS 2007 : 2007 IEEE International Symposium on Circuits and Systems : New Orleans, Louisiana, May 27-30, 2007, proceedings, p. 1681-1684 How to cite?
Abstract: The unscented Kalman filter (UKF) has recently been proposed for filtering noisy chaotic signals. Though computationally advantageous, the UKF has not been thoroughly analyzed in terms of its convergence property. In this paper, non-periodic oscillatory behavior of the UKF when used to filter chaotic signals is reported. We show both theoretically and experimentally that the gain of the UKF may oscillate aperiodically. More precisely, when applied to periodic signals generated from nonlinear systems, the Kalman gain and error covariance of the UKF converge to zero. However, when the system being considered is chaotic, the Kalman gain either converges to a fixed point with a magnitude larger than zero or oscillates aperiodically.
ISBN: 1424409217
Rights: © 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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