NDLI: The square root unscented Kalman filter formulation of risk-sensitive filter

Content Provider	IEEE Xplore Digital Library
Author	Wenyan Guo Chongzhao Han Ming Lei
Copyright Year	2008
Description	Author affiliation: Electron. & Inf. Engr, Xian Jiaotong Univ., Xian (Wenyan Guo; Chongzhao Han; Ming Lei)
Abstract	Risk-sensitive filter is a robust and numerically efficient algorithm compared to risk neutral filter with model uncertainties. For nonlinear plant, the square root unscented Kalman risk-sensitive filter (SUKRSF) is proposed in this paper by using unscented transformation approximation. Square root unscented Kalman filter (SRUKF), a derivative-free nonlinear estimation tool is used to solve risk-sensitive problem because its several intrinsic properties suggest its use over extended risk-sensitive filter (ERSF) in highly nonlinear systems. The simulation results for certain nonlinear system also show that the new algorithm has better estimation performance than ERSF while driven under the identical machine model and parameters.
Starting Page	1
Ending Page	4
File Size	226047
Page Count	4
File Format	PDF
ISBN	9783800730926
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-30
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	ISIF (Intl Society of Information Fusion)
Subject Keyword	Filtering algorithms Filtering theory Kalman filters Estimation Approximation methods Nonlinear systems Filtering risk-sensitive filters Unscented Kalman filter nonlinear
Content Type	Text
Resource Type	Article

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The square root unscented Kalman filter formulation of risk-sensitive filter