Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21519
Title: A class of stable square-root nonlinear information filters
Authors: Wang, S
Feng, J
Tse, CK 
Keywords: Nonlinear estimation
nonlinear information filter
numerical stability
square-root decomposition
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on automatic control, 2014, v. 59, no. 7, 6681929, p. 1893-1898 How to cite?
Journal: IEEE transactions on automatic control 
Abstract: Information filters can process nonlinear systems with uncertain prior knowledge, and the particular square-root form of adaptive filters can improve numerical stability. Based on a square-root decomposition of information matrix and an extra positive definite matrix, the unscented transform and the cubature rule are applied to the information filtering architecture for nonlinear estimation. A class of stable square-root nonlinear information filters is then proposed in this technical note. In addition, the boundedness of their estimation errors is also proven. Results from simulations of filtering a chaotic map demonstrate that the proposed square-root nonlinear filters can improve numerical stability, and has better filtering performance than other information filters.
URI: http://hdl.handle.net/10397/21519
ISSN: 0018-9286
EISSN: 1558-2523
DOI: 10.1109/TAC.2013.2294619
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