Kalman and smooth variable structure filters for robust estimation

Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/30139

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DC Field	Value	Language
dc.contributor.author	Gadsden SA	-
dc.contributor.author	Habibi S	-
dc.contributor.author	Kirubarajan T	-
dc.date.accessioned	2024-09-08T17:16:59Z	-
dc.date.available	2024-09-08T17:16:59Z	-
dc.date.issued	2014-01-01	-
dc.identifier.issn	0018-9251	-
dc.identifier.issn	1557-9603	-
dc.identifier.uri	http://hdl.handle.net/11375/30139	-
dc.description.abstract	The extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are among the most popular estimation methods. The smooth variable structure filter (SVSF) is a relatively new sliding mode estimator. In an effort to use the accuracy of the EKF and the UKF and the robustness of the SVSF, the filters have been combined, resulting in two new estimation strategies, called the EK-SVSF and the UK-SVSF, respectively. The algorithms were validated by testing them on a well-known target tracking computer experiment. © 2014 IEEE.	-
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)	-
dc.rights.uri	7	-
dc.subject	40 Engineering	-
dc.subject	4001 Aerospace Engineering	-
dc.title	Kalman and smooth variable structure filters for robust estimation	-
dc.type	Article	-
dc.date.updated	2024-09-08T17:16:58Z	-
dc.contributor.department	Mechanical Engineering	-
dc.rights.license	Attribution-NonCommercial-NoDerivs - CC BY-NC-ND	-
dc.identifier.doi	https://doi.org/10.1109/taes.2014.110768	-
Appears in Collections:	Mechanical Engineering Publications

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