Kalman and smooth variable structure filters for robust estimation

dc.contributor.author	Gadsden SA
dc.contributor.author	Habibi S
dc.contributor.author	Kirubarajan T
dc.contributor.department	Mechanical Engineering
dc.date.accessioned	2024-09-08T17:16:59Z
dc.date.available	2024-09-08T17:16:59Z
dc.date.issued	2014-01-01
dc.date.updated	2024-09-08T17:16:58Z
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.identifier.doi	https://doi.org/10.1109/taes.2014.110768
dc.identifier.issn	0018-9251
dc.identifier.issn	1557-9603
dc.identifier.uri	http://hdl.handle.net/11375/30139
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.rights.license	Attribution-NonCommercial-NoDerivs - CC BY-NC-ND
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

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