Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/30139
Title: | Kalman and smooth variable structure filters for robust estimation |
Authors: | Gadsden SA Habibi S Kirubarajan T |
Department: | Mechanical Engineering |
Keywords: | 40 Engineering;4001 Aerospace Engineering |
Publication Date: | 1-Jan-2014 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
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. |
metadata.dc.rights.license: | Attribution-NonCommercial-NoDerivs - CC BY-NC-ND |
URI: | http://hdl.handle.net/11375/30139 |
metadata.dc.identifier.doi: | https://doi.org/10.1109/taes.2014.110768 |
ISSN: | 0018-9251 1557-9603 |
Appears in Collections: | Mechanical Engineering Publications |
Files in This Item:
File | Description | Size | Format | |
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010-Kalman_and_smooth_variable_structure_filters_for_robust_estimation.pdf | 1.72 MB | Adobe PDF | View/Open |
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