Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/31199| Title: | Application of the smooth variable structure filter to a multi-target tracking problem |
| Authors: | Gadsden SA Dunne D Tharmarasa R Habibi SR Kirubarajan T |
| Department: | Mechanical Engineering |
| Keywords: | 40 Engineering;4006 Communications Engineering;4009 Electronics, Sensors and Digital Hardware;51 Physical Sciences;5102 Atomic, Molecular and Optical Physics |
| Publication Date: | 13-May-2011 |
| Publisher: | SPIE, the international society for optics and photonics |
| Abstract: | The most popular and well-studied estimation method is the Kalman filter (KF), which was introduced in the 1960s. It yields a statistically optimal solution for linear estimation problems. The smooth variable structure filter (SVSF) is a relatively new estimation strategy based on sliding mode theory, and has been shown to be robust to modeling uncertainties. The SVSF makes use of an existence subspace and of a smoothing boundary layer to keep the estimates bounded within a region of the true state trajectory. This article discusses the application of two estimation strategies (the KF and the SVSF) on a multi-target tracking problem. © 2011 SPIE. |
| URI: | http://hdl.handle.net/11375/31199 |
| metadata.dc.identifier.doi: | https://doi.org/10.1117/12.884063 |
| ISSN: | 0277-786X 1996-756X |
| Appears in Collections: | Mechanical Engineering Publications |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 015-gadsden_conf_015.pdf | Published version | 577.99 kB | Adobe PDF | View/Open |
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