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http://hdl.handle.net/11375/31216| Title: | Target tracking formulation of the SVSF as a probabilistic data association algorithm |
| Authors: | Attari M Gadsden SA Habibi SR |
| Department: | Mechanical Engineering |
| Keywords: | 40 Engineering;4001 Aerospace Engineering |
| Publication Date: | 1-Jan-2013 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Abstract: | Target tracking algorithms are important for a number of applications, including: physics, air traffic control, ground vehicle monitoring, and processing medical images. The probabilistic data association algorithm, in conjunction with the Kalman filter (KF), is one of the most popular and well-studied strategies. The relatively new smooth variable structure filter (SVSF) offers a robust and stable estimation strategy under the presence of modeling errors, unlike the KF method. The purpose of this paper is to introduce and formulate the SVSF-PDA, which can be used for target tracking. A simple example is used to compare the estimation results of the popular KF-PDA with the new SVSF-PDA. © 2013 AACC American Automatic Control Council. |
| URI: | http://hdl.handle.net/11375/31216 |
| metadata.dc.identifier.doi: | https://doi.org/10.1109/acc.2013.6580830 |
| ISSN: | 0743-1619 2378-5861 |
| Appears in Collections: | Mechanical Engineering Publications |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 030-gadsden_conf_030.pdf | Published version | 386.14 kB | Adobe PDF | View/Open |
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