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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Enderli, C.J. |
| Copyright Year | 2007 |
| Description | Author affiliation: Thales Airborne Syst., Elancourt (Enderli, C.J.) |
| Abstract | This paper introduces an original supervised classification method based on the optimization of the Fisher ratio under the Volterra filtering model. Optimum Volterra filters are derived for the problem of discriminating 2 classes. They have properties yielding some decision strategy that aims to reject (i.e. take no decision) data corresponding to unlearned classes. An original extension of this solution is then proposed for the problem of discriminating more than 2 classes. Performances of our method are evaluated by classifying real data of jet fighters range profiles. Influence of the filtering model order is investigated. Interest of the waveform polarization states is also analyzed. Results obtained show that our method outperforms the nearest neighbor classification method in term of error probability, while yielding equivalent performances in term of correct identification probability. Moreover, it is shown that good rejection probability of unlearned classes can be obtained, particularly with fully-polarized data. |
| Starting Page | 817 |
| Ending Page | 821 |
| File Size | 1600048 |
| Page Count | 5 |
| File Format | |
| ISBN | 1424402832 |
| ISSN | 10975659 |
| DOI | 10.1109/RADAR.2007.374325 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-04-17 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Filtering Aircraft Context modeling Linear discriminant analysis Optimization methods Filters Error probability Radar scattering Airborne radar Radar polarimetry |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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