The problem studied in this thesis, is the classification of the small-scale
aircraft targets by using a natural resonance based electromagnetic feature extraction
technique. The aircraft targets are modeled by perfectly conducting, thin wire
structures. The electromagnetic back-scattered data used in the classification process,
are numerically generated for five aircraft models.
A contemporary signal processing tool, the Wigner-Ville distribution is
employed in this study in addition to using the principal components analysis
technique to extract target features mainly from late-time target responses. The
Wigner-Ville distribution (WD) is applied to the electromagnetic back-scattered
responses from different aspects. Then, feature vectors are extracted from suitably
chosen late-time portions of the WD outputs, which include natural resonance related
v
information, for every target and aspect to decrease aspect dependency. The database
of the classifier is constructed by the feature vectors extracted at only a few reference
aspects. Principal components analysis is also used to fuse the feature vectors and/or
late-time aircraft responses extracted from reference aspects of a given target into a
single characteristic feature vector of that target to further reduce aspect dependency.
Consequently, an almost aspect independent classifier is designed for small-scale
aircraft targets reaching high correct classification rate.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/3/12605522/index.pdf |
| Date | 01 October 2004 |
| Creators | Ersoy, Mehmet Okan |
| Contributors | Sayan, Gonul Turhan |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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