Application of a natural-resonance based feature extraction technique to small-scale aircraft wires for electromagnetic target classification

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2004

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Ersoy, Mehmet Okan

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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.

Subject Keywords

Applications of Electric Power.

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http://etd.lib.metu.edu.tr/upload/3/12605522/index.pdf
https://hdl.handle.net/11511/14592

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. O. Ersoy, “Application of a natural-resonance based feature extraction technique to small-scale aircraft wires for electromagnetic target classification,” M.S. - Master of Science, Middle East Technical University, 2004.