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The problem studied in this paper is the design of an electromagnetic target classifier for small-scale aircraft targets by using a natural resonance based feature extraction technique supported by feature fusion. The aircraft targets are modeled by perfectly conducting straight thin wire structures and the electromagnetic fields back-scattered from targets are numerically generated. This technique uses the Wigner-Ville distribution (WD) and the principal component analysis (PCA). The technique is applied to perfectly conducting targets of moderately complicated geometries for the first time. The resulting classifier is successfully demonstrated to recognize five wire-modeled aircraft targets based on a reference database that is constructed at only three different aspect angles.