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Research Paper | Aerospace Engineering | Kuwait | Volume 6 Issue 4, April 2017
Aircraft Target Identification by Null Polarization Based Feature Set
Abstract: The paper utilizes a small feature set formed by the polarization nulls of the targets resonances to identify airborne model targets. Once linked to the target resonances, the small feature set can reflect shape attributes like the elongation, symmetry, and tilt degrees in the individual target substructures. Based on a 3D feature space formed by these three degrees, the identification approach applies Euclidean distance measure to identify two electrically similar targets of similar resonance behavior. The identification performance indicated that the feature set is robust, and in particular, the elongation feature demonstrated superior discriminative ability.
Keywords: Characteristics Polarization Theory, Radar Target Identification, Supervised Learning, Lagrangian Optimization
Edition: Volume 6 Issue 4, April 2017,
Pages: 1028 - 1032
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