Abstract
The study utilises two shape factors as the radar feature set for the recognition of a mid-sized aircraft target in the high-frequency (HF) band. The two shape factors are the dihedral and tilt features of the aircraft parts. The determination of the two shape factors is feasible through the optimum polarisation states of the target's complex natural resonances in the HF band. The identification algorithm applies a resonance-weighted measure to the feature set in a supervised learning approach to discriminate between two targets of the same class that slightly differ in shape. The rate of correct recognition within a sector of the target aspect exceeded 80% for receiver sensitivity above −10 dB.
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