We propose a novel algorithm for automatic aircraft classification. The proposed method makes numerical equivalents to
shape, size and other aircraft features as critical criteria to constitute the algorithm for their correct classification. This
method uses Inverse Synthetic Aperture Radar (ISAR) aircraft images that are making maneuvers that introduce aircraft
rotation relative to the radar station. By means of analyzing the shape of the radar pulse and Doppler shifts that are
caused by rotation of the aircraft, an image of the aircraft shape can be constructed. We computer simulated five
different categories of ISAR images. We tested the proposed classification algorithm on these five categories and on two
more categories taken from the Internet. One aircraft model is simulated and the other one is a real sequence with much
added noise. All seven different aircraft models are flying a holding pattern. We investigated where in the holding
patterns ISAR reflections made it possible to identify each category of aircraft. Our experimental results demonstrate that
in most parts of the holding pattern the category of the aircraft can be successfully identified. The performed tests show
that the proposed algorithm appears to be noise resistant.
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