Classification of Targets Improved by Fusion of the Range Profile and the Inverse Synthetic Aperture Radar Image

The range profile (RP) and the inverse synthetic aperture radar (ISAR) image are the useful radar signatures for classifying unknown targets because they can be used regardless of daynight and weather conditions. Since classification that uses RP and ISAR is heavily dependent on flight conditions, however, much more study is required on this topic. This paper proposes an efficient method of classifying targets by using a classifier-level fusion of RP and ISAR as well as a scenario-based construction method of the training database. Simulation results using the five targets composed of point scatterers prove that the proposed method yields high classification results when the targets are flying in a variety of directions at both short and long ranges.