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

The range proflle (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 day- night and weather conditions. Since classiflcation that uses RP and ISAR is heavily dependent on ∞ight conditions, however, much more study is required on this topic. This paper proposes an e-cient method of classifying targets by using a classifler-level fusion of RP and ISAR as well as a scenario-based construction method of the training database. Simulation results using the flve targets composed of point scatterers prove that the proposed method yields high classiflcation results when the targets are ∞ying in a variety of directions at both short and long ranges.