Aircraft recognition using a statistical model and sparserepresentation

International audienceThis paper presents a novel approach for automatic targetrecognition (ATR) using inverse synthetic aperture radar(ISAR) images. This proposed approach is mainly com-posed of two steps. In the rst step, we adopt a statisti-cal method to compute a novel target template from fea-ture descriptors. The proposed template is achieved bycombining the Gamma statistical parameters of the bothdual-tree complex wavelet transform (DT-CWT) coecientsand the scale-invariant feature transform (SIFT) descrip-tor. In order to validate the proposed target template,we achieve in the second step the recognition task usinga sparse representation-based classication (SRC) method.The performance of the proposed approach has been success-fully veried using ISAR images reconstructed from anechoicchamber. The experimental results show that the proposedmethod can achieve a high average accuracy and is signi-cantly superior to the well-known SVM classier