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In this paper, a novel approach, namely nonlinear subprofile space (NSS), is proposed for radar target recognition using high-resolution range profile (HRRP). First, the HRRP samples are mapped into a high-dimensional feature space using nonlinear mapping. Second, the nonlinear features, namely nonlinear subprofiles, are extracted by nonlinear discriminant analysis. Then, for each class, the nonlinear subprofile space is formed using all the training nonlinear subprofiles of class. Finally, thedoi:10.2528/pierl12052302 fatcat:buiw4fnt6rcyjbw46pqxo2ufqy