Radar Hrrp The Target Recognition Method,

The radar target recognition, which plays an important role in modern radar system, has been one of the key components of the present and future defense weapon system. The range profiles of targets, containing more information for recognition, can be obtained easily by high-range resolution radar. Many methods for feature extraction and classification in radar target recognition by range profiles are studied intensively and extensively in this dissertation. The main work of this dissertation is listed as follows:1.The scatter-center model is discussed. Four kinds of simulated point targets are designed and their rangeprofiles at aspect angles are computed.2.The classic radar target recognition method based on PCA and LDA was first reviewed. Then, PCA+LDA method is introduced into radar target recognition. Furethmore, an improved LDA was employed to address Small Sample Size (SSS) problem.3.A recently developed feature extraction method: Non-negative Matrix Factorization (NMF)– was introduced to radar target recognition. Compare to PCA, NMF learns parts-based representations of targets. To efficiently learn parts-based representations, another NMF approach NMFs (NMF with sparseness Constraints) was proposed. Experimental results showed that the parts-based features are as effective for radar range profile classification as holistic features do.4.Radar target recognition based on non-linear recognition methods (such as KPCA and KFDA) were presented. KPCA plus LDA aggregate method was especially studied. Experimantal results verified the efficiency of KPCA, KFDA, KPCA plus LDA in radar target recognition.