Study On Recognition Of Radar Target Using Range Profiles

The automatic radar target recognition system, which is one of the key components of present and future defense weapon systems, is widely and intensively focused by all of the countries. The scattering information collected by the different radars is different. The rangeprofile can be formed by high-range resolution radar (HRR). The rangeprofiles of the targets contain more information for recognition than the radar cross section (RCS). Some methods of radar target recognition are intensively and extensively studied in this paper. The method for building target library is also discussed. The main contents and new ideas include:The scatter-center model is discussed. The four kinds of simulated point targets are designed and the rangeprofiles at aspect angle are computed.The radar target recognition method based on the modified canonical subspace is investigated. First, the dimension of the modified canonical subspace are not limited by the number of target classes; Second, in the sense of separability, the modified canonical subspace transformation is optimal to the canonical subspace transformation. Therefore, the recognition performance is improved.The radar target recognition method based on the optimal cluster centers is studied. The optimal transformation matrix is formed by training sample set. The difference between the same classes is reduced by using this optimal transformation. The difference between the different classes is enhanced by selecting the optimal cluster centers in feature space.The optimal projection plane based radar target recognition method is discussed. The recognition problem for many classes is changed into the recognition problem for two classes. For two classes problem, the optimal projection plane method is used. The votes for each class are collected and a final decision made in accord with the class having the most votes. The ideathat the recognition problem for many classes is turned into the recognition problem for two classes may be applied to the canonical subspace method.The unknown target rejected method for building target library is investigated. The unknown target rejected threshold (UTRT) is used in classification phase of the conventional recognition approach to reject the unknown targets that are not included in training dataset. This may be used to build target library dynamically.All of these methods are proved by experiments on simulated data and real data of planes. These methods can be applied to automatic and real time recognition systems.