Radar Target Distance As Identification Method

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 main contents and new ideas include:The scatter-center model is discussed. The three kinds of simulated point targets are designed and the rangeprofiles at aspect angle are computed.The radar target recognition method based on the optimal cluster centers is simulated and studied. It is discovered that the algorithm is effective when there are lots of training data, but noneffective when there are only a few training data.The reason of the above error is found out: the recognition method based on the optimal cluster centers disposes badly-conditioned matrixes inaccurately. So, an improved approach based on optimal cluster centers is proposed. It's core spirit is transforming badly-conditioned matrixes to well-conditioned matrixes, then accurate recognition results are obtained. It inherits advantage of the recognition method based on the optimal cluster centers.Radar target recognition by a logarithm bispectrum-based method is simulated and studied. It is discovered that the more test samples that generate the subrangeprofile of logarithm of averaged bispectrum are, the higher recognition rate is.And using phase information is a key to obtaining high recognition rate.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.