Radar Target High-resolution Distance As Identification Method

The automatic radar target identification system, which is one of the momentous components of present and future defensive weapon systems, is much accounted of almost all countries. The scattering information collected by different radar systems is different. The range profile can be obtained by High range resolution (HRR)radar easily。There is much more information to recognize the targets contained in the range profile than in the radar cross section (RCS)。Some methods of radar target identification are intensively and extensively studied in this dissertation。The main contents include:High resolution range profile of emulational radar targets is discussed in chapter 2.Characteristics of them are analysed also.The radar targets identification based on feature extraction with wavelet transformation and nearest-distance classer is studied in chapter 3.Discrete orthogonal wavelet transformation and wavelet transformation based on Beylkin algorithm are applied to the samples of the targets to test their performance.The former has a better antinoise performance and the latter has a better identification rate.The radar target identification based on artificial neural network is the protagonist of the chapter 4.BP network and wavelet network are used to classified the emulational radar targets.With the powerful capability of non-linnear identification of BP neural network,its'born limitations such as local extremum,slow convergence etc. can be reformed by the wavelet network,which is a network with a wavelet function embedded into the node of a BP network.The radar targets identification based on SVM is studied in chapter 5.With the balance of the empirical risk minimum and complication,the method has a better classification performance.The validity of these methods are verified by experiments on simulated data.