Radar Target Modeling, Detection And Identification

In modern radar applications, the research about distribution of main scatterers on the target is very important for target modeling and identification. The precondition of such research work is to obtain the complex radar cross section(RCS), and then the RCS can be used to extract the distribution of the scatterers on the radar target for the purpose of target identification. In this dissertation, the main concern is focused on the RCS calculation, target modeling, target detecting and target identification. The main jobs which have been done are as follows:1. In order to obtain the complex RCS of the target quickly in high frequency band, the Graphical Electromagnetic Computing software, GRECO, is used. The modification of the computing kernel code is presented. The judgement of edges of complex targets is more sufficient and the computation of edge wave based on Physical Theory of Diffraction(PTD) is more exact after the modification.2. A frequency extrapolation scheme is developed to effectively predict radar cross section using Floating Genetic Algorithm based on the Geometrical Theory of Diffraction (GTD) model. The threshold Discrete Fourier Transform(TDFT) is introduced for the data compression in angle domain.3. A new scheme to distinguish the single target or multiple target in the case of low resolution is developed by applying the Two Scatterer Algorithm(TSA) in Complex-Image Analysis(CIA) theory, and the CIA results of a sphere and a corner reflector are studied for the purpose of target identification.4. Both CIA and Time-Frequency Analysis(TFA) are applied to the detection of the radar target in strong noise environment. These methods possess better detection ability than conventional Constant False Alert Ratio(CFAR) method.5. One dimensional TSA is expanded to two dimensional one by using two dimensional phase unwrapping technique. It is useful for the modification of some algorithms in CIA theory.