Simulation System Based On Ground-based Radar Target Identification

Since it was been made, ballistic missile has been an efficient weapon in warfare because of its long range, strong power, high precision, good maneuverability and strong viability. As its contrary, missile defense system emerges as the times require. It provides all-orientation and multi-hierarchy defense for our basic facilities, military establishment and armies. Ground based radar (GBR) is playing a key role in missile defense because it's an indispensable tool for detecting, tracking and recognizing targets.Radar targets recognition (RTR) is one of the main functions of GBR. Depending on it, we can get description of type and estimation of threaten level for targets by dealing with the signals and information received by radar, then, provide evidence and advice for missile defense system to make the right decision. In this dissertation, base on the review and analysis of current mainstream algorithms and techniques, we build up whole RTR system, and study some efficient recognition methods for different radar characters. The major research work and contributions in this dissertation are summarized as below:1.Summarized current popular pattern recognition methods, this dissertation researched in the algorithms and performances of nearest neighbor (NN) classifier, multi-layer perceptron and RBFN (Radial Basis Function Network). Experimental results show that these three classifiers can get high recognition rate. They are simple, efficient, nonlinear and suitable for RTR.2. After analyzing the characteristic of ballistic trajectory in midcourse, we established spatial objects'kinetic model, and introduced a method for trajectory fitting and impact point estimation using a series of targets'plot detected by radar. Test results show that this method can get high precision.3.We studied the feature of targets'range profile and ISAR profile. In order to eliminate the illegibility of boundary and large dynamic range in amplitude, this dissertation presented a preprocess method for ISAR profile using adaptive threshold segment. In the stage of classification, typical simples is chosen in each scale of 17°...