Design And Implementation Of Radar Emitter Recognition System Based On Parallel Boosting Algorithm

Electronic War is the important form for today's warfare. Radar plays an important role in battle field. Only by obtaining the parameters and system information of enemy radars can we have mastery about their work state, control mode of their correlative weapon system, the tactics feature and fight capability etc, and then we can provide decision evidence to commanders. So the exact recognition of radar is of great significance in contemporary war.The new method of radar emitter recognition constructed with parallel boosting algorithm is introduced in this paper. In the paper feature extracting theory is discussed comprehensively. The dataset of the system is pretreated, and the high dimensions data is projected onto low dimensions data so as to raise the recognition ratio. As the basic classifier algorithm of parallel boosting, the BP neural network is also discussed in detail, and a rational neural network configuration is made successfully which is suitable for the system. Finally, we focus on the study of parallel Boosting algorithm and the study of designing, constructing, improving of multiple classify implement under the environment of multiprocessor, and we find that this method is very effective by testing it with RADAR dataset, and its recognition time is relatively less than other similar methods. Meanwhile, compared with the test results of basic classifier algorithm BP, Parallel boosting method is able to raise remarkably the detect ratio of weak classifier. And the theory of the multiple classifier system is feasible.