Ground Moving Targets Recognition Based on Chaos Genetic Algorithm

The target feature selection and the hidden layer numbers confirm of the neural network are the key problems in the radar target identification. In this paper initial population suitable for ground moving targets recognition is constructed. Then the alterable crossover probability and alterable mutation probability are proposed, which consider the influence of every generation to algorithm and the effect of different individual fitness in every generation. A satisfying result is acquired after many times crossover and mutation operation. At last by analysis and comparison of the final classification results of three kinds of ground moving targets, the feasibility and effectiveness are tested.