关键词: 隐性交叉遗传算法, 广义回归神经网络, 实时动态, 导弹追踪目标, 导航常量

Abstract: Guidance and control algorithm is complex when missile tracking targets in three-dimensional environment, which will cause complex computing, for which a real-time dynamic tracking target model based on general regression neural network optimized by recessive crossover genetic algorithm is proposed. Missile defense is discretized into many little models so as to generating imputing data, RCGA is used to estimate the navigation constant and notice time for each acceptable target parameter data set. Inputted and outputted target parameter data sets are used to generate training set needed by GRNN. The trained GRNN is applied into implementation of missile guidance real-time system. The effectiveness and reliability of proposed algorithm has been verified by tactical target simulation model. Simulation results show that proposed algorithm has better instantaneity and higher target positional accuracy than several target tracking algorithms.

Key words: recessive crossover genetic algorithm, general regression neural network, real time dynamics, missile tracking target, navigation constant