基于混沌遗传算法的二维平面阵研究

Research on two-dimensional planar array based on chaotic genetic algorithm

针对一般均匀平面阵列方向图旁瓣较高的问题,利用传统遗传算法对均匀阵进行二维稀布排列,有效降低了旁瓣电平,但遗传算法收敛速度慢,容易陷入局部最优解。因混沌优化算法具有随机性、遍历性以及规律性的特性,把混沌优化算法引入到遗传算法中,利用混沌序列初始化种群,可提高遗传算法的收敛速度和获得全局最优解的能力。因此,提出一种基于混沌优化算法的遗传算法,并把该算法应用到二维平面阵天线设计中,该算法对天线阵的排布进行了优化设计。仿真结果显示混沌遗传算法的收敛速度有所提高,阵列天线的副瓣电平进一步降低,说明该方法具有一定的可行性。

Aiming at the problem of high sidelobe in the pattern of general uniform planar array,the traditional genetic algorithm is used to arrange the uniform array in two-dimensional sparse distribution,which effectively reduces the sidelobe level,but the convergence speed of genetic algorithm is slow and easy to fall into local optimal solution.Because chaotic optimization algorithm has the characteristics of randomness,ergodicity and regularity,introducing chaotic optimization algorithm into genetic algorithm and initializing population by chaotic sequence can improve the convergence speed of genetic algorithm and the ability to obtain global optimal solution.Therefore,a genetic algorithm based on chaotic optimization algorithm is proposed and applied to the design of two-dimensional planar array antenna.The algorithm optimizes the layout of antenna array.The simulation results show that the convergence speed of chaotic genetic algorithm is improved and the sidelobe level of array antenna is further reduced,which shows that this method is feasible.