利用基因算法确定阵列天线的激励系数

为了提高天线增益和辐射效率,降低副瓣电平,特别是在许多应用中需要天线方向图形成赋形波束以达到所需的效果而采用天线阵[1],[引.对于形成辐射方向图已提出许多方法来确定阵列天线的激励系数,通常这些方法是以波束控制或旁瓣抑制为根据,采用解析逼近共轭梯度法.但是如果调整n个参变量或者要形成多波束的话,那么要找出最佳性能指标是困难的.并且大多数天线方向图在零点或接近零点处的斜率很大,这意味着收敛性差.为了解决这些问题,可以采用基因算法(Genetic Algorithms)来确定激励系数的最佳集合.基因算法是模拟生物进化过程的计算模型,作为一种新的全局优化搜索算法,其简单通用、鲁捧性强,适于并行处理而得到了广泛应用.

The Decision of the Stimulation Coeffcients of the Antenna Array by Genetic Algorithms

s:In order to improve the gain of antenna, the efficiency of radiation and reduce the power level of side-lope, the antenna array is deployed especially in many applications in order to get the wanted results to shape the oriented graphics into a wave beam with assigned form. Many methods are put forward to deciding the stimulation coefficients of the antenna array about the shaping of oriented graphics and these methods are usually based on the wave beam control or side-lope suppress using the analytic conjugate gradient algorithm. But it is difficult to find out the optimum targets of performance, if n parameters should be adjusted or the multi-beam be wanted. What's more, the slopes of most of the oriented graphics of antenna are large in zero point or near the zero point, which means a bad convergence. In order to solve these problems, the Genetic Algorithms can be used to make sure of the optimum collection of the stimulation coefficient. Genetic Algorithms is a computing model which simulates the development of the procedure of the creature, and as a new global optimum search method, it is widely used because of its simplicity, strong robust and ability suitable to the parallel process.