基于粒子群算法的阵列天线波束赋形

文中介绍了粒子群算法的基本原理和基本流程,并将其用于阵列天线的波束赋形设计.粒子群算法是在遗传算法基础上发展起来的一种新的并行优化方法,可用于解决大量非线性、不可微和多峰值的复杂问题.与遗传算法不同的是,粒子群算法中的粒子有记忆功能,整个搜索过程是跟随当前最优粒子的过程,因此在大多数情况下,所有的粒子可能更快的收敛于最优解.而且粒子群算法理论简单,参数少,因此其应用更为广泛.文中把粒子群算法用于阵列天线的波束赋形,结果表明粒子群算法在对天线形状进行设计方面有很好的发展前景.

Pattern synthesis of array antenna based on PSO

In this paper,the principle of particle swarm optimization(PSO)algorithm is introduced,by which pattern synthesis of array antenna is designed.PSO can be used in problems with mass nonlinear,nonderivative and multipeaked values,which is a new parallel optimization algorithm based on GA.Different from GA,members in PSO can remember and share information about best positions founding during their searching for food.Hence most of the time,PSO has faster convergence.Moreover,PSO has simpler principle,fewer parameters.So PSO can be used in various areas.In this paper PSO is used in pattern synthesis of antenna,and results indicate that PSO has better prospects in pattern synthesis of antenna.