摘要
针对标准粒子群算法在阵列综合应用中收敛所需的迭代次数较多、收敛速度较慢等问题,提出了一种基于改进适应度函数计算的粒子群改进算法。根据阵列在采用标准粒子群算法时的收敛趋势,提出在适应度函数计算中,对适当角度范围内的适应度函数进行加权计算,使影响收敛速度因素的计算权值得到提高、并得到优先处理,从而降低平均计算时间。通过对线阵天线的仿真实验,结果表明该方法效果明显,可以在满足方向图要求的前提下,大大减少收敛所需迭代的次数,加快收敛速度。
An improved particle swarm optimization algorithm based on improved fitness function calculation is proposed to solve the problems of overmuch iterativeness and slow evolving speed of convergence in array synthesis.Based on the convergence trend,the proposed method conducts weighted calculation in an appropriate range in the fitness function calculation,so it can deal with the facts which affect the speed of convergence.The simulation experiment of a linear array antennas indicates that the effect is distinct.In the prerequisite of pattern request being satisfied,it can decrease the number of iterativeness and increase the speed of convergence greatly.
出处
《雷达科学与技术》
2011年第3期281-285,共5页
Radar Science and Technology
关键词
粒子群优化(PSO)
适应度函数
方向图综合
线阵天线
particle swarm optimization（PSO）
fitness function
pattern synthesis
linear array antenna
