摘要
研究传感器阵列信号优化问题,针对传统的简单遗传算法应用于传感器阵列的波束形成时,存在收敛速度慢和计算结果稳定性低的问题,提出了一种基于改进遗传算法的波束形成优化方法。算法对简单遗传算法的初始种群生成、适应度函数、交叉算子和异化算子等多个要素进行了改进,并融入了自适应技术。将改进的遗传算法应用于波束形成,并进行了仿真。仿真结果证明,有效地提高了收敛速度和计算结果的稳定性。证明改进遗传算的波束形成方法,获得了比原始方法旁瓣级更低的波束图,波束形成的性能更优。
This paper proposes an optimization approach of beamforming based on genetic algorithm（IGA）,considering the fact that the conventional simple genetic algorithm（SGA） has disadvantages of slow convergent speed and low stability when applied in beamforming of an array.The improved algorithm makes some improvements in several factors of SGA,which include initial population creation,fitness function,crossover operator and mutation operator.And the conception of adaptation is also introduced into this algorithm.The convergent speed and stability are both effectively promoted when IGA is applied to beamforming.The results of simulation show that the sidelobe of beam pattern based on IGA is lower than that based on SGA,and the performance of beamforming based on IGA is superior to that based on SGA.
出处
《计算机仿真》
CSCD
北大核心
2010年第8期208-211,共4页
Computer Simulation
关键词
波束形成
波束图
改进遗传算法
收敛速度
稳定性
Beamforming
Beam pattern
Improved genetic algorithm
Convergent speed
Stability
