Radiation Pattern Synthesis for Adaptive Antenna Arrays Using Improved Quantum Genetic Algorithm

Ming Liu, Chaowei Yuan, Tian-Song Li, Hong-Hai Wu
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引用次数: 6

Abstract

In this paper, compared with genetic algorithm (GA), an improved quantum genetic algorithm (QGA) was proposed, and it was used to calculate the complex excitations, amplitudes and phases of adaptive antenna arrays. The optimization goal is to maximize the output power of the desired signal and minimize the total output power of the interfering signals. Simulation results show that the improved QGA has better performance than existing GA.
基于改进量子遗传算法的自适应天线阵辐射方向图合成
在遗传算法(GA)的基础上,提出了一种改进的量子遗传算法(QGA),并将其用于自适应天线阵的复杂激励、幅值和相位的计算。优化目标是使期望信号的输出功率最大化,使干扰信号的总输出功率最小。仿真结果表明,改进后的QGA比现有的遗传算法具有更好的性能。
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