基于粒子群算法的线性阵列SLL和FNBW优化

N. Rao, G. Ram
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引用次数: 3

摘要

在许多通信应用中,如雷达和点对点微波链路,需要窄波束宽度和低旁瓣电平波束。试图用传统的天线合成方法产生窄波束会导致更高的旁瓣电平,而试图产生低旁瓣波束会导致更宽的波束。多尔夫切比切夫线性阵列方法是一种介于SLL和FNBW之间的折衷方法。在此方法中,对于给定的波束宽度,可以得到最窄的波束宽度,对于给定的波束宽度,可以得到最小的波束宽度。但在最窄的波束宽度下,没有得到最小的SLL。本文采用粒子群优化(PSO)和遗传算法(GA)等随机随机方法,在不显著增加波束宽度的情况下获得最窄的主波束宽度,在不显著拓宽波束宽度的情况下获得最小的主波束宽度。比较了粒子群算法和遗传算法得到的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of SLL and FNBW in Linear Arrays Using PSO
In many communication applications like radar and point to point micro wave links, narrow beamwidth and low side lobe level beams are required. Trying to generate narrow beams using conventional antenna synthesis methods results in higher side lobe levels and trying to generate low side lobe beams results in broader beams. Dolph chebychev linear array method is a compromise between SLL and FNBW. In this method, for a given SLL, the narrowest beam width is obtained and for a given beamwidth the smallest SLL is obtained. But the smallest SLL for the narrowest beamwidth is not obtained. In this paper an effort is made to get the narrowest main beamwidth without significantly increasing SLL and the smallest SLL is obtained without significantly broadening the beamwidth using random stochastic methods like Particle swarm optimization (PSO) and Genetic algorithm (GA). Results obtained with PSO and results obtained with GA are compared.
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