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Design of Non-Uniform Circular Antenna Arrays Using a Modified Invasive Weed Optimization Algorithm

机译:基于改进的杂草优化算法的非均匀圆形天线阵列设计

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An ecologically inspired optimization algorithm, called invasive weed optimization (IWO), is presented for the design of non-uniform, planar, and circular antenna arrays that can achieve minimum side lobe levels for a specific first null beamwidth while avoiding the mutual coupling effects simultaneously. IWO recently emerged as a derivative-free real parameter optimizer that mimics the ecological behavior of colonizing weeds. For the present application, classical IWO has been modified by introducing a more explorative routine of changing the standard deviation of the seed population (equivalent to mutation step-size in evolutionary algorithms) of the algorithm. Simulation results over three significant instances of the circular array design problem have been presented to illustrate the effectiveness of the modified IWO algorithm. The design results obtained with modified IWO have been shown to comfortably beat those obtained with other state-of-the-art metaheuristics like genetic algorithm (GA), particle swarm optimization (PSO), original IWO and differential evolution (DE) in a statistically meaningful way.
机译:针对非均匀,平面和圆形天线阵列的设计,提出了一种生态学上受启发的优化算法,称为侵入性杂草优化(IWO),该阵列可以针对特定的第一个零波束宽度实现最小旁瓣电平,同时避免相互耦合效应。 IWO最近成为一种无导数的实参优化器,它可以模拟定居杂草的生态行为。对于本申请,通过引入更具探索性的例程来更改算法的种子种群的标准偏差(相当于进化算法中的突变步长),从而对经典IWO进行了修改。提出了关于圆形阵列设计问题的三个重要实例的仿真结果,以说明改进的IWO算法的有效性。用修改后的IWO获得的设计结果已证明在统计上可以轻松击败用其他最新的元启发式方法获得的结果,例如遗传算法(GA),粒子群优化(PSO),原始IWO和差分进化(DE)有意义的方式。

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