基于遗传算法的随机间隔线性阵列旁瓣电平抑制

V. S. Gangwar, A. K. Singh, S. Singh
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引用次数: 13

摘要

本文提出了一种降低旁瓣电平的随机间隔线性阵列的合成方法。假设阵列单元间的激励幅值恒定,单元间的间距保持在规定的范围内。提出了一种全局优化算法(遗传算法)来计算最小可能峰值SLL所对应的单元间间距的最优排列。为了验证所提方法的有效性,以24单元的RSLA为例进行了分析,并将数值结果与采用均匀单元间距和其他类似设计场景的方法进行了比较。此外,利用商用HFSS软件,考虑m型贴片辐射单元,研究了阵列单元之间的相互耦合对RSLA性能的影响。对具有相互耦合的m形等激励贴片单元的RSLA进行了电磁仿真,并与不具有相互耦合的贴片单元、数值结果和已发表的结果进行了比较。
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Side lobe level suppression in randomly spaced linear array using genetic Algorithm
This paper presents synthesis of randomly spaced linear array (RSLA) with reduced side lobe level (SLL). Excitation amplitude is assumed to be constant across the array elements and the inter-element spacing is kept in the specified range. A global optimization algorithm (Genetic Algorithm) is proposed to compute the optimum arrangement of inter-element spacings corresponding to lowest possible peak SLL. To validate the effectiveness of the proposed method, an example of RSLA with 24 elements is analysed and numerical results are compared with those using uniform elements' spacing and other published approaches for similar design scenario. Additionally, the effect of mutual coupling among array elements on the performance of RSLA is investigated through an extensive EM simulation study using commercial HFSS software by considering M-shaped patch radiating elements. The EM simulation results for the proposed RSLA having M-shaped equally-excited patch elements with mutual coupling among array elements are compared with those of without mutual coupling, numerical and published results.
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