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Optimized hyper beamforming of receiving linear antenna arrays using Firefly algorithm

机译:使用Firefly算法优化接收线性天线阵列的超波束成形

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In this paper, an optimized hyper beamforming method is presented based on a hyper beam exponent parameter for receiving linear antenna arrays using a new meta-heuristic search method based on the Firefly algorithm (FFA). A hyper beam is derived from the sum and difference beam patterns of the array, each raised to the power of a hyper beam exponent parameter. As compared to the conventional hyper beamforming of the linear antenna array, FFA applied to the hyper beam of the same array can achieve much more reduction in sidelobe level (SLL) and improved first null beam width (FNBW), keeping the same value of the hyper beam exponent. As compared to the uniformly excited linear antenna array with inter-element spacing of λ/2, conventional non-optimized hyper beamforming and optimal hyper beamforming of the same obtained by real-coded genetic algorithm, particle swarm optimization and Differential evolution, FFA applied to the hyper beam of the same array can achieve much greater reduction in SLL and same or less FNBW, keeping the same value of the hyper beam exponent parameter. The whole experiment has been performed for 10-, 14-, and 20-element linear antenna arrays.
机译:本文提出了一种基于超波束指数参数的优化超波束成形方法,该方法采用基于萤火虫算法(FFA)的新型元启发式搜索方法来接收线性天线阵列。从阵列的和光束图和差光束图得出超光束,每个光束图提高到超光束指数参数的幂。与线性天线阵列的常规超波束成形相比,应用于同一阵列的超波束的FFA可以实现更多的旁瓣电平(SLL)减小和改善的第一空波束宽度(FNBW),并保持相同的超束指数。与单元间间隔为λ/ 2的均匀激发线性天线阵列相比,通过实编码遗传算法,粒子群优化和差分进化获得的常规非优化超波束成形和最优超波束成形,FFA应用于相同阵列的超光束可以实现更大的SLL降低,以及相同或更少的FNBW,同时保持相同的超光束指数参数值。整个实验已针对10个,14个和20个元素的线性天线阵列进行。

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