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Non-uniform Circular Array Geometry Synthesis Using Wind Driven Optimization Algorithm

机译:使用风驱动优化算法的非均匀圆形阵列几何合成

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This paper describes fast, efficient and global optimization method for pattern synthesis of non-uniform circular array antenna having a minimum side lobe level (SLL) and beam width by controlling the amplitude and position-only using wind driven optimization (WDO) algorithm. The WDO is a new nature-inspired optimization technique based on the movement of air parcel in the earth's atmosphere. It uses a new learning strategy to update the velocity and position of air packets based on their current pressure values. One design example of non-uniform circular array antenna is considered and the results obtained by WDO algorithm is compared with those obtained by other evolutionary algorithms such as GA, PSO, CS, FA, BBO, COA, and MIWO. This algorithm achieves a minimum SLL compared to one of the best results obtained by the cuckoo search algorithm (COA). Also, the learning characteristic shows that WDO algorithm takes less than 50 iterations to determine the optimal excitation amplitude and position of the array element. The simulation results demonstrate the improved performance of the WDO algorithm in terms of directivity, minimum SLL, null control and the rate of convergence compared to other algorithms reported in literature.
机译:本文描述了快速,具有最小旁瓣电平(SLL)和波束宽度通过控制振幅及位置仅使用风力驱动优化(WDO)算法的非均匀圆形阵列天线的图案合成高效和全局优化方法。该WDO是基于空气包裹在地球大气运动的新灵感来自大自然的优化技术。它采用了全新的学习策略,以更新空气包根据其当前压力值的速度和位置。非均匀圆形阵列天线的一个设计实例考虑和WDO算法获得的结果与由其他进化算法如GA,PSO,CS,FA,BBO,COA,和MIWO获得的那些进行比较。相比于由杜鹃搜索算法(COA)中获得的最好的结果中的一个,该算法实现了最小SLL。另外,学习特性表明,WDO算法只需不到50次迭代来确定的数组元素的最佳激发幅度和位置。仿真结果表明该WDO算法在方向性,最小SLL,空控制,并与其他算法收敛速度方面的改进的性能在文献中报道。

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