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Synthesizing broad null in linear array by amplitude-only control using wind driven optimization technique

机译:使用风驱动优化技术通过幅度控制在线性阵列中合成宽无空

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This paper describes fast, efficient and global optimization method called wind driven optimization (WDO) algorithm for nulling pattern synthesis of uniformly spaced linear array having maximum side lobe level (SLL) suppression, restricted dynamic range ratio (DRR), beam width and null control by controlling the array elements amplitude-only. A broad null is placed in the direction of maximum interference by undesired signals while receiving signal from the desired direction. The WDO is a new nature-inspired evolutionary algorithm derived from to the point movement of the 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 to accelerate the convergence. The pressure (objective) function is based on an exact penalty method. The results are compared with those obtained by other evolutionary algorithm such as bacterial foraging optimization (BFO), plant growth simulation algorithm (PGSA) and bee algorithm. The simulation study demonstrates that the WDO outperforms the three algorithms particularly in terms of minimum SLL, beam width control, DRR, null control and the rate of convergence.
机译:本文介绍了一种良好,高效,全球优化方法,称为风驱动优化(WDO)算法,用于均匀间隔的线性阵列的均线合成,具有最大侧瓣级(SLL)抑制,受限的动态范围比(DRR),光束宽度和空控制仅通过控制阵列元素幅度。在从所需方向接收信号的同时,通过不需要的信号放置宽无空方的方向。 WDO是一种新的自然启发进化算法,它来自地球大气中的空气包裹的点运动。它使用新的学习策略来根据其当前压力值更新空中数据包的速度和位置,以加速收敛。压力(目标)功能基于精确的惩罚方法。将结果与其他进化算法获得的结果进行比较,例如细菌觅食优化(BFO),植物生长模拟算法(PGSA)和BEE算法。仿真研究表明,WDO优于三种算法,特别是在最小SLL,光束宽度控制,DRR,空控制和收敛速率方面。

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