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首页> 外文期刊>International journal of antennas and propagation >Pattern Nulling of Linear Antenna Arrays Using Backtracking Search Optimization Algorithm
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Pattern Nulling of Linear Antenna Arrays Using Backtracking Search Optimization Algorithm

机译:基于回溯搜索优化算法的线性天线阵方向图归零

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An evolutionary method based on backtracking search optimization algorithm (BSA) is proposed for linear antenna array pattern synthesis with prescribed nulls at interference directions. Pattern nulling is obtained by controlling only the amplitude, position, and phase of the antenna array elements. BSA is an innovative metaheuristic technique based on an iterative process. Various numerical examples of linear array patterns with the prescribed single, multiple, and wide nulls are given to illustrate the performance and flexibility of BSA. The results obtained by BSA are compared with the results of the following seventeen algorithms: particle swarm optimization (PSO), genetic algorithm (GA), modified touring ant colony algorithm (MTACO), quadratic programming method (QPM), bacterial foraging algorithm (BFA), bees algorithm (BA), clonal selection algorithm (CLONALG), plant growth simulation algorithm (PGSA), tabu search algorithm (TSA), memetic algorithm (MA), nondominated sorting GA-2 (NSGA-2), multiobjective differential evolution (MODE), decomposition with differential evolution (MOEA/D-DE), comprehensive learning PSO (CLPSO), harmony search algorithm (HSA), seeker optimization algorithm (SOA), and mean variance mapping optimization (MVMO). The simulation results show that the linear antenna array synthesis using BSA provides low side-lobe levels and deep null levels.
机译:提出了一种基于回溯搜索优化算法(BSA)的进化方法,用于线性天线阵列方向图合成,在干扰方向上规定了零点。通过仅控制天线阵列元件的幅度,位置和相位来获得方向图归零。 BSA是一种基于迭代过程的创新元启发式技术。给出了具有指定的单个,多个和宽零点的线性阵列模式的各种数值示例,以说明BSA的性能和灵活性。将BSA获得的结果与以下17种算法的结果进行比较:粒子群优化(PSO),遗传算法(GA),改进的旅行蚁群算法(MTACO),二次规划方法(QPM),细菌觅食算法(BFA) ),蜜蜂算法(BA),克隆选择算法(CLONALG),植物生长模拟算法(PGSA),禁忌搜索算法(TSA),模因算法(MA),非主导排序GA-2(NSGA-2),多目标差分进化(MODE),具有差分进化的分解(MOEA / D-DE),全面学习PSO(CLPSO),和声搜索算法(HSA),搜寻器优化算法(SOA)和均值方差映射优化(MVMO)。仿真结果表明,使用BSA的线性天线阵列合成可提供较低的旁瓣电平和较深的零电平。

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