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Optimal design of subarray configurations for large phased antenna array based on modified clustering method

机译:基于改进聚类方法的大相控天线阵子阵配置优化设计

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Subarray partition technique is widely employed in large phased array radar system design with purposes of low complexity and computation burden. In order to reduce the performance loss caused by inappropriate subarray partition, optimization of subarray partition should be considered. An optimal method based on a weighted K-means clustering is investigated in this paper. The optimization can be formulated as a clustering problem according to the excitation matching principle. When the elements are weighted uniformly, K-means clustering method can provide the minimum excitation matching error. However, the error cannot be minimized completely when the elements are weighted non-uniformly for specific intensions such as low sidelobes. Therefore, a weighted K-means clustering method is proposed in this paper to reduce the error for non-uniform element weights, which takes full advantages of the element weights by modifying the membership rule and clustering center of K-means clustering. Numerical simulations are carried out to verify the effectiveness of proposed method.
机译:子阵列划分技术广泛应用于大型相控阵雷达系统设计中,其目的是降低复杂度和降低计算负担。为了减少因不适当的子阵列分区而导致的性能损失,应考虑优化子阵列分区。研究了基于加权K-均值聚类的最优方法。可以根据激励匹配原理将优化公式化为聚类问题。当元素被均匀加权时,K-均值聚类方法可以提供最小的激励匹配误差。但是,当针对特定强度(例如低旁瓣)对元素进行非均匀加权时,无法完全减小误差。因此,本文提出了一种加权的K均值聚类方法,以减少非均匀元素权重的误差,该方法通过修改K均值聚类的隶属规则和聚类中心,充分利用了元素权重。通过数值模拟验证了所提方法的有效性。

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