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一种嵌套K-means聚类的任意形状波束子阵划分方法

张清河 李宇航 沈钊阳 文方青

电子学报2025,Vol.53Issue(1):119-127,9.
电子学报2025,Vol.53Issue(1):119-127,9.DOI:10.12263/DZXB.20231119

一种嵌套K-means聚类的任意形状波束子阵划分方法

A K-means-Based Nested Subarray Partition Method for Generating Arbitrary Shaped Beam Patterns

张清河 1李宇航 2沈钊阳 1文方青1

作者信息

  • 1. 水电工程智能视觉监测湖北省重点实验室(三峡大学),湖北 宜昌 443002||三峡大学计算机与信息学院,湖北 宜昌 443002
  • 2. 三峡大学计算机与信息学院,湖北 宜昌 443002
  • 折叠

摘要

Abstract

Traditional phased arrays,due to their high cost limitations,are no longer able to meet the growing de-mand for widespread applications.However,non-traditional phased array technologies based on sparse arrays,subarrays,and other technologies have received widespread attention and research.How to effectively draw molecular arrays and opti-mize the calculation process of sub arrays are key issues in improving computational efficiency and performance.This arti-cle proposes a nested iterative optimization method that integrates swarm intelligence optimization and clustering tech-niques to solve the problem of arbitrary shaped beam subarray partitioning.This method consists of two nested loop itera-tive optimization processes:(i)The outer loop uses swarm intelligence optimization method to achieve a reference array un-der any user-defined directional pattern,and analyzes multiple sets of different unit excitations(determined by the roots of the Shekunov polynomial distributed on a non unit circle)using Shekunov polynomial and basic algebraic theory;(ii)Based on the excitation matching strategy,the inner loop aims to achieve the optimal subarray layout and corresponding subarray excitation coefficients of the phased array through K-means clustering method,and ultimately generate a beam pattern that approximates the reference array.The effectiveness of the proposed method was verified by comparing it with traditional K-means clustering methods and particle swarm optimization methods in terms of pattern approximation,excitation matching error,pattern matching error,array performance parameters,and computational efficiency.

关键词

任意形状波束阵列/子阵划分/嵌套K-means聚类/激励匹配策略/群智能优化方法

Key words

arbitrary-shaped beams array/sub-array partitioning/nested K-means clustering/excitation matching strategy/swarm intelligence optimization methods

分类

信息技术与安全科学

引用本文复制引用

张清河,李宇航,沈钊阳,文方青..一种嵌套K-means聚类的任意形状波束子阵划分方法[J].电子学报,2025,53(1):119-127,9.

基金项目

国家自然科学基金(No.62371271) National Natural Science Foundation of China(No.62371271) (No.62371271)

电子学报

OA北大核心

0372-2112

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