基于并查集的低复杂度模糊聚类信号分选算法  

Low complexity fuzzy clustering signal sorting algorithm based on union-find set

作　　者：张悦 司伟建[1,2] ZHANG Yue;SI Weijian(College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China;Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学信息与通信工程学院,哈尔滨150001 [2]哈尔滨工程大学先进船舶通信与信息技术工业和信息化部重点实验室,哈尔滨150001

出　　处：《电波科学学报》2021年第5期797-806,共10页Chinese Journal of Radio Science

基　　金：中央高校基本科研业务费专项(3072020CF0814);航空科学基金(2019010P6001,2019010P6002)。

摘　　要：随着雷达技术与电子技术的不断发展,电子对抗环境日趋复杂.为能够在复杂电子对抗环境中进行实时有效的信号分选,提出了一种基于并查集的低复杂度模糊聚类信号分选算法.通过计算两脉冲间相似度,以相似度高于阈值作为集合归并条件,依次完成集合归并后查询并查集完成聚类结果输出.通过结合并查集与模糊聚类分选算法,大大降低了模糊聚类分选算法的复杂度,本文所提算法时间复杂度为O(n2),空间复杂度为O(n).由于该算法具有低复杂度的特点,可应用于工程项目.With the continuous development of radar technology and electronic technology, the complexity of electronic countermeasure environment is increasing. To perform real-time and effective signal sorting in the complex electronic countermeasure environment, a low complexity fuzzy clustering signal sorting algorithm based on union-find set is proposed. It is used as the set merge condition that the similarity between the two pulses is higher than the threshold. After the sets are merged in turn, the union-find set is queried and the clustering result output is completed.By combining union-find set and fuzzy clustering sorting algorithms, the complexity of the fuzzy clustering sorting algorithm is greatly reduced. It can be proved that the time complexity of the algorithm is complexity is O( n). Due to its low complexity, the algorithm can be applied to engineering projects.

关 键 词：电子对抗 信号分选 模糊聚类 低复杂度 并查集 

分 类 号：TN957.51[电子电信—信号与信息处理]