Radar signal sorting method based on data field combined PRI transform and clustering

被引：3
|
作者：
Zhang Y. [1 ,2 ,3 ]
Guo W. [1 ,3 ]
Kang K. [1 ,3 ]
Yao Y. [2 ]
Zhang L. [1 ,3 ]
Zhang W. [1 ,3 ]
机构：
[1] Deparment of Operational Support, Rocket Force University of Engineering, Xi'an
[2] Unit 96816 of the PLA, Jinhua
[3] Deparment of Operational Support, Rocket Force University of Engineering, Xi'an
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2019年 / 41卷 / 07期
关键词：
Data field; K-means clustering; Pulse description words (PDW); Pulse repetition interval (PRI) transform; Radar signal sorting;
D O I：
10.3969/j.issn.1001-506X.2019.07.11
中图分类号：
学科分类号：
摘要：
In radar signal sorting based on pulse description words (PDW), the traditional clustering algorithm needs to set the clustering center and the number of clustering in advance. To solve this problem, this paper proposes a new radar signal sorting method, which combines pulse repetition interval (PRI) transform and clustering based on the data field theory. Firstly, noise points are removed based on the potential value according to the data field theory, and then the PRI transformation algorithm is used to obtain the PRI estimate. Based on the PRI value, the pre-classification of normalized PDW data are carried out to calculate all kinds of center points, and the kinds with the euclidean distance of its center points less than the radiation factor are combined to determine the initial clustering center and the number of clustering automatically. Finally, the improved K-means algorithm is used for clustering and sorting. Simulation results show that the proposed method can deal with the complex signal environment with frequency agility, repeated frequency fluctuation, jitter, overlapping parameters and partial pulse loss, and the correct sorting probability is obviously improved. © 2019, Editorial Office of Systems Engineering and Electronics. All right reserved.
引用
收藏
页码：1509 / 1515
页数：6
相关论文
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