摘要
雷达辐射源信号分选是电子情报侦察的关键环节,其中未知雷达的信号分选一直是分选中的难题。针对传统K-Means聚类算法对初始聚类中心敏感、需要事先确定初始聚类数目的缺点,将数据场算法引入到雷达信号分选,并将其与K-Means聚类算法相结合,提出了一种融合算法,该算法不需要雷达信号的先验知识,适用于处理未知雷达信号。通过仿真实验验证所提出的融合算法分选准确率较高,为雷达信号分选提供了新的思路。
Radar signal sorting is a great important part of electronic intelligence reconnaissance sys- tems. The unknown radar signal sorting is a hard problem. K-Means algorithm has several limitations：sensi- tive to initial center of clustering and choosing the number Of initial class centre. In this paper, the data field algorithm is introduced into the radar signal sorting, and is combined with K-Means. This method is a new way for sorting, and does not need prior knowledge of the radar signal. It is suitable for sorting the unknown radar signal. The simulation proves .that the method has good sorting result and provides a new way of radar signal sorting.
出处
《雷达科学与技术》
北大核心
2016年第5期517-520,525,共5页
Radar Science and Technology
作者简介
赵贵喜 男，1983年9月出生于哈尔滨，硕士，空军93199部队理论训练系讲师，主要从事电子对抗方面研究。E-mail：sydney99_1983@163．com
