摘要
针对传统的K-Means聚类雷达信号分选算法对初始聚类中心敏感和易陷入局部最优解的缺点,将改进的人工蜂群算法和K-Means迭代相结合,提出了一种混合聚类雷达信号分选算法,使算法对初始聚类中心的依赖性和陷入局部最优解的可能性降低,提高了算法的稳定性。通过仿真实验证明该算法分选准确率高,为雷达信号分选提供了新的思路。
Since the K-Means clustering method is sensitive to initial clustering centers and easy to be trapped by local optimum,the basic Artificial Bee Colony（ABC）clustering algorithm is im-proved which is combined with K-Means. The new algorithm reduces the dependence on the ini-tial clusteringcenters and the probability to be trapped by local optimum,thus the stability of the algorithm is improved. The simulation shows that the method has a good sorting result, providing a new way of radar signal sorting.
出处
《电子信息对抗技术》
2015年第4期4-7,共4页
Electronic Information Warfare Technology
关键词
雷达信号分选
人工蜂群
聚类
radar signal sorting
artificial bee colony algorithm
clustering
