电讯技术2018，Vol.58Issue(3)：295-299,5.DOI:10.3969/j.issn.1001-893x.2018.03.010
应用K-means聚类的分布式多传感器航迹关联算法
A Distributed Multi-sensor Track Association Algorithm Based on K-means Clustering
摘要
Abstract
Aiming at the characteristics of distributed multi-sensor track association,a track association al-gorithm based on K-means clustering is adopted.The local tracks from the sensors are associated with the systems tracks and the system tracks are selected as the initial clustering centers to avoid the defect of the K-means algorithm itself relying on the initial values.The sum of the Euclidean distance and the 1-Norm of state vector between tracks are proposed as the similarity measure.The distance threshold is set to reduce the impact of extreme data on clustering results.And the polysemy processing is increased. Monte Carlo simulation results show that the algorithm can obtain a higher average correlation rate at a lower cost in the case of target-intensive.At the same time,the algorithm overcomes the local optimal characteristics of the nearest neighbor method and the limitation that the correlation accuracy is highly dependent on the feature threshold.关键词
航迹关联/聚类分析/K-means聚类/向量范数/正确关联率Key words
track association/clustering analysis/K-means clustering/vector norm/correct association rate分类
信息技术与安全科学引用本文复制引用
李素,王运锋..应用K-means聚类的分布式多传感器航迹关联算法[J].电讯技术,2018,58(3):295-299,5.基金项目
国家自然科学基金资助项目(91338107) （91338107）
四川省科技厅软科学研究项目(2016ZR0087) （2016ZR0087）
