A Novel Classification Scheme of Moving Targets at Sea Based on Ward's and K-means Clustering
Yan Jiang, Bo Li, Hao Zhang, Quming Luo, Pengxin Zhou · Proceedings of the 2nd International Conference on Computer Science and Application Engineering · 2018
Based1 on the structure database technology, Ward's and K-means clustering, a classification and identification scheme is proposed for the monitoring data of the moving targets at sea. First, a structural database is built to store the monitored data. Secondly, by analyzing the movement rules of ships which derived from the automatic identification system(AIS), the identification features of the moving targets at sea are obtained and extracted them from the monitored data. And then, the Ward's clustering is used to classify the feature data. Finally, the K-means clustering is used to identify the existing formation ships. The simulation results show that the proposed scheme is applicable to classify and identify the moving targets at sea.