Research on Underwater Multi-clutter Data Association Based on Fuzzy Clustering

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	Research on Underwater Multi-clutter Data Association Based on Fuzzy Clustering
	Ding Y(丁一)1,2; Zhang Y(张瑶)2; Wu MY(吴梦妍)1,2
	2019
会议日期	November 22-24, 2019
会议地点	Hangzhou, China
关键词	data association fuzzy clustering target tracking Kalman filter
页码	5115-5119
英文摘要	In this paper, a multi-target tracking association algorithm based on fuzzy clustering is proposed to cope with the multi-clutter phenomenon and large measurement error in underwater environment. The algorithm obtains the membership degree of each measurement to the clustering center point by using the Fuzzy Clustering (FCM) algorithm, and then weights the associated measurement values as a weight coefficient. Finally, the Kalman filter algorithm is used to obtain the estimated value of the state, so that multiple targets can be tracked. Simulation results show that the traditional algorithm is easy to generate false alarms or even filter divergence in the multi-clutter environment. However, the algorithm proposed in this paper takes all the measured values falling within the tracking gate into account, which greatly improves the tracking accuracy and stability. So that our method can be applied to actual engineering projects.
产权排序	1
会议录	Proceedings - 2019 Chinese Automation Congress, CAC 2019
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-4094-0
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/26408]
专题	沈阳自动化研究所_海洋信息技术装备中心
通讯作者	Ding Y(丁一)
作者单位	1.University of Chinese Academy of Sciences, Beijing, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
推荐引用方式 GB/T 7714	Ding Y,Zhang Y,Wu MY. Research on Underwater Multi-clutter Data Association Based on Fuzzy Clustering[C]. 见:. Hangzhou, China. November 22-24, 2019.