Distributed Variational Filtering for Simultaneous Sensor Localization and Target Tracking in Wireless Sensor Networks

	Distributed Variational Filtering for Simultaneous Sensor Localization and Target Tracking in Wireless Sensor Networks
	Teng, Jing; Snoussi, Hichem; Richard, Cedric; Zhou, Rong
刊名	IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
	2012
卷号	61 期号:5 页码:2305-2318
关键词	Bayesian method filtering algorithm simultaneous localization and tracking wireless sensor networks
ISSN号	0018-9545
通讯作者	Teng, J (reprint author), N China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China.
中文摘要	The tracking of a moving target in a wireless sensor network (WSN) requires exact knowledge of sensor positions. However, precise information about sensor locations is not always available. Given the observation that a series of measurements are generated in the sensors when the target moves through the network field, we propose an algorithm that exploits these measurements to simultaneously localize the detecting sensors and track the target (SLAT). The main difficulties that are encountered in this problem are the ambiguity of sensor locations, the unrestricted target moving manner, and the extremely constrained resources in WSNs. Therefore, a general state evolution model is employed to describe the dynamical system with neither prior knowledge of the target moving manner nor precise location information of the sensors. The joint posterior distribution of the parameters of interest is updated online by incorporating the incomplete and inaccurate measurements between the target and each of the sensors into a Bayesian filtering framework. A variational approach is adopted in the framework to approximate the filtering distribution, thus minimizing the intercluster communication and the error propagation. By executing the algorithm on a fully distributed cluster scheme, energy and bandwidth consumption in the network are dramatically reduced, compared with a centralized approach. Experiments on an SLAT problem validate the effectiveness of the proposed algorithm in terms of tracking accuracy, localization precision, energy consumption, and execution time.
英文摘要	The tracking of a moving target in a wireless sensor network (WSN) requires exact knowledge of sensor positions. However, precise information about sensor locations is not always available. Given the observation that a series of measurements are generated in the sensors when the target moves through the network field, we propose an algorithm that exploits these measurements to simultaneously localize the detecting sensors and track the target (SLAT). The main difficulties that are encountered in this problem are the ambiguity of sensor locations, the unrestricted target moving manner, and the extremely constrained resources in WSNs. Therefore, a general state evolution model is employed to describe the dynamical system with neither prior knowledge of the target moving manner nor precise location information of the sensors. The joint posterior distribution of the parameters of interest is updated online by incorporating the incomplete and inaccurate measurements between the target and each of the sensors into a Bayesian filtering framework. A variational approach is adopted in the framework to approximate the filtering distribution, thus minimizing the intercluster communication and the error propagation. By executing the algorithm on a fully distributed cluster scheme, energy and bandwidth consumption in the network are dramatically reduced, compared with a centralized approach. Experiments on an SLAT problem validate the effectiveness of the proposed algorithm in terms of tracking accuracy, localization precision, energy consumption, and execution time.
学科主题	空间技术
收录类别	SCI ; EI
资助信息	Fundamental Research Funds for the Central Universities; China Scholarship Council-French University of Technology Applied Science Group Program; CapSec Program; Contrat de Projets Etat-Region Champagne-Ardenne
语种	英语
公开日期	2014-12-15
内容类型	期刊论文
源URL	[http://ir.nssc.ac.cn/handle/122/3331]
专题	国家空间科学中心_其他部室
推荐引用方式 GB/T 7714	Teng, Jing,Snoussi, Hichem,Richard, Cedric,et al. Distributed Variational Filtering for Simultaneous Sensor Localization and Target Tracking in Wireless Sensor Networks[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2012,61(5):2305-2318.
APA	Teng, Jing,Snoussi, Hichem,Richard, Cedric,&Zhou, Rong.(2012).Distributed Variational Filtering for Simultaneous Sensor Localization and Target Tracking in Wireless Sensor Networks.IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,61(5),2305-2318.
MLA	Teng, Jing,et al."Distributed Variational Filtering for Simultaneous Sensor Localization and Target Tracking in Wireless Sensor Networks".IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 61.5(2012):2305-2318.