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Yonggui LIU,Bugong XU,Linfang FENG.[en_title][J].Control Theory and Technology,2011,9(1):058~065.[Copy]
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YongguiLIU,BugongXU,LinfangFENG
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Received:October 21, 2010Revised:October 21, 2010
基金项目:This work was supported by the NSFC-Guangdong Joint Foundation Key Project (No. U0735003), the Oversea Cooperation Foundation (No.60828006), the Fundamental Research Funds for the Central Universities (No. 2009ZM0076), the Specialized Research Funds for the Doctoral Program of Higher Education of China (No. 20100172120028), and the Scientific Research Funds for the Returned Overseas Chinese Scholars, State Education Ministry.
Energy-balanced multiple-sensor collaborative scheduling for maneuvering target tracking in wireless sensor networks
Yonggui LIU,Bugong XU,Linfang FENG
(College of Automation Science and Engineering, South China University of Technology)
Abstract:
An energy-balanced multiple-sensor collaborative scheduling is proposed for maneuvering target tracking in wireless sensor networks (WSNs). According to the position of the maneuvering target, some sensor nodes in WSNs are awakened to form a sensor cluster for target tracking collaboratively. In the cluster, the cluster head node is selected to implement tracking task with changed sampling interval. The distributed interactive multiple model (IMM) filter is employed to estimate the target state. The estimation accuracy is improved by collaboration and measurement information fusion of the tasking nodes. The balanced distribution model of energy in WSNs is constructed to prolong the lifetime of the whole network. In addition, the communication energy and computation resource are saved by adaptively changed sampling intervals, and the real-time performance is satisfactory. The simulation results show that the estimation accuracy of the proposed scheme is improved compared with the nearest sensor scheduling scheme (NSSS) and adaptive sensor scheduling scheme (ASSS). Under satisfactory estimation accuracy, it has better performance in saving energy and energy balance than the dynamic collaborative scheduling scheme (DCSS).
Key words:  IMM filter  Multiple-sensor collaborative scheduling  Target tracking  WSNs  Energy balance