Dynamic Nearest Neighborhood Collaboration Target Tracking for WSN

摘要：

Target tracking is one of the most important applications for wireless sensor networks. Generally, multi-sensors working collaboratively can achieve better performance but with high-energy consumption in target tracking. In this paper, a dynamically clustering algorithm, called nearest neighborhood collaboration, is proposed for collaborative target tracking in wireless sensor networks. It selects cluster head based on minimum distance between predicted target position and sensor nodes. Cluster head forms the cluster of tasking sensors in its neighborhood and fulfills estimation update, next state prediction, and executes information fusion based on central Kalman Filter. Simulation results show that, compared with existing sensor scheduling algorithm, the proposed multisensor scheduling scheme not only achieve superior tracking accuracy but also energy saving, it is also robust to the uncertainty of process noise.

关键词： wireless sensor network target tracking nearest neighborhood collaboration kalman filter

作者: Hui Long Zhihua Qu Xiaoping Fan Shaoqiang Liu Wenyan Tang

作者单位: School of Information Science and Engineering Central South University Department of Information Tec Department of Electrical Engineering and Computer Science University of Central Florida Orlando, U.S School of Information Science and Engineering Central South University Changsha, China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 180-184

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）