RBF Neural Network Based Prediction for Target Tracking in Chain-type Wireless Sensor Networks

摘要：

A target tracking is an important embranchment of WSN, which can assure the position of a moving target realtime. This paper works on the prediction problem of target tracking of chain-type wireless sensor networks. We choose RBF neural network as the basis of the tracking prediction model. Based on analysis of chain-type tracking characters and RBF neural network based tracking prediction model, we build a target tracking prediction algorithm. The target tracking prediction problems of moving objects in coal tunnel are simulated and the simulation results show that a moving target can be traced real-time and accurately using the presented tracking prediction model and algorithm.

关键词： WSNs RBF Neural Network Prediction Target Tracking

作者: Chen Guangzhu Zhou Lijuan Zhu Zhencai Zhou Gongbo

作者单位: School of Mechanical & Electrical Engineering China University of Mining & Technology Xuzhou, Jiangsu, China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 635-639

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）