摘要
为降低无线传感器网络中的能量开销,减少存储和网络资源,采用了一种新的信息融合机制。根据目标的当前地理位置,将无线传感器网络中的节点动态分簇,建立分布式的跟踪机制。利用一种基于信息矩阵加权的卡尔曼算法在该机制下进行目标跟踪,与无分簇机制下的信息矩阵融合算法进行性能比较,仿真实验结果表明该方法具有较高的有效性和可靠性。同时,在网络存在丢包情况下,基于Grubbs准则进行改进,能有效地提高精度。
In this paper, a new information fusion mechanism is proposed to reduce the requirement for energy, the storage and network resources in wireless sensor network (WSN). According to the current position of the target, these nodes are dynamically clustered such that a distributed tracking mechanism is established. And then, the Kalman filter algorithm based on information matrix is proposed to attain the objective tracking, which is also compared with the same algorithm without clustering. The simulation results show that the proposed algorithm is effective and reliable. Moreover, for the case that there may happen packed-drop in WSN, Gruhh.~ erltoria ff~~:..^l.. : ,
出处
《华东理工大学学报(自然科学版)》
CAS
CSCD
北大核心
2012年第3期356-359,390,共5页
Journal of East China University of Science and Technology
关键词
无线传感器网络
分布式卡尔曼滤波
信息融合
动态分簇
wireless sensor network
distributed Kalman filter
information fusion
dynamic clusters