摘要
为提高无线传感器网络节点定位精度,提出一种基于跳数量化的定位(MDS-HE)算法。将网络中节点的一跳邻居节点集合分割成3个不相交的子集,根据跳环分割的相交区域面积来估算节点间的距离,从而将整数跳数转换成实数跳数,转换后节点间实数跳数更能准确地表示节点间的距离;将实数跳数矩阵应用于多维定标(MDS)算法中,并且引入扩展卡尔曼滤波算法对节点坐标进行准确定位。在节点随机布撒的网络中,对提出的算法进行了仿真和实验分析。仿真和实验结果表明:在不同节点数量情况下,MDS-HE算法的性能优于距离向量定位算法和经典MDS算法,而且在锚节点足够多的条件下,MDS-HE算法定位更加准确。
A novel algorithm based on hop-count quantization and extended Kalman filter based on multi- dimensional scaling (MDS-HE) is proposed to improve the localization accuracy of nodes in wireless sensor networks. The integer hop-count can be transformed into a real number hop-count by partitioning a node's one-hop neighbor set into three disjoint subsets and estimating the distance between nodes by the areas of the intersection regions of hop ring segmentation. The transformed real number hop-count is a more accurate representation of distance between nodes. The real number hop-count matrix is applied to the multidimensional scaling (MDS) method, and the extended Kalman filter is applied to refine accurately the coordinates of nodes. The localization performance of MDS-HE algorithm is simulated and analyzed in WSNs which is composed of nodes deploying randomly over a region. Simulated and experimental results show that the performance of the MDS-HE algorithm outperforms the DV-Hop method and the classical MDS method in the case of different number of nodes. The MDS-HE algorithm is exceedingly accu- rate in case of the enough anchor nodes.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2017年第5期932-939,共8页
Acta Armamentarii
基金
国家自然科学基金项目(61573061)
关键词
信息处理技术
无线传感器网络
定位
多维定标算法
跳数量化
扩展卡尔曼滤波
information processing technology
wireless sensor network
localization
multidimensional scaling
hop-count quantization
extended Kalman filter