基于跳数量化的无线传感器网络节点定位算法

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 multidimensional 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 accurate in case of the enough anchor nodes.