摘要
节点定位在无线传感器网络中应用广泛,是重要的支撑技术之一,目前很多算法是通过由全球卫星定位系统提供位置的信标节点来确定其他多数节点的位置,这样就出现在支撑数量较大的节点部署情况下的定位较为困难。信标节点由于人为或环境因素,容易出现位置漂移,而且当在室内环境时,信标节点本身运作就会发生困难。提出了一种角度和距离结合的无信标节点WSN定位算法。在无信标结点存在的情况下,利用树结构分类及合并的思想,在测量角度以及距离后,调整节点的方位与坐标,计算得到节点在系统中的坐标。仿真结果表明,当节点在随机分布时,所提出算法的定位精度比聚类SPA算法有明显的提高。
Node localization technology is one of the important support technology in wireless sensor network application,many current algorithm is through the global positioning system to provide the location of beacon node to further determine the location of the most other nodes,so under the condition of supporting large number of nodes deployed,location is relatively difficult.Due to human or environmental factors,beacon nodes are to have position drifts,and under indoor environment,difficulty of beacon node operation will happen.Therefore,a localization algorithm of WSN without beacon node combining angle and distance is proposed.In the case that no beacon node exists,the idea of tree structure classification and merge is used,the angle measurement and distance measurement are combined,and the node’s orientation and coordinate in synchronization are gradually adjusted,so as to calculate the coordinates of all nodes in the regional coordinate system.Finally,the simulation results show that the proposed algorithm is more precise than the clustering SPA algorithm in the case of random distribution of nodes.
作者
张拓
蒋健
姚海峰
钱升港
毛科技
何文秀
赵永标
ZHANG Tuo;JIANG Jian;YAO Haifeng;QIAN Shenggang;MAO Keji;HE Wenxiu;ZHAO Yongbiao(College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou Zhejiang 310023,China;Zhejiang Information Security Standardization Technical Committee,Hangzhou Zhejiang 310000,China;Yuecheng Fire and Resure Department,Shaoxing Zhejiang 312000,China;Zhijiang College,Zhejiang University of Technology,Shaoxing Zhejiang 312030,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2023年第10期1657-1662,共6页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(62072410)
浙江省基础公益研究计划项目(LGG22F020014,LGF21F020015)。
关键词
WSN
节点定位
无信标节点
角度和距离
树结构
WSN
node localization
beaconless node
angle and distance
tree structure
