基于跳距修正与狮群优化的WSNs三维定位算法  

A three-dimensional positioning algorithm based on hop correction and lion swarm optimization in WSNs

作　　者：苟平章 刘学治 孙梦源 何博 GOU Ping-zhang;LIU Xue-zhi;SUN Meng-yuan;HE Bo(College of Computer Science and Engineering,Northwest Normal University,Lanzhou 730070,China)

机构地区：[1]西北师范大学计算机科学与工程学院,甘肃兰州730070

出　　处：《计算机工程与科学》2021年第8期1405-1412,共8页Computer Engineering & Science

基　　金：国家自然科学基金(61261015,61561043);全国高等院校计算机教育研究会教育教学研究项目(2019-AFCEC-079);国家级大学生创新创业训练计划(201910736022)。

摘　　要：针对DV-Hop在三维空间中存在定位误差,为提高节点定位精度,提出一种基于跳距修正和狮群优化的WSNs三维定位算法(HCLSO-3D)。首先,通过多通信半径传播,对节点跳数进行精确划分,得到优化跳数值。其次,使用相似路径搜索算法获取与待定位节点到相应锚节点之间最相似的锚节点对的路径,对此路径平均跳距值进行修正,得到待定位节点到目标锚节点的平均跳距。最后,利用狮群算法优化求解待定位节点坐标位置。仿真结果表明,在同样的网络环境下,HCLSO-3D算法与3D-DVHop定位算法和文献[16]定位算法相比,定位精度明显提高。To reduce the positioning error of DV-Hop in three-dimensional space and improve the positioning accuracy of nodes,a three-dimensional positioning algorithm based on hop correction and lion swarm optimization in wireless sensor networks(WSNs)is proposed(HCLSO-3D).Firstly,through the propagation of multiple communication radii,the node hops are accurately divided to obtain the optimized hop value.Secondly,the similar path search algorithm is used to obtain the path of the most similar anchor node pair between the to-be-determined location node and the corresponding anchor node,and the average hop distance of this path is corrected to obtain the average hop distance from the to-be-determined location node to the target anchor node.Finally,the lion swarm optimization algorithm is used to solve the coordinates of the to-be-determined node.The simulation results show that,compared with the 3D-DVHop algorithm and the algorithm in reference[16],HCLSO-3D significantly improves the positioning accuracy in the same network environment.

关 键 词：无线传感器网络 三维节点定位 多通信半径 跳距修正 狮群优化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]