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作 者:苗凯 苟平章 MIAO Kai;GOU Pingzhang(College of Computer Science and Engineering,Northwest Normal University,Lanzhou 730073,China)
机构地区:[1]西北师范大学计算机科学与工程学院,兰州730070
出 处:《电讯技术》2025年第2期322-328,共7页Telecommunication Engineering
基 金:国家自然科学基金资助项目(71961028,62261048)。
摘 要:为解决三维DV-Hop计算平均每跳距离和确定待定位节点时存在的较大误差问题,提出了一种改进的三维DV-Hop定位算法(3D-ISDVHop)。首先,引入理想跳数,重新定义修正因子,优化锚节点的原始跳数,减少跳数计算的累计误差;其次,通过最大路径搜索算法获取一条待定位节点到锚节点之间的最相似锚节点对的路径,修正该路径的平均跳距,得到待定位节点到目标锚节点的平均跳距;最后,利用非线性周期调整机制和精英协作策略改进沙猫群优化算法,通过函数最小化求解待定位节点坐标。仿真实验结果表明,在相同网络环境下,3D-ISDVHop表现出更优的性能,对比3D-DVHop、3D-SBDVHop和ILSOA-DVHop平均定位误差率分别降低约36.8%、5.6%、2.3%。To solve the problem of large errors in 3D DV-Hop in calculating the average distance per hop and determining the nodes to be located,a 3D DV-Hop localization algorithm based on distance correction and improved sand cat swarm optimization(3D-ISDVHop)is proposed.Firstly,the ideal hop count is introduced to redefine the correction factor to optimize the original hop count of the anchor node and reduce the cumulative error in the hop count calculation.Secondly,a path of the most similar anchor node pair between the to-be-located node and the anchor node is obtained by the maximum path search algorithm,and the average hopping distance of this path is corrected to obtain the average hopping distance from the to-be-located node to the target anchor node.Finally,the sand cat swarm optimization algorithm is improved by using a nonlinear cycle adjustment mechanism and an elite collaboration strategy to solve the coordinates of the nodes to be located by function minimization.The simulation experiment results show that 3D-ISDVHop exhibits better performance under the same network environment,and the average positioning error rate is reduced by about 36.8%,5.6%,and 2.3%compared with 3D-DVHop,3D-SBDVHop,and ILSOA-DVHop,respectively.
关 键 词:无线传感器网络(WSN) 3D-DVHop算法 跳距修正 相似路径 沙猫群优化算法
分 类 号:TP212.9[自动化与计算机技术—检测技术与自动化装置] TN929.5[自动化与计算机技术—控制科学与工程]
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