| 一种基于跳距修正的物联网中节点定位算法 |
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| 引用本文： | 唐一韬,邓河.一种基于跳距修正的物联网中节点定位算法[J].全球定位系统,2022,47(4):50. |
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| 作者姓名： | 唐一韬 邓河 |
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| 作者单位： | 长沙民政职业技术学院 通识教育中心, 长沙 410004 |
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| 基金项目： | 湖南省教育厅科研项目(14C0064)；湖南省教育厅科研项目(15C0081) |
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| 摘 要： | 针对传统的DV-Hop算法存在较大定位误差的问题，提出基于狮群优化算法的节点定位 (NLLSO) 算法. NLLSO算法从估计最小跳数、修正平均跳距误差和定位算法三方面进行改进，进而降低定位误差. NLLSO算法用不同通信半径传递Beacon包，进而提高估计最小跳数值的精度. 同时，通过引入权值参数修正平均跳距的估计值. 最后，通过狮群优化算法(LSO)估计未知节点位置. 仿真结果表明:NLLSO算法的定位精度高于传统的DV-Hop算法.
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| 关 键 词： | 无线传感网络(WSN) 定位算法 多通信半径 平均跳距 狮群优化 (LSO) 算法 |
| 收稿时间： | 2022-03-22 |
A hop correction-based node localization algorithm in things of network |
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| Institution: | ChangSha Social Work College, Changsha 410004, China |
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| Abstract: | In view of the large localization error in the traditional DV-Hop algorithm in wireless sensor network, node localization based on lion swarm optimization (NLLSO) algorithm is proposed in this paper. In NLLSO algorithm, the minimum-hop estimation, average hop error correction and position process are optimized to reduce the localization error. Beacon packet is transmitted in multiple communication radii way, and accuracy of estimating minimum-hop count is improved. In addition, the weight is introduced to correct the average hop. Finally, lion swarm optimization algorithm is used to solve the position of the node. The simulation results show that positioning accuracy of NLLSO algorithm is significantly improved compared with traditional DV-Hop algorithm. |
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