| 潘志远,卜凡亮.基于蜣螂算法优化的 DV-Hop 定位算法[J].电子测量与仪器学报,2023,37(7):33-41 |
| 基于蜣螂算法优化的 DV-Hop 定位算法 |
| DV-Hop localization algorithm optimized based on dung beetle optimizer |
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| DOI： |
| 中文关键词: 无线传感器网络 DV-Hop 定位算法 蜣螂优化算法 双通信半径 节点定位 |
| 英文关键词:wireless sensor network DV-Hop localization algorithm dung beetle optimization algorithm dual communication radius node localization |
| 基金项目:中国人民公安大学安全防范工程双一流专项(2023SYL08)项目资助 |
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| 中文摘要: |
| 针对无线传感器网络中传统 DV-Hop( distance vector-hop) 算法定位误差大的问题,提出了一种基于蜣螂算法优化的
DV-Hop 定位算法。 首先使用双通信半径的方式细化节点间跳数,并使用最小均方误差准则计算锚节点的平均跳距,将改进后
的平均跳距的平均值当做每个未知节点的平均跳距,最后引入权重因子优化适应度函数,使用蜣螂优化算法代替三边测量法进
行坐标计算。 仿真结果表明,所提算法比经典 DV-Hop 算法平均定位误差提升了 55. 69%、59. 61%和 67. 59%,误差方差提升了
52. 41%、45. 58%和 36. 87%,具有良好的定位精度和较好的稳定性。 |
| 英文摘要: |
| A DV-Hop (distance vector-hop) localization algorithm based on dung beetle algorithm optimization was proposed for the
problem of significant localization error of traditional DV-Hop algorithm in wireless sensor networks. Firstly, the dual communication
radius was introduced to refine the number of hop nodes, then the average hop size of anchor nodes was calculated using the minimum
mean square error criterion, and the mean of the improved average hop size was taken as the average hop size of each unknown node,
finally, a weighting factor was introduced to optimize the fitness function, and the dung beetle optimization algorithm was used for
coordinate calculation instead of the trilateral measurement method. The simulation results show that the proposed algorithm improves the
average positioning error by 55. 69%, 59. 61% and 67. 59%, and the error variance by 52. 41%, 45. 58% and 36. 87% than the
classical DV-Hop algorithm, which has good positioning accuracy and better stability. |
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