基于蜣螂算法优化的 DV-Hop 定位算法

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。

DV-Hop localization algorithm optimized based on dung beetle optimizer

A DV-Hop (distance vector-hop) localization algorithm based on dung beetle algorithm optimization was proposed for theproblem of significant localization error of traditional DV-Hop algorithm in wireless sensor networks. Firstly, the dual communicationradius was introduced to refine the number of hop nodes, then the average hop size of anchor nodes was calculated using the minimummean 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 forcoordinate calculation instead of the trilateral measurement method. The simulation results show that the proposed algorithm improves theaverage positioning error by 55. 69%, 59. 61% and 67. 59%, and the error variance by 52. 41%, 45. 58% and 36. 87% than theclassical DV-Hop algorithm, which has good positioning accuracy and better stability.