【摘要】 针对三维(3D)-DV-Hop定位算法未知节点从最近的锚节点获取平均跳距估算距离时定位精度低的问题，提出了一种新的基于WBOA的3D-DV-Hop算法。首先，该算法去除了网络中无法通信和无法定位的节点；然后添加了修正因子，修正平均跳距。接着创建一个用于优化的蝴蝶初始种群，构建目标函数。采用自适应权重来平衡全局搜索与局部搜索的能力，使得算法不易陷入局部最优，加快了算法的收敛精度；最终求得全局最优平均跳距。仿真结果表明：尽管算法的平均运行时间略有增加，但算法的定位精度得到了有效提高。更多还原

【Abstract】 Aiming at the problem of low positioning precision when the unknown node obtains average hop distance from the nearest anchor node in the 3D-DV-Hop localization algorithm, a new 3D-DV-Hop algorithm based on WBOA is proposed.Firstly, the algorithm removes the nodes that cannot communicate and cannot be located in the network.Then, a correction factor is added to correct the average hop distance.Next, an initial butterfly population is created for optimization, and objective function is constructed, and adaptive weights are used to balance the ability of global search and local search, which makes the algorithm not easy to fall into local optimal, speeds up the convergence precision of the algorithm.Finally, the global optimal average hop distance is obtained.The simulation results show that although the average running time of the algorithm is slightly increased, the localization precision of the algorithm is effectively improved.更多还原