ty -jour a2 -prieto，javier au -cui，huanqing au -zhao，jhao，junyi au -zhou，chuanai au -Zhang -na py -na py -20222 da -20222/29 ti -ti -dimization ti -dimization ti ti -dimization ti -dimization for两个移动锚点辅助的无线传感器网络使用改进的灰狼优化器SP -6292629 VL -2022 AB-本地化对无线传感器网络至关重要。在最近提出的本地化算法中，移动锚定辅助定位（MAL）算法似乎很有希望。使用单个移动锚的Mal算法的能源消耗较低，但本地化误差很高。相反，具有三个或更多移动锚的MAL算法具有较小的本地化错误，但能耗高。通过平衡能源消耗和本地化精度，我们的研究开发了一种由两个移动锚固辅助的本地化算法。移动锚沿双锚扫描（DASCAN）路径横穿网络，该路径将部署区域分为网格，并要求两个移动锚以锯齿形模式穿越不同的水平线。传感器节点使用多触及策略灰狼优化（MDS-GWO）算法来估计其位置，该算法通过引入非线性减轻的重量，随机的灰狼和镜子灰狼的随机扰动来改善优化。使用MATLAB，DASCAN与GTURN，GSCAN，PP-MMAN，H-Curves，M-Curves和Scan路径进行了比较。将MDS-GWO的本地化误差与三级，PSO，WOA和GWO进行了比较。 The impacts of radio irregularity, radio radius, and fading effect on MDS-GWO with different paths were also analyzed. The simulation results showed that the energy consumption of DASCAN was, on average, 30.1% less than GSCAN, GTURN, and PP-MMAN, but they had almost the same localization accuracy. The energy consumption of DASCAN was an average of 18.67% more than M-Curves, H-Curves, and SCAN, but the localization error of DASCAN was average of 32.3% less than SCAN, H-Curves, and M-Curves. The localization error of MDS-GWO was average of 25.5% less than trilateration, PSO, WOA, and GWO. Moreover, the performance of the proposed algorithm was less affected by different setups than the compared methods. SN - 1530-8669 UR - https://doi.org/10.1155/2022/6292629 DO - 10.1155/2022/6292629 JF - Wireless Communications and Mobile Computing PB - Hindawi KW - ER -