井下人员定位对于煤矿的安全管理和应急救援都非常重要,由于井下环境复杂,而质心定位算法受环境影响较小,因此在无线传感网络的节点定位中广泛应用。但传统质心算法精度较差,针对这种情况提出了一种改进质心定位算法,采用遗传算法对权值进行优化。仿真结果表明,经过遗传算法优化后,定位精度优于传统的质心算法。 Downhole personnel positioning is very important for the safety management and emergency rescue of coal mines. Due to the complex underground environment and the centroid location algorithm being less affected by the environment, it is widely used in the location of nodes in wireless sensor networks. However, the accuracy of the traditional centroid algorithm is poor. In view of this situation, an improved centroid localization algorithm is proposed, and the genetic algorithm is used to optimize the weights. Simulation results show that, after genetic algorithm optimization, the positioning accuracy is better than the traditional centroid algorithm.