基于PSO-GSA优化的井下加权质心人员定位算法

摘要

In a complex environment of underground localization,focusing on received signal strength indicator(RSSI) in underground personnel positioning accuracy is low and the problem of dynamic tracing parameters change.Therefore,using an improved gravitational search algorithm (GSA) for the weighted centroid localization that based on RSSI.Utilizing the log distance path loss model got the distance between the beacon nodes and unknown nodes,and then through the weighted centroid localization algorithm performed the unknown node positioning.Finally,the improved GSA-PSO optimized the preliminary location results and parameters.Experimental results show the proposed method can improve both the positioning accuracy effectively and the adaptive ability of changeful environment.%针对煤矿复杂环境中,接收信号强度指示的人员定位精度较低,难以动态跟踪参数变化的问题,提出一种利用改进的引力搜索算法应用于加权质心定位中进行井下人员定位的方法.先采用对数距离路径损耗模型得到信标节点到未知节点的距离,然后通过加权质心定位算法对未知节点进行定位,最后利用粒子群万有引力混合算法对相关参数和估计的位置信息进行优化.实验结果表明,该方法能够增强对环境变化的自适应能力,更有效地提高了定位精度.