面向变电站智能巡检5G大规模MIMO融合定位方法

5G Large-scale Antenna Fusion Positioning Method for Intelligent Inspection of New Substations

随着新型电力系统建设的不断推进,电力终端和采集类设备的大范围接入,对变电站的巡检工作开展产生了巨大的挑战,实施难度大、定位精度无法保障。为此,设计了一种基于5G的大规模MIMO的融合定位算法,首先,利用静止波束成形方法拟合粗定位体系结构,确定直接定位方法的搜索区域。然后,推导四阶累积量拟合近场模型,并计算与远场基站关联的自适应权值。最后,构建了一种基于远场与近场联合直接定位的位置感知模型,将直接定位方法有效应用于粗定位区域,解决了依靠传统到达角定位方式密集小区误差大的问题。仿真结果表明,在相同的实验环境下基于5G基站的远近场景大规模MIMO融合定位技术具有更高的定位精度和稳定性,能够有效保证站内巡检定位的准确性。

With the continuous advancement of the construction of new power systems,the large-scale access of power terminals and acquisition equipment has created huge challenges for the inspection work of substations,and the implementation is difficult and the positioning accuracy cannot be guaranteed.In this regard,this paper designs a fusion positioning algorithm based on 5G massive MIMO.First,the static beamforming method is used to fit the coarse positioning architecture to determine the search area of the direct positioning method;then,the fourth-order cumulant is derived to fit the approximate field model and computes adaptive weights associated with far-field base stations.Finally,a location-aware model based on FNDP is constructed,and the direct positioning method is effectively applied to the coarse positioning area,which solves the problem of large errors in dense cells relying on the traditional angle of arrival positioning method.The simulation results show that under the same experimental environment,the massive MIMO fusion positioning technology based on the 5G base station in the far and near scenarios proposed in this paper has higher positioning accuracy and stability,and can effectively ensure the accuracy of the inspection and positioning in the station.