面向电力巡检的5G室内三维指纹定位算法

5G Indoor Three-dimensional Fingerprint Localization Algorithm for Power Inspection

针对目前电力巡检机器人在室内环境中存在的三维定位成本高、精度低的问题,文章利用5G信号特征和多信号分类(multiple signal classification,MUSIC)算法,提出面向电力巡检的5G室内三维指纹定位算法。首先构建三维信道模型,以降低多径干扰导致的定位信号参数偏差;其次提出多径定位信号优化算法,以克服随机噪声导致的定位信号相位偏移问题,以此降低定位决策的软硬件成本。仿真结果表明,本算法在三维室内定位精度和定位成本方面实现了较好的性能与平衡。

Aiming at the problem of high cost and low precision of three-dimensional localization of power inspection robots in indoor environment,this paper proposes a 5G indoor three-dimensional fingerprint localization algorithm for power inspection with 5G signal characteristics and multi-signal classification algorithm.Firstly,a three-dimensional channel model is constructed to reduce the deviation of positioning signal parameters caused by multi-path interference.Secondly,the multi-path positioning signal optimization algorithm is proposed to overcome the phase deviation caused by random noise,so as to reduce the hardware and software cost of positioning decision.Simulation results show that the proposed algorithm achieves good performance and balance in two aspects of three-dimensional indoor positioning accuracy and positioning cost.