无人机机载5G一体化基站后台数据集成方法

Background data integration method of UAV airborne 5G integratedbase station

传统无人机机载5G基站后台数据集成方法的数据集成性能较差,对此文中提出新的无人机机载5G一体化基站后台数据集成方法。采用无线传感网络和RFID标签射频检测法分区调度大数据,提取基站后台数据的关联规则性特征。利用特征模糊层次性融合方法实现后台数据关联性挖掘。通过机器学习方法实现对后台数据属性的聚类处理,结合子空间压缩方法实现对基站后台数据的集成。仿真实验结果表明,采用该方法集成基站后台数据的性能较好,数据特征提取精度较高,后台数据分类管理能力较强。

The data integration performance of the traditional background data integration method of 5G base station on UAVs is poor.Thus,a new method of background data integration for 5G integrated base station of UAV is proposed.The wireless sensor network and RFID tag RF detection method are used to partitioned schedule the big data,and extract the association regularity characteristics of the background data of the base station.The correlation mining of background data is realized by using feature fuzzy hierarchical fusion method.The machine learning method is used to cluster the attributes of the background data,and the subspace compression method is used to integrate the background data of the base station.The simulation results show that this method has advantages,including good performance in integrating base station background data,high precision in data feature extraction,and strong ability in classification and management of background data.