计算机与现代化Issue(12)：1-10,10.DOI:10.3969/j.issn.1006-2475.2025.12.001
基于三维点云SVT算法的MIMO雷达测流方法
Flow Velocity Measurement Method Using MIMO Radar Based on 3D Point Cloud SVT Algorithm
摘要
Abstract
River surface velocity is a key parameter in hydrological monitoring,as it provides essential information for under-standing hydrological conditions,regulating water volume,and preventing flood disasters.Compared with traditional contact-based flow velocity measurement methods,radar-based flow velocity measurement technology boasts advantages such as non-contact measurement(which is not affected by water body conditions)and real-time monitoring capabilities.To improve the ac-curacy and real-time performance of river channel flow velocity measurement,this study adopts a MIMO radar flow measurement method based on the 3D point cloud SVT algorithm.Through processing steps including projection filtering,grid partition denois-ing,and scale correction applied to the point cloud across three dimensions—space,velocity,and time—this method reduces noise interference and data redundancy,enhances the accuracy and stability of flow velocity measurement,and further enables the intuitive presentation of multi-point flow velocity distribution on the river channel surface.The radar can be installed in a shore-based lateral manner,which lowers the requirements for the installation environment and realizes multi-point flow velocity measurement on the river channel surface.Experimental results show that in medium-to-high flow velocity scenarios(v≥0.5 m/s),the relative error is less than 5%;in low flow velocity scenarios(0.3 m/s≤v＜0.5 m/s),the absolute error is less than 5 cm/s.In summary,this method can effectively improve the accuracy and stability of river channel flow velocity measurement,providing technical support for hydrological monitoring.关键词
MIMO雷达/点云/流速/数据处理/栅格分区/去噪Key words
MIMO radar/point cloud/flow velocity/data processing/grid partitioning/denoising分类
信息技术与安全科学引用本文复制引用
李健,宋钰,张文鑫,于然..基于三维点云SVT算法的MIMO雷达测流方法[J].计算机与现代化,2025,(12):1-10,10.基金项目
国家自然科学基金青年基金资助项目(62406032) （62406032）
北京市自然科学基金资助项目(4242036) （4242036）
