基于多波束测深技术的水下地形点云数据优化方法  

Optimization of Underwater Terrain Point Cloud Data Based on Multi-beam Sounding Technology

作　　者：杨莉 杨亮 姬焕 李嘉豪 郑广豪 张宏洋 王祥宇 徐良杰 YANG Li;YANG Liang;JI Huan;LI Jiahao;ZHENG Changhao;ZHANG Hongyang;WANG Xiangyu;XU Liangjie(Huaihe River Commission Construction Engineering Administration Bureau,Bengbu 233040,Anhui,China;Henan Provincial Water Conservancy First Engineering Bureau,Zhengzhou 450016,Henan,China;School of Water Conservancy,North China University of Water Resources and Electric Power,Zhengzhou 450045,Henan,China)

机构地区：[1]淮河水利委员会治淮工程建设管理局,安徽蚌埠233040 [2]河南省水利第一工程局集团有限公司,河南郑州450016 [3]华北水利水电大学水利学院,河南郑州450045

出　　处：《水力发电》2025年第5期25-29,124,共6页Water Power

基　　金：国家自然科学基金资助项目(52079051);河南省高校重点基金项目(22A570004,23A570006)。

摘　　要：基于多波束测深技术测量的河道水下地形图点云数据存在数据异常的问题,采用基于趋势面和抗差M估计滤波法优化处理了点云数据异常值,结合基于边界范围的抽稀算法保留的50%、25%和16%点云数据量,对比分析了滤波优化方法和抽稀优化处理的数据保留率。结果表明,基于抗差M估计的测深异常值滤波法去噪效果更优,在保证数据特征完整性的前提下,具有25%数据保留率的抽稀优化成果可最大限度的降低数据密度。The point cloud data of underwater topographic map of river channel measured by multi-beam sounding technology has the problem of data anomalies.The outliers of point cloud data are optimized by using trend surface and robust M estimation filtering method,and the 50%,25%and 16%point cloud data retained by the boundary range-based extraction algorithm are combined.The data retention rates of filter optimization and extraction optimization are compared and analyzed.The results show that the outlier filtering method based on the robust M estimation has better denoising effect,and the extraction optimization results with 25%data retention rate can reduce the data density to the maximum extent while ensuring the integrity of data features.

关 键 词：多波束测深技术 河道水下地形图 数据滤波 数据抽稀 

分 类 号：TV698.1[水利工程—水利水电工程]