Lv Xiaoyang, Wang Lei, Huang Dexiang, Wang Shengli
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China.
Key Laboratory of Ocean Geomatics, Ministry of Natural Resources, Qingdao 266590, China.
Sensors (Basel). 2023 Aug 28;23(17):7483. doi: 10.3390/s23177483.
The utilization of multibeam sonar systems has significantly facilitated the acquisition of underwater bathymetric data. However, efficiently processing vast amounts of multibeam point cloud data remains a challenge, particularly in terms of rejecting massive outliers. This paper proposes a novel solution by implementing a cone model filtering method for multibeam bathymetric point cloud data filtering. Initially, statistical analysis is employed to remove large-scale outliers from the raw point cloud data in order to enhance its resistance to variance for subsequent processing. Subsequently, virtual grids and voxel down-sampling are introduced to determine the angles and vertices of the model within each grid. Finally, the point cloud data was inverted, and the custom parameters were redefined to facilitate bi-directional data filtering. Experimental results demonstrate that compared to the commonly used filtering method the proposed method in this paper effectively removes outliers while minimizing excessive filtering, with minimal differences in standard deviations from human-computer interactive filtering. Furthermore, it yields a 3.57% improvement in accuracy compared to the Combined Uncertainty and Bathymetry Estimator method. These findings suggest that the newly proposed method is comparatively more effective and stable, exhibiting great potential for mitigating excessive filtering in areas with complex terrain.
多波束声纳系统的应用极大地促进了水下测深数据的采集。然而，高效处理大量多波束点云数据仍然是一项挑战，尤其是在剔除大量离群点方面。本文提出了一种新颖的解决方案，即对多波束测深点云数据实施圆锥模型滤波方法进行滤波。首先，采用统计分析从原始点云数据中去除大规模离群点，以增强其对方差的抗性以便后续处理。随后，引入虚拟网格和体素下采样来确定每个网格内模型的角度和顶点。最后，对点云数据进行反转，并重新定义自定义参数以实现双向数据滤波。实验结果表明，与常用滤波方法相比，本文提出的方法能有效去除离群点，同时将过度滤波降至最低，与人机交互滤波的标准差差异最小。此外，与联合不确定性和测深估计器方法相比，其精度提高了3.57%。这些结果表明，新提出的方法相对更有效且稳定，在缓解复杂地形区域的过度滤波方面具有巨大潜力。
