海洋多波束测深异常数据自动化检测和处理方法研究进展

Research progress on automated detection and cleaning of abnormal ocean multibeam bathymetry data

  • 摘要: 针对海洋多波束测深异常数据的自动化检测和处理问题,综合国内外研究进展,本文根据针对的处理目标不同,将其分为3类:测深点数据域检测处理方法、单ping数据域检测处理方法及构建曲面模型域检测处理方法。通过对中值滤波、聚类算法、布料模拟法、CUBE算法、趋势面法和抗差估计法等方法的梳理,归纳总结出各种方法的处理过程、应用对象、应用准则、适用领域以及结果判断的不同之处,并通过列表的方式进行分类和对比分析,得到这三类方法处理时的侧重方向和适用的异常数据类型。分析了三类针对不同目标的自动化检测和处理方法的优势和不足,总结了以往各种方法在处理和实践中存在的问题,并在此基础上提出相应的建议。

     

    Abstract: Aiming at the automated detection and cleaning of abnormal ocean multibeam bathymetric data, and integrating the research progress at home and abroad, we classified the methods into three categories according to the different processing objectives: detection and processing in bathymetric point data domain, in single ping data domain, and in the domain of constructing surface model. By sorting out the median filtering, clustering algorithm, CSF algorithm, CUBE algorithm, trend surface method, and robust estimation method, we summarized the differences in the processing process, application targets, application criteria, application fields, and result judgment of the methods; classified and compared the three types of methods in a list; and obtained the direction of focus and the type of abnormal data applicable to the processing of the three types of methods. The advantages and shortcomings of the three types of the methods for different targets were analyzed, and the problems and the solutions in the processing and practice of the previous methods were reviewed.

     

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