Acta Geodaetica et Cartographica Sinica >

2017 , Vol. 46 >Issue 5: 658 - 665

DOI: https://doi.org/10.11947/j.AGCS.2017.20160491

Multi-beam Bathymetry Data Processing Using Iterative Algorithm of Robust Least Squares Collocation

  • WANG Leyang ,
  • CHEN Hanqing
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  • 1. Faculty of Geomatics, East China University of Technology, Nanchang 330013, China;
    2. Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASG, Nanchang 330013, China;
    3. Key Laboratory for Digital Land and Resources of Jiangxi Province, Nanchang 330013, China

Received date: 2016-10-17

  Revised date: 2017-04-13

  Online published: 2017-06-05

Supported by

National Natural Science Foundation of China (Nos.41664001;41204003);Support Program for Outstanding Youth Talents in Jiangxi Province (No.20162BCB23050);National Key Research and Development Program(No.2016YFB0501405);Science and Technology Project of the Education Department of Jiangxi Province (No.GJJ150595);the Project of Key Laboratory for Digital Land and Resources of Jiangxi Province(No.DLLJ201705)

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Abstract

In the process of dealing with multi-beam bathymetry data by least squares collocation, the quadric curved mathematical model of trend term can not express accurately the whole variation trend of seafloor topography in general. Moreover, the covariance function estimated by general method is incapable of accurately expressing statistical characteristics with the multi-beam bathymetry data contains gross errors or outliers. So the iterative algorithm of robust least squares collocation is proposed in this paper. Firstly, the initial weight matrix of observations and the initial parameters of covariance function are both given in this method, then the trend term is fitted by polyhedral function and equivalent weights scheme is applied into robust estimation in this method. Finally, the robust parameters of covariance function and solutions of least squares collocation are iteratively calculated. The experimental results show that the method proposed in this paper can express well the whole variation trend of seafloor topography and overcome the effect of gross error or outlier in multi-beam bathymetry data to a certain extent. Compared with the conventional robust method, the proposed method in this paper more effectively probes the outliers in bathymetry data with the robust and better predicted results.

Key words： least squares collocation; seabed terrain generation; covariance function; robust; trend term

Cite this article

WANG Leyang , CHEN Hanqing . Multi-beam Bathymetry Data Processing Using Iterative Algorithm of Robust Least Squares Collocation[J]. Acta Geodaetica et Cartographica Sinica, 2017 , 46(5) : 658 -665 . DOI: 10.11947/j.AGCS.2017.20160491

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