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    Solution for the Robust Estimation of Heterogeneous Data Fusion Based on Classification Estimation

    Source: Journal of Surveying Engineering:;2024:;Volume ( 150 ):;issue: 003::page 04024004-1
    Author:
    Yeqing Tao
    ,
    Xinchuan Li
    ,
    Hao Chen
    ,
    Juan Yang
    DOI: 10.1061/JSUED2.SUENG-1492
    Publisher: ASCE
    Abstract: Data fusion is an important issue as multi-source observation technology is widely used in geoscience. Although the problem of robust estimation exists widely in the data fusion, few solutions have been reported. This paper investigates a solution for the robust estimation of heterogeneous data fusion implementing classification, robust estimation, and data fusion. A new approach based on Msplit estimation is constructed to define accurate scales for multi-source observation data and, adopting the Institute of Geodesy and Geophysics (IGG)III weight function, an iterative algorithm is proposed for the above problem. Finally, two instances are considered in verifying the feasibility of the presented solution.
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      Solution for the Robust Estimation of Heterogeneous Data Fusion Based on Classification Estimation

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4296863
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    contributor authorYeqing Tao
    contributor authorXinchuan Li
    contributor authorHao Chen
    contributor authorJuan Yang
    date accessioned2024-04-27T22:31:44Z
    date available2024-04-27T22:31:44Z
    date issued2024/08/01
    identifier other10.1061-JSUED2.SUENG-1492.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296863
    description abstractData fusion is an important issue as multi-source observation technology is widely used in geoscience. Although the problem of robust estimation exists widely in the data fusion, few solutions have been reported. This paper investigates a solution for the robust estimation of heterogeneous data fusion implementing classification, robust estimation, and data fusion. A new approach based on Msplit estimation is constructed to define accurate scales for multi-source observation data and, adopting the Institute of Geodesy and Geophysics (IGG)III weight function, an iterative algorithm is proposed for the above problem. Finally, two instances are considered in verifying the feasibility of the presented solution.
    publisherASCE
    titleSolution for the Robust Estimation of Heterogeneous Data Fusion Based on Classification Estimation
    typeJournal Article
    journal volume150
    journal issue3
    journal titleJournal of Surveying Engineering
    identifier doi10.1061/JSUED2.SUENG-1492
    journal fristpage04024004-1
    journal lastpage04024004-9
    page9
    treeJournal of Surveying Engineering:;2024:;Volume ( 150 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian