Acta Geodaetica et Cartographica Sinica ›› 2019, Vol. 48 ›› Issue (4): 403-411.doi: 10.11947/j.AGCS.2019.20180044

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Ridge estimation algorithm to ill-posed uncertainty adjustment model

LU Tieding1,2,3, WU Guangming1, ZHOU Shijian4   

  1. 1. Faculty of Geomatics, East China University of Technology, Nanchang 330013, China;
    2. Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASMG, Nanchang 330013, China;
    3. Jiangxi Province Key Lab for Digital Land, Nanchang 330013, China;
    4. Nanchang Hangkong University, Nanchang 330063, China
  • Received:2018-01-25 Revised:2019-01-29 Online:2019-04-20 Published:2019-05-15
  • Supported by:
    The National Natural Science Foundation of China(No.41464001); The Special S-cientific Research Fund for Public Welfare Profession of Surveying, Mapping and Geoinformation (No.201512026); The Science and Technology Project of the Education Department of Jiangxi Province (No. KJLD12077); The State's Key Project of Research and Development Plan(Nos. 2016YFB0501405; 2016YFB0502601-04); The Natural Science Foundation of Jiangxi Province of China(No. 2017BAB203032)

Abstract: Uncertainties usually exist in the process of acquisition of measurement data, which affects the parameter estimation results. The solution method of uncertainty adjustment model can effectively improve the validity and reliability of parameter estimation. When the coefficient matrix of the observation equation has a singular value close to zero, the ridge estimation can effectively suppress the influence of the ill-posed state of the observation equation on the parameter estimation results.When the uncertainty adjustment model is ill-posed, it is more seriously affected by the error of the coefficient matrix and the observation,this paper applies ridge estimation method to ill-posed uncertainty adjustment model, derives an iterative algorithm to improve the stability and reliability of the result, and verifies it with two examples. The results show that the new method is effective and feasible.

Key words: ill-posed, uncertainty, adjustment model, ridge estimation

CLC Number: