EGU2020-18906
https://doi.org/10.5194/egusphere-egu2020-18906
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Ridge estimation iterative algorithm to ill-posed uncertainty adjustment model

tieding lu
tieding lu
  • East China University of Technology, Geomatics, Surveying Engineering, China (tieding_lu@163.com)

 Uncertainties usually exist in the process of acquisition of measurement data, which affect the results of the parameter estimation. The solution of the 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, i.e., the coefficient matrix is ill-posed, the ridge estimation can effectively suppress the influence of the ill-posed problem of the observation equation on the parameter estimation. When the uncertainty adjustment model is ill-posed, it is more seriously affected by the error of the coefficient matrix and observation vector. In this paper, the ridge estimation method is applied to ill-posed uncertainty adjustment model, deriving an iterative algorithm to improve the stability and reliability of the results. The derived algorithm is verified by two examples, and the results show that the new method is effective and feasible.

How to cite: lu, T.: Ridge estimation iterative algorithm to ill-posed uncertainty adjustment model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18906, https://doi.org/10.5194/egusphere-egu2020-18906, 2020

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