Mixed LS-TLS Estimation Based on Nonlinear Gauss-Helmert Model

  • FANG Xing ,
  • ZENG Wenxian ,
  • LIU Jingnan ,
  • YAO Yibin ,
  • WANG Yong
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  • 1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    2. Research Center of GNSS, Wuhan University, Wuhan 430079, China;
    3. Surveying and Mapping School of Zhengzhou, Zhengzhou 450015, China

Received date: 2015-03-26

  Revised date: 2015-11-01

  Online published: 2016-03-25

Supported by

The National Natural Science Foundation of China(Nos.41404005;41474006;41231174;41274022);The Fundamental Research Founds for the Central Universities(No.2042014kf053)

Abstract

For the case of design matrix in EIV(errors-in-variables) model containing both fixed elements and random elements, this paper proposes a mixed LS-TLS(least squares-total least squares) algorithm and deduces the precision estimator by reformulating an EIV model as a nonlinear Gauss-Helmert model, in which random elements are extracted to the random model of adjustment. This algorithm can be applied to the general design matrix including simultaneously fixed columns, fixed elements and random elements. The example illustrates that the solution of mixed LS-TLS equal the solution of structured or weighted TLS algorithms which can solve mixed LS-TLS problem. Additionally, the solution of mixed LS-TLS statistically superior to solution of LS or TLS.

Cite this article

FANG Xing , ZENG Wenxian , LIU Jingnan , YAO Yibin , WANG Yong . Mixed LS-TLS Estimation Based on Nonlinear Gauss-Helmert Model[J]. Acta Geodaetica et Cartographica Sinica, 2016 , 45(3) : 291 -296 . DOI: 10.11947/j.AGCS.2016.20150157

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