Acta Geodaetica et Cartographica Sinica ›› 2016, Vol. 45 ›› Issue (1): 22-29.doi: 10.11947/j.AGCS.2016.20140560

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An Algorithm for Partial EIV Model

WANG Leyang1,2,3, YU Hang1, CHEN Xiaoyong1,2,3   

  1. 1. Faculty of Geomatics, East China Institute of Technology, Nanchang 330013, China;
    2. Key Laboratory of Watershed Ecology and Geographical Environment Monitoring of NASG, Nanchang 330013, China ;
    3. Jiangxi Province Key Lab for Digital Land, Nanchang 330013, China
  • Received:2014-10-30 Revised:2015-04-15 Online:2016-01-20 Published:2016-01-28
  • Supported by:
    The National Natural Science Foundation of China (Nos.41204003;41161069;41304020);National Department Public Benefit Research Foundation (Surveying,Mapping and Geoinformation) (No. 201512026);Natural Science Foundation of Jiangxi Province (Nos.20132BAB216004;20151BAB203042);Science and Technology Project of the Education Department of Jiangxi Province (Nos.GJJ13456;KJLD12077;KJLD14049);Key Laboratory of Geo-informatics of State Bureau of Surveying and Mapping (No.201308);Scientific Research Foundation of ECIT (No.DHBK201113).

Abstract: A new thinking for solving partial errors-in-variables (partial EIV) model was proposed. Through the transposition processing in partial EIV model, a new functional model was reconstructed. Adjustment of indirect observations has been used two times to calculate the model parameters and the stochastic elements in coefficient matrix, translating total least squares problem to least squares problem. It also achieves high convergence rate through some simple variables transformation. Finally, real and simulation data were implemented to compare with the existing algorithms and to analysis the applicability of the proposed algorithms. The results show that the new algorithms are feasible and it can achieve the same values with the existing algorithms.

Key words: total least squares, partial errors-in-variables model, indirect observations adjustment, coordinate transformation, straight line fit

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