Home Multiple incompatible datum points identification in vertical control network for high-speed railway based on likelihood ratio test
Article
Licensed
Unlicensed Requires Authentication

Multiple incompatible datum points identification in vertical control network for high-speed railway based on likelihood ratio test

  • Guangfeng Yan ORCID logo EMAIL logo , Yangtenglong Li and Chunyan Liu
Published/Copyright: July 22, 2021
Become an author with De Gruyter Brill

Abstract

The high-speed railway (HSR) surveying system in China has developed into a modern large-scale precision surveying system with multi-stage structure, large scale, and high precision and reliability requirements. The effective control of the surveying data quality in each stage and each link is a complex but important issue in the processing of surveying data. However, as an important part of surveying system, the study on the data quality control of vertical control network has not attracted as much attention as that of plane control network. Constrained adjustment is the essential link of surveying data processing of HSR vertical control network to obtain the height of new control points. Before that, in addition to the gross errors checking of observations, the compatibility diagnosis of datum points should also be an important step, which is often neglected in practice. In this paper, the likelihood ratio (LR) test with the highest power among all the competitors for simple hypotheses problem is extended to solve the problem of composite hypothesis, resulting in a new multiple incompatible datum points identification strategy (ICDPI-LR). With a benchmark along route control network and a CPIII vertical control network as the example, the performance of the proposed method is demonstrated, and showing the importance and necessity of the identification of incompatible datum points in vertical control network for HSR.

References

[1] Amiri-Simkooei A, 2003. Formulation of L 1 norm minimization in Gauss-Markov models. Journal of Surveying Engineering, 129(1), pp. 37–43.10.1061/(ASCE)0733-9453(2003)129:1(37)Search in Google Scholar

[2] Baarda W, 1968. A testing procedure for use in geodetic networks. Neth Geod Comm Publ on Geodesy, 2(5), pp. 27–55.10.54419/t8w4sgSearch in Google Scholar

[3] Blaha G, 1982. A note on adjustment of free networks. Bulletin Géodésique, 56(4), pp. 281–299.10.1007/BF02525729Search in Google Scholar

[4] Cen M, Li Z, Ding X, et al., 2003. Gross error diagnostics before least squares adjustment of observations. Journal of Geodesy, 77(9), pp. 503–513.10.1007/s00190-003-0343-4Search in Google Scholar

[5] Cen M, Zhang T, Li J, et al., 2011. Comparison of measuring dada compression methods of CPIII control networks. Journal of the China Railway Society, 33(8), 99–102 (in Chinese with English abstract).Search in Google Scholar

[6] Grafarend E, Kleusberg A, Schaffrin B, 1980. An introduction to the variance- covariancecomponent estimation of Helmert type. Z Vermess, 105, pp. 161–180.Search in Google Scholar

[7] Guo J, Ou J, Wang H, 2007. Quasi-Accurate detection of outliers for correlated observations. Journal of Surveying Engineering, 133(3), pp. 129–133.10.1061/(ASCE)0733-9453(2007)133:3(129)Search in Google Scholar

[8] Guo J, Ou J, Wang H, 2010. Robust estimation for correlated observations: two local sensitivity-based downweighting strategies. Journal of Geodesy, 84(4), pp. 243–250.10.1007/s00190-009-0361-ySearch in Google Scholar

[9] Huang S, 1996. The compatibility analysis of common points for GPS network. Wtusm Bulletin of Science and Technology, 2, pp. 1–6 (in Chinese with English abstract).Search in Google Scholar

[10] Kargoll B, 2012. On the theory and application of model misspecification tests in geodesy. Deutsche Geodätsche Kommission Reihe C, München.Search in Google Scholar

[11] Koch K, 1999. Parameter estimation and hypothesis testing in linear models. Springer, Berlin.10.1007/978-3-662-03976-2Search in Google Scholar

[12] Lehmann B, Neitzel F, 2013. Testing the compatibility of constraints for parameters of a geodetic adjustment model. Journal of Geodesy, 87(6), pp. 555–566.10.1007/s00190-013-0627-2Search in Google Scholar

[13] Lehmann B, 2014. Transformation model selection by multiple hypotheses testing. Journal of Geodesy, 88(12), pp. 1117–1130.10.1007/s00190-014-0747-3Search in Google Scholar

[14] Li B, 2016. Surveying network design and adjustment for ballastless track HSR: case study with the first HSR in China. Journal of Surveying Engineering, doi:10.1061/(ASCE)SU.1943-5428.0000171.Search in Google Scholar

[15] Marshall J, 2002. L 1 -norm pre-analysis measures for geodetic networks. Journal of Geodesy, 76(6), pp. 334–344.10.1007/s00190-002-0254-9Search in Google Scholar

[16] Tao B, 2007. Statistical theory and method of survey data processing. Surveying and Mapping Press, Beijing.Search in Google Scholar

[17] Teunissen P, 2000. Testing theory: an introduction. Delft University of Technology, Netherlands.Search in Google Scholar

[18] Weiss G, Weiss R, Bartoš K, et al., 2016. Survey control points: compatibility and verification. Springer International Publishing, Switzerland.10.1007/978-3-319-28457-6Search in Google Scholar

[19] Yan G, Cen M, 2019. The identification method of gross error detection failpoint in L 1 -norm estimation. Acta Geodaetica et Cartographica Sinica, 48(11), pp. 1430–1438 (in Chinese with English abstract).Search in Google Scholar

[20] Yan G, Cen M, Li Y, 2020. Gross error detectability and identifiability analysis in track control network for high-speed railway based on GEJE. Journal of Surveying Engineering, 146(1): 04019020.10.1061/(ASCE)SU.1943-5428.0000297Search in Google Scholar

[21] Yang Y, Song L, Xu T, 2002. Robust estimator for correlated observations based on bifactor equivalent weights. Journal of Geodesy, 76(6), pp. 353–358.10.1007/s00190-002-0256-7Search in Google Scholar

[22] Yetkin M, Inal C, 2011. L 1 norm minimization in GPS networks. Survey Review, 43(323), pp. 523–532.10.1179/003962611X13117748892038Search in Google Scholar

[23] Zhu Y, Lu J, Cheng A, Yan H, Liu C, and Wang G, 2010. Code for engineering survey of high speed railway. China Railway Publishing House, Beijing.Search in Google Scholar

[24] Zhou J, 1983. Quasi-stable adjustment of monitoring networks. Tectonophysics, doi: 10.1016/0040-1951(83)90155-5.Search in Google Scholar

Received: 2021-02-17
Accepted: 2021-07-07
Published Online: 2021-07-22
Published in Print: 2022-01-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 1.11.2025 from https://www.degruyterbrill.com/document/doi/10.1515/jag-2021-0008/html
Scroll to top button