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An attempt to determine the effect of increase of observation correlations on detectability and identifiability of a single gross error

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Języki publikacji
EN
Abstrakty
EN
The paper presents the results of investigating the effect of increase of observation correlations on detectability and identifiability of a single gross error, the outlier test sensitivity and also the response-based measures of internal reliability of networks. To reduce in a research a practically incomputable number of possible test options when considering all the non-diagonal elements of the correlation matrix as variables, its simplest representation was used being a matrix with all non-diagonal elements of equal values, termed uniform correlation. By raising the common correlation value incrementally, a sequence of matrix configurations could be obtained corresponding to the increasing level of observation correlations. For each of the measures characterizing the above mentioned features of network reliability the effect is presented in a diagram form as a function of the increasing level of observation correlations. The influence of observation correlations on sensitivity of the w-test for correlated observations (Förstner 1983, Teunissen 2006) is investigated in comparison with the original Baarda’s w-test designated for uncorrelated observations, to determine the character of expected sensitivity degradation of the latter when used for correlated observations. The correlation effects obtained for different reliability measures exhibit mutual consistency in a satisfactory extent. As a by-product of the analyses, a simple formula valid for any arbitrary correlation matrix is proposed for transforming the Baarda’s w-test statistics into the w-test statistics for correlated observations.
Rocznik
Strony
313--333
Opis fizyczny
Bibliogr. 21 poz., tab., wykr.
Twórcy
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Pl. Politechniki 1, 00-661 Warsaw, Poland
autor
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Pl. Politechniki 1, 00-661 Warsaw, Poland
Bibliografia
  • [1] Ananga, N., Coleman, R. and Rizos, C. (1994). Variance-covariance estimation of GPS Networks. Bulletin Geodesique, 68: 77–87.
  • [2] Baarda, W. (1968). A testing procedure for use in geodetic networks. Publications on Geodesy, New Series, vol.2, no.5, Netherlands Geodetic Commission, Delft.
  • [3] Cook, R.D. and Weisberg, S. (1982). Residuals and influence in regression. Chapman and Hall, New York.
  • [4] Dufresne, D. (2005). Two notes on financial mathematics. Actuarial Research Clearing House, No.2.
  • [5] Förstner, W. (1983). Reliability and discernibility of extended Gauss-Markov models. Deutsche Geodätische Kommission, Reihe A, No. 98, Munchen.
  • [6] Hawkins, D.M. (1980). Identification of outliers. Chapman and Hall, New York.
  • [7] Kim, H-J. (2006). On the ratio of two folded normal distributions. Communications in Statistics-Theory and Methods, 35: 965–977.
  • [8] Kim, H-J. (2014). Some distributional properties of ratio of two folded normals. Technical Report, Statistics Department, Dongguk University, Seoul, Korea.
  • [9] Knight, N.L, Wang, J. and Rizos, C. (2010). Generalised measures of reliability for multiple outliers. J. Geod., DOI 10.1007/s00190-010-0392-4.
  • [10] Kok, J.J. (1984). On data snooping and multiple outlier testing. NOAA Technical Report, NOS NGS. 30, U.S. Department of Commerce, Rockville, Maryland.
  • [11] Leandro, R., Santos, M. and Cove, K. (2005). An Empirical Approach for the Estimation of GPS Covariance of Observations, ION 61st Annual Meeting, the MITRE Corporation & Draper Laboratory, Cambridge, MA.
  • [12] Prószyński, W. (2000). On outlier-hiding effects in specific Gauss-Markov models: geodetic examples,. J Geod 74: 581–589. DOI: 10.1007/s001900000121.
  • [13] Prószyński, W. (2010). Another approach to reliability measures for systems with correlated observations. J Geod, 84: 547-556. doi:10.1007/s00190-010-0394-2.
  • [14] Prószyński, W. (2015). Revisiting Baarda’s concept of minimal detectable bias with regard to outlier identifiability, J Geod, 89: 993-1003. DOI 10.1007/s00190-015-0828-y.
  • [15] Prószyński, W, Kwaśniak, M. and Twardziak, P. (2011). Essentials of internal reliability analysis for systems with correlated observations (Technical Report – unpublished), research sponsored by Committee for Scientific Research (No. N N526 135134).
  • [16] Schaffrin, B. (1997). Reliability measures for correlated observations, J. Surv. Eng., 123 (3): 126–137.
  • [17] Teunissen, P.J.G. (1990). Quality control in integrated navigation systems. IEEE Aerosp. Electron. Syst. Mag. 5(7): 35–41.
  • [18] Teunissen, P.J.G. (2006). Testing theory, an introduction. Delft University Press, Delft.
  • [19] Wang, J. and Chen, Y. (1994). On the reliability measure of observations. Acta Geodaet. et Cartograph. Sinica, English Edition, pp. 42–51.
  • [20] Wang, J., Almagbile, Y., Wu, T. and Tsujii, T. (2012). Correlation Analysis for Fault Detection Statistics in Integrated GNSS/INS Systems, Journal of global positioning systems, 11(2): 89–99.
  • [21] Wang, J. and Knight, N. (2012). New Outlier Separability Test and Its Application in GNSS Positioning. Journal of Global Positioning Systems, 11(1): 46–57, DOI: 10.5081/jgps.11.1.46.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-45bbe044-f5e5-4746-ada9-3f1acd6273c3
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