Illustrative presentation of some basic concepts of network internal reliability with comments as regards engineering surveys

• Autorzy: Prószyński W.

Identyfikatory

DOI

10.1515/rgg-2016-0021

• Języki publikacji: EN

Abstrakty

EN

The paper integrates some earlier and the recent findings of the author in the area of network internal reliability and presents a consistent system of concepts in this respect. The concepts of outlier detection and outlier identification linked directly with the global model test and the outlier tests respectively, are shown as a basis for the concepts such as outlier detectability and outlier identifiability. Also, a four level classification of gross errors expressed in a form of a tree-diagram is presented including perceptible and imperceptible errors, detectable and undetectable errors and identifiable and unidentifiable errors. Their properties are given mainly in a descriptive way, deliberately limiting rigorous mathematical formulas to a necessary minimum. Understanding of different types of gross errors is useful in analyzing the results of the outlier detection and identification procedures as well as in designing the networks to make them duly robust to observation gross errors. It is of special importance for engineering surveys where quite often low-redundancy networks are used. Main objective of the paper is to demonstrate a clear and consistent system of basic concepts related to network internal reliability.

Słowa kluczowe

EN

unit redundancy; low-redundancy networks; detectability; identifiability; gross error classification

PL

redundancja jednostki; sieci niskiej redundancji; wykrywalność; identyfikowalność; błąd klasyfikacji

• Wydawca: Wydział Geodezji i Kartografii Politechniki Warszawskiej
• Czasopismo: Reports on Geodesy and Geoinformatics
• Rocznik: 2016
• Tom: Vol. 101
• Strony: 54--59
• Opis fizyczny: Bibliogr. 14 poz., rys.

Twórcy

autor

Prószyński W.

• Warsaw University of Technology, Faculy of Geodesy and Cartography, Pl. Politechniki 1, 00-661 Warsaw, Poland

Bibliografia

• [1] Baarda, W. (1968). A testing procedure for use in geodetic networks. Publications on Geodesy, New Series, vol.2, no.5, Netherlands Geodetic Commission, Delft
• [2] Förstner, W. (1983). Reliability and discernability of extended Gauss-Markov models. Deutsche Geodätische Kommission, Reihe A, No. 98, Munchen
• [3] Hawkins, D. M. (1980). Identification of outliers. Chapman and Hall, New York
• [4] Knight, N. L., Wang, J. & Rizos, C. (2010). Generalised measures of reliability for multiple outliers. J Geod., DOI. 10.1007/s00190-010-0392-4
• [5] Prószyński, W. (2008). The vector space of imperceptible observation errors: a supplement to the theory of network reliability. Geodesy and Cartography; vol. 57, No.1, pp. 3-19
• [6] Prószyński, W. (2010). Another approach to reliability measures for systems with correlated observations. J Geod 84: pp. 547-556
• [7] Prószyński, W. (2015). Revisiting Baarda’s concept of minimal detectable bias with regard to outlier identifiability. J Geod 89: pp. 993-1003
• [8] Schaffrin, B. (1997). Reliability measures for correlated observations. J. Surv. Eng., 123 (3), pp. 126-137
• [9] Teunissen, P. J. G. (1990). Quality control in integrated navigation systems. IEEE Aerosp Electron Syst Mag 5(7), pp. 35-41
• [10] Teunissen, P. J. G. (1998). Minimal detectable biases of GPS data. J Geod 72: pp. 236-244.
• [11] Teunissen, P. J. G. (2000). Testing theory: an introduction. Delft University Press, Delft
• [12] Wang, J. & Chen, Y. (1994). On the reliability measure of observations. Acta Geodaet. et Cartograph. Sinica, English Edition, pp. 42-51
• [13] Wang, J. & Knight, N. (2012). New Outlier Separability Test and Its Application in GNSS Positioning. Journal of Global Positioning Systems, 11(1), pp. 46-57
• [14] Yang, L., Wang, J., Knight, N. & Shen, Y. (2013). Outlier Separability Analysis with a Multiple Alternative Hypotheses Test. J Geod 87(6), pp. 591-604

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.