Comparison Between Gross Errors Detection Methods in Surveying Measurements

Khalid Ali Mohammed Haidar, Ahmed Mohamed Ibrahim

Abstract


The least squares estimation method is commonly used to process measurements. In practice, redundant measurements are carried out to ensure quality control and to check for errors that could affect the results. Therefore, an insurance of the quality of these measurements is an important issue. Measurement errors of collected data have different levels of influence due to their number, measured accuracy and redundancy. The aim of this paper is to examine the detection of gross error capabilities in vertical control networks using three methods; Global Test, Data Snooping and Tau Test to compare the effectiveness of these three methods. With the least squares’ method, if there are gross errors in the observations, the sizes of the corresponding residuals may not always be larger than for other residuals that do not have gross errors. This makes it difficult to find (detect) it. Therefore, it is not certain that serious errors should be detected by just examining the magnitudes of the residuals alone. These methods are used in conjunction with developed programs to calculate critical values for the distributions (in real time) rather than look for these in statistical tables. The main conclusion reached is that the tau (τ) statistic is the most sensitive to the presence gross error detection; therefore, it is the one recommended to be used in gross error detection.

Keywords


gross error, statistical test, data snooping, redundancy, quality control.

Full Text:

PDF

References


Barada, W., (1968). "A testing procedure for use in geodetic networks". publications on geodesy, new series, Netherlands geodetic commission, V. 2, N. 5, delft, the Netherlands.

Pope, A, (1976). "The statistics of residuals and the detection of outliers". NOAA technical report NOS 65 NGS1, U.S. department of commerce, Washington, D.C., USA.

Caspary, W.F (1987). "Concepts of networks and deformation analysis". school of surveying monograph II, university of New South Wales, 183 PP.

Cooper, M.A.R (1987). "Control surveying in civil engineering". Blackwell scientific Oxford, 381 PP.

Ibrahim, A. M. (1995). "Reliability analysis of combined GPS-Aerial triangulation system". Ph.D. thesis, Newcastle university, England.

Secord. J. M. (1986). "Terrestrial survey methods for Preston deformation measurements". Oct. 31-Nov.I. Massachusetts institute of technology, Cambridge, MA

Cross P.A (1983). "Advanced least squares applied to position fixing". working paper No6 department of surveying, North East London polytechnic, 185 PP.

El-Hakim, S.F and Zeimann, H. (1984). "Step-by-step strategy for gross error detection". photogrammetric engineering and remote sensing, Vol. 50 (6), 6PP.

Mierlo, J. Van (1977). "Systematic investigations on the stability of control points". presented paper at XV international congress of surveyors, stockholm, Sweden.

Uotila, A.U. (1976). "Statistical tests as guidelines in analysis of adjustment of control nets". presented paper, federation international des geometers, 14th Congress, Washington, D.C.

Saifeldeen Abdalmajeed Mahmood, (2019) "Performance Evaluation of Natural Scenes Features to create Opinion Unaware-Distortion Unaware IQA Metric", Journal of Engineering and Computer Science (JECS), Vol 20, No 3.

Achtert, E., Kriegel, H.-P., Reichert, L., Schubert, E., Wojdanowski, R., Zimek, A. (2010). "Visual evaluation of outlier detection models". in proc. international conference on database systems for advanced applications (DASFAA), Tsukuba, Japan.

Klein, I. et al. (2015). "On evaluation of different methods for quality control of correlated observations". Survey review, 47 (340), pp. 28–35.

Knight, N. L. Wang, J. Rizos, C. (2010). "Generalised measures of reliability for multiple outliers". Journal of Geodesy, 84, pp. 625–635.

Awad Saad Hassan, Omer Saad Ali, (2021), "Industrial Building Systems (IBS) as an Alternative Approach for Housing the Poor in Sudan", Journal of Engineering and Computer Science (JECS), Vol 22, No 1.

Lehmann, R. (2013a). "On the formulation of the alternative hypothesis for geodetic outlier detection". Journal of Geodesy, 87, pp. 373–386.

Lehmann, R. (2013b). "The 3σ-rule for outlier detection from the viewpoint of geodetic adjustment". Journal of Surveying Engineering, 139(4), pp. 157–165.

Leys, C. et al. (2013). "Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median". Journal of Experimental Social Psychology, 49(4), pp. 764-766.

Rofatto, V. F. Matsuoka, M. T. Klein, I. (2017). "An attempt to analyse Baarda’s iterative data snooping procedure based on Monte Carlo simulation". South African Journal of Geomatics, 6 (3), pp. 416-435.

Rofatto, V. F. Matsuoka, M. T. Klein, I. (2018). "Design of geodetic networks based on outlier identification criteria: an example applied to the leveling network". Bulletin of Geodetic Sciences, 24 (2), pp. 152-170.

Teunissen, P. J. G. (2018). "Distributional theory for the DIA method". journal of geodesy, 92, pp. 59-80.

Yetkin, M. Berber, M. (2013). "Application of the Sign-Constrained Robust Least-Squares Method to Surveying Networks". journal of surveying engineering, 139 (1), pp. 59-65.

Wang J, Knight N (2012). "New outlier separability test and its application in GNSS positioning". J Glob position syst 11(1):46–57

Willberg, Martin, Zingerle, Philipp, Pail, Roland (2019). "Residual least-squares collocation: use of covariance matrices from high-resolution global geopotential models". journal of geodesy, volume 93, issue 9, pp.1739-1757.

Yang L, Wang J, Knight N, Shen Y (2013). "Outlier separability analysis with a multiple alternative hypotheses test". J geod 87(6):591–604.