American Society of Civil Engineers


Robust-Biased Estimation Based on Quasi-Accurate Detection


by Qing-ming Gui, (Inst. of Surveying and Mapping, Information Engrg. Univ., No. 66 Longhai Middle Rd., Zhengzhou 450052, P. R. China. E-mail: guiqm@public2.zz.ha.cu), Guo Czhong Li, (Inst. of Surveying and Mapping, Information Engrg. Univ., No. 66 Longhai Middle Rd., Zhengzhou 450052, P. R. China), and Ji-kun Ou, (Inst. of Geodesy and Geophysics, Chinese Academy of Sciences, No. 174 Xudong Rd., Wuhan 430077, P. R. China. E-mail: ojk1009@public.wh.hb.cn)

Journal of Surveying Engineering, Vol. 131, No. 3, August 2005, pp. 67-72, (doi:  http://dx.doi.org/10.1061/(ASCE)0733-9453(2005)131:3(67))

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Document type: Journal Paper
Abstract: In order to combat the influences of both outlier and multicollinearity on geodetic adjustments, a new robust-biased estimation method is proposed by combining outlier identification with biased estimation. The estimation scheme is roughly divided into two steps. First, quasi-accurate detection of gross error (QUAD) is used to detect outliers and correct observations. Then the “clean” observations and biased estimations are used to obtain more accurate estimates of unknown parameters. Several selection schemes of the biased parameters included in the biased estimators based on QUAD are given in detail. A numerical example illustrates that the new robust-biased estimation method not only can resist the bad influence of outlier and effectively overcome the difficulty caused by multicollinearity simultaneously, but also is far more accurate than least-squares estimation, biased estimation, robust estimation, and generalized shrunken type-robust estimation.


ASCE Subject Headings:
Estimation
Geodetic surveys
Errors