Abstract
Generally, gross errors exist in observations, and they affect the accuracy of
results. We review methods to detect the gross errors by Robust estimation method based
on L1-estimation theory and their validity in adjustment of geodetic networks with different
condition. In order to detect the gross errors, we transform the weight of accidental model
into equivalent one using not standardized residual but residual of observation, and apply
this method to adjustment computation of triangulation network, traverse network, satellite
geodetic network and so on. In triangulation network, we use a method of transforming
into equivalent weight by residual and detect gross error in parameter adjustment without
and with condition. The result from proposed method is compared with the one from using
standardized residual as equivalent weight. In traverse network, we decide the weight by
Helmert variance component estimation, and then detect gross errors and compare by the
same way with triangulation network In satellite geodetic network in which observations
are correlated, we detect gross errors transforming into equivalent correlation matrix by
residual and variance inflation factor and the result is also compared with the result from
using standardized residual. The results of detection are shown that it is more convenient
and effective to detect gross errors by residual in geodetic network adjustment of various
forms than detection by standardized residual.
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