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Empirical methods of reducing the observations in geodetic networks

机译:减少大地测量网络中观测值的经验方法

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The paper presents empirical methodology of reducing various kinds of observations in geodetic network. A special case of reducing the observation concerns cartographic mapping. For numerical illustration and comparison of methods an application of the conformal Gauss-Krüger mapping was used. Empirical methods are an alternative to the classic differential and multi- stages methods. Numerical benefi ts concern in particular very long geodesics, created for example by GNSS vectors. In conventional methods the numerical errors of reduction values are signifi cantly dependent on the length of the geodesic. The proposed empirical methods do not have this unfavorable characteristics. Reduction value is determined as a difference (or especially scaled difference) of the corresponding measures of geometric elements (distances, angles), wherein these measures are approximated independently in two spaces based on the known and corresponding approximate coordinates of the network points. Since in the iterative process of the network adjustment, coordinates of the points are systematically improved, approximated reductions also converge to certain optimal values.
机译:本文提出了减少大地测量网络中各种观测值的经验方法。减少观测值的一种特殊情况涉及制图。为了进行数值说明和方法比较,使用了保形高斯-克鲁格映射的应用。经验方法是经典差分和多阶段方法的替代方法。数值收益尤其涉及很长的测地线,例如由GNSS向量创建的测地线。在常规方法中,减小值的数值误差明显取决于测地线的长度。所提出的经验方法没有这种不利的特征。减小值被确定为几何元素的相应量度(距离,角度)的差(或尤其是比例差),其中,基于网络点的已知和相应的近似坐标,在两个空间中独立地近似这些量度。因为在网络调整的迭代过程中,系统地改善了点的坐标,所以近似的减少也收敛到某些最佳值。

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