The seamless model for three-dimensional datum transformation
The seamless model for three-dimensional datum transformation
复制标题
三维基准转换的无缝模型
DOI：
10.1007/s11430-012-4418-z
复制
发表时间：
2012-06
期刊：
影响因子：
--
通讯作者：
SHEN YunZhong
中科院分区：
文献类型：
--
作者：
Li BoFeng;SHEN YunZhong
随着空间大地测量学的广泛应用，三维基准转换模型必然被用于不同坐标系中的坐标转换。其本质是预测在（此处“se”可能是不完整信息）中的非公共点的坐标。
With extensive applications of space geodesy, three-dimensional datum transformation model has been necessarily used to transform the coordinates in the different coordinate systems. Its essence is to predict the coordinates of non-common points in the second coordinate system based on their coordinates in the first coordinate system and the coordinates of common points in two coordinate systems. Traditionally, the computation of seven transformation parameters and the transformation of non-common points are individually implemented, in which the errors of coordinates are taken into account only in the second system although the coordinates in both two systems are inevitably contaminated by the random errors. Moreover, the coordinate errors of non-common points are disregarded when they are transformed using the solved transformation parameters. Here we propose the seamless (rigorous) datum transformation model to compute the transformation parameters and transform the non-common points integratively, considering the errors of all coordinates in both coordinate systems. As a result, a nonlinear coordinate transformation model is formulated. Based on the Gauss-Newton algorithm and the numerical characteristics of transformation parameters, two linear versions of the established nonlinear model are individually derived. Then the least-squares collocation (prediction) method is employed to trivially solve these linear models. Finally, the simulation experiment is carried out to demonstrate the performance and benefits of the presented method. The results show that the presented method can significantly improve the precision of the coordinate transformation, especially when the non-common points are strongly correlated with the common points used to compute the transformation parameters.
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影响因子：
4.4
作者：
Y. Yang;A. Zeng;J. Zhang
通讯作者：
Y. Yang;A. Zeng;J. Zhang
DOI：
--
发表时间：
1991-04
期刊：
--
影响因子：
--
作者：
R. Rapp
通讯作者：
R. Rapp
影响因子：
4.4
作者：
Yunzhong Shen;Bofeng Li;Yi Chen
通讯作者：
Yunzhong Shen;Bofeng Li;Yi Chen
DOI：
--
发表时间：
2004
期刊：
--
影响因子：
--
作者：
P. Teunissen;D. Simons;C. Tiberius
通讯作者：
P. Teunissen;D. Simons;C. Tiberius
影响因子：
--
作者：
Bofeng Li;Y. Shen;L. Lou
通讯作者：
Bofeng Li;Y. Shen;L. Lou