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Weakly Multicollinear Datum Transformations

机译:弱多共线基准变换

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Geodetic network design and optimization is a very well-known concept in geodesy. However, in many cases, the available geodetic network configuration with respect to the estimation model is insufficient because of the physical and financial limitations. For the case of estimating the datum transformation parameters between two datums, the colocated points are only an unevenly and inhomogenously distributed subset of the available national/regional networks. Because the transformation parameters are defined with respect to an earth-centered, earth-fixed (ECEF) frame, very limited geographic coverage of the national/regional networks often leads to a weakly multicollinear estimation problem. Such limited geographical coverage is often coupled with the intrinsic geometrical distortions as well as the relatively lower precision of the observations, in particular, when transforming a terrestrial network into a space-based network. In such cases, the individual parameters become highly correlated and oversensitive to the network configuration, and the individual transformation parameters cannot be estimated reliably. In this study, the concept of an idealized three-dimensional (3D) regional network geometry is introduced, its inverse cofactor matrix is analytically derived, and a regularized estimation method based on the inverse cofactor matrix of an ideal network distribution is presented to deal with the weakly multicollinear datum transformation problem. The efficiency of the proposed method is shown in three realistically simulated networks. The proposed method outperforms the standard least squares in terms of mean square error (MSE) and reduces the correlations among the parameters.
机译:大地测量网络的设计和优化是大地测量学中非常著名的概念。但是,在许多情况下,由于物理和财务方面的限制,相对于估计模型而言,可用的大地测量网络配置不足。对于估计两个基准之间的基准转换参数的情况,共置点仅是可用国家/地区网络的不均匀且不均匀分布的子集。由于转换参数是相对于以地球为中心的固定地球(ECEF)框架定义的,因此国家/区域网络的地理覆盖范围非常有限,通常会导致弱共线性估计问题。这种有限的地理覆盖范围通常与固有的几何变形以及相对较低的观测精度相结合,尤其是在将地面网络转换为基于空间的网络时。在这种情况下,各个参数变得高度相关并且对网络配置过于敏感,并且各个转换参数无法可靠地估算。在这项研究中,介绍了理想的三维(3D)区域网络几何的概念,分析了其逆辅因子矩阵,并提出了一种基于理想网络分布的逆辅因子矩阵的正则化估计方法弱多共线基准变换问题。在三个实际仿真的网络中显示了该方法的效率。提出的方法在均方误差(MSE)方面优于标准最小二乘,并减少了参数之间的相关性。

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