顾及系数矩阵结构性的加权总体最小二乘解算

发布时间：2018-04-12 16:23

本文选题：加权总体最小二乘WLTS + 总体最小二乘平差EIV模型　；参考：《测绘科学》2017年04期

【摘要】：针对加权总体最小二乘平差模型中系数矩阵具有结构性的问题,该文设计了一种顾及系数矩阵结构性的加权总体最小二乘迭代解法:首先,利用非线性最小二乘平差方法将总体最小二乘模型线性化;然后,采用结构矩阵的方法顾及系数矩阵的重复元素和常数项,通过间接平差的原理推导了顾及系数矩阵结构性的加权总体最小二乘迭代公式,可适用于加权总体最小二乘的参数估计;最后,通过算例分析并与其他算法进行比较,验证了该算法的有效性和可行性。
[Abstract]:In order to solve the structural problem of coefficient matrix in weighted population least square adjustment model, a weighted global least squares iterative solution considering the structure of coefficient matrix is designed in this paper.The nonlinear least square adjustment method is used to linearize the total least squares model, and the structural matrix is used to take into account the repeated elements and constant terms of the coefficient matrix.Based on the principle of indirect adjustment, the iterative formula of weighted population least squares considering the structure of coefficient matrix is derived, which can be used to estimate the parameters of weighted population least squares.The validity and feasibility of the algorithm are verified.
【作者单位】：湖南软件职业学院;湘潭大学能源工程学院;
【基金】：湖南省教育厅科研项目(15C0741,13C903)
【分类号】：P207

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