部分待估参数具有先验随机性的WTLS平差

部分待估参数具有先验随机信息，且误差方程系数矩阵含有观测误差，是一类新的平差问题。本文构造了部分待估参数含有先验随机信息的加权整体最小二乘平差函数模型，推导该模型参数估计与精度评定公式，给出计算步骤，适用于一般情形。实例对比分析证明，该算法正确可靠，迭代收敛速度较优。

Weighted Total Least-Squares Adjustment with Partial Prior Random Parameter

A total least square with partial random parameter adjustment problem occurs if some of the estimated parameters in an adjustment problem have priori random information and the error equation coefficient matrix contains observation errors. This paper proposes a function model of total least squares adjustment with additional partial random parameters. The model has general adaptability. The algorithms formula of parameter estimation and accuracy evaluation are derived, and the steps of computation are presented, which can process the data that only partial (from 0 to all) parameter has random prior information. The feasibility, reliability and correctness of the algorithms are demonstrated by several examples and comparative analysis. The proposed algorithms have advantages in iterative convergence times.