在测量数据的获取过程中, 经常存在着不确定性, 它们影响着参数估计的可靠性。本文通过把不确定度作为参数融入函数模型, 建立了不确定性平差模型。依据残差中不确定性传播规律, 确定了残差最大不确定度达到最小的平差准则, 利用迭代算法得到了不确定性平差模型的解算方法。通过实例分析了最小二乘平差、整体最小二乘平差和不确定性平差准则下最优解的不同特点, 从一个新的角度探讨了不确定性观测数据处理方法, 推广了现有的误差理论。
Uncertainty often exists in the process of obtaining measurement data, which affects the reliability of parameter estimation. This paper establishes a new adjustment model in which uncertainty is incorporated into the function model as a parameter. A new adjustment criterion and its iterative algorithm are given based on uncertainty propagation law in the residual error, in which the maximum possible uncertainty is minimized. This paper also analyzes, with examples, the different adjustment criteria and features of optimal solutions about the least-squares adjustment, the uncertainty adjustment and total least-squares adjustment. Existing error theory is extended with new observational data processing method about uncertainty.
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