赫尔默特方差分量估计在边角网中的应用

The application of Helmert variance component estimation in the corner- edge network

在融合多源异构信息时,不同种类的观测值应具有不同的权阵。但是在数据处理前,往往不知道不同观测值之间的关系,进而无法对不同观测值进行定权。针对边角网布设时对角度和边长两类观测值进行测量平差时观测值种类不同的问题,本文在经典最小二乘基础上将赫尔默特(Helmert)方差分量估计应用到边角网平差过程中,并通过算例进行分析。结果表明,将Helmert方法应用于两类观测值的平差后,精度有所提高,可为多类观测值、平差网形较大、精度要求高的工程应用提供一定的参考。

When multi-sourced heterogeneous information is fused,different types of observations should have different weight arrays,while before data processing,it is usually not known the relationship between different observations,so it is impossible to determine the weight of different observations.For the reasons above,the Helmert variance component estimation is used in this paper in the adjustment process of the corner-edge network on the basis of the classical least squares in view of the different types of observations during the adjustment of angle and side length.The results show that the accuracy of the Helmert method is improved in the adjustment of the two types of observations,it will provide some helpful reference for the engineering applications of multiple types of observations,large adjustment mesh and high accuracy requirements.