Baarda粗差探测和M抗差估计的优劣性比较

Comparison between Baarda Gross Error Detection and M-Robust Estimation

最小二乘平差法广泛应用于测量数据处理,缺点是不能根据残差有效地发现和定位粗差,而基于均值平移模型的粗差探测和基于方差膨胀模型的抗差估计,继承了最小二乘优良的性质,同时能对粗差进行良好的定位和修正。本文结合实例,对Baarda粗差探测和M抗差估计进行了对比分析,结果表明,M抗差估计粗差探测效果优于Baarda粗差探测。

The least squares adjustment method is widely used in measurement data processing,but it can not find and locate the gross error effectively according to the residual error.The gross error detection based on mean shift model and robust estimation based on variance inflation model inherit the excellent properties of least squares,and can locate and correct gross errors well.This paper makes a comparative analysis of Baarda gross error detection and M robust estimation with an example,and the results show that M robust estimation is better than Baarda gross error detection.