加权总体最小二乘没有考虑观测数据中可能存在的粗差，本文基于IGG权函数，采用选权迭代法求解加权总体最小二乘。结合模拟数据和真实数据，系统地比较了加权总体最小二乘方法、基于Huber权函数的稳健加权总体最小二乘方法和基于IGG权函数的稳健加权总体最小二乘方法的系数估计和误差估计，通过对比分析表明，两种稳健加权总体最小二乘方法的参数估计结果比加权总体最小二乘方法更加可靠，且以基于IGG权函数的稳健加权总体最小二乘方法为最优。

In weighted total least squares, gross errors of observation data are not taken into consideration. In order to resolve this problem, a robust method of weighted total least squares with reweighting iteration based on IGG weighting function is proposed. Thorough experimental evaluation with a large number of simulation data and real-life data sets has been carried out. The results of coefficient estimation and error estimation are systematically compared with weighted total least squares, and robust weighted total least squares based on Huber weighting function. It is shown that (a) more reliable parameter estimation can be obtained by two robust weighted total least squares; and (b) more importantly, the proposed method performs better than others.