说明：  适当选择辅助变量，使之满足相应条件，参数估计值就可以是无偏一致。估计辅助变量法的计算量与最小二乘法相当，但辨识效果却比最小二乘法好的多。尤其当噪声是有色的，而噪声的模型结构又不好确定时，增广最小二乘法和广义最小二乘法一般都不好直接应用，因为他们需要选用特定的模型结构，而辅助变量法不需要确定噪声的模型结构，因此辅助变量法就显得更为灵活，但辅助变量法不能同时获得噪声模型的参数估计。
(Choose appropriate secondary variables, meet the relevant conditions and parameter estimate can be unbiased consistent. Estimated auxiliary variable method calculation and least square method is quite, but the identification effect is much better than the least square method. Especially when the noise is colored, and noise model structure and not sure, augmented the least squares and the generalized least squares method is generally not used directly, because they need to choose specific model structure, and auxiliary variable method does not need to make sure that noise model structure, so the auxiliary variable method is more agile, but not at the same time auxiliary variable method for noise model parameter estimation.)