Compared with the recursive extended least squares algorithms, the proposed two algorithms have fast convergence rates and can produce highly accurate parameter estimation.
与常规递推增广最小二乘算法相比，提出的方法具有更快的收敛速度，能产生更高精度的参数估计。
Using the model Identification and Parameter Estimation, the linear model is turns out to be accurate.
并通过模型识别与参数估计，得到线性模型的准确形式。
The comparison among various methods of parameter estimation shows that the least-squares fitting method in the time domain is more accurate one.
各种参数估值方法的比较表明，时间域最小二乘拟合法较为精确。
The new method can give more accurate results of parameter estimation with more effective con-vergence rate than EKF does since the computation of innovation is improved.
由于改善了偏差估计的新息计算，使得偏差估计的结果更准确、收敛速度更快。
The new method can give more accurate results of parameter estimation with more effective con-vergence rate than EKF does since the computation of innovation is improved.
由于改善了偏差估计的新息计算，使得偏差估计的结果更准确、收敛速度更快。
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