卡尔曼滤波与经典最小二乘法

Kalman Filter and Classical Least-Squares

在卡尔曼滤波的应用中若将时间因素固定,则卡尔曼滤波退化为经典最小二乘法。在通常情况下必须进行迭代计算,计算过程比经典最小二乘法复杂,但解的精度不会有任何改善。

In the application of Kalman filtering, in case the system dynamics is kept constant, the Kalman filter becomes classical least-squares. Iteration is necessary in most cases. However,the calculation procedure has not proved to be promising in that the complexity in calculation and does not produce an improvement in the precision.