广义卡尔曼滤波递推公式的证明

Deductive proof of generalized kalman filter recursive formula

卡尔曼滤波方法是一种应用广泛的估值方法,但其要求系统数学模型已知。而广义卡尔曼滤波与卡尔曼滤波相比并不需要系统数学模型已知,具有更强的现实意义。在广义卡尔曼滤波方法的状态模型和测量模型的基础上讨论了其递推公式的证明问题。最后通过广义卡尔曼滤波与经典卡尔曼滤波仿真曲线的比较,验证了广义卡尔曼滤波的有效性。

The Kalman filter is widely used in many estimation fields, it depends on the given system model. The generalized Kalman filter is a method which is based on the unknown model system. Its significance is obvious. In this paper, based on the signal model and measure model, we deduced the recursive formula.. At Last, the simulation curves were completed by the Kalman filter and generalized Kalman filter. By comparison of two curves , the effect of the generalized Kalman filter is shown evident.