说明：  卡尔曼滤波从与被提取信号有关的量测量中通过算法估计出所需信号。卡尔曼滤波处理有几个特点：(1)卡尔曼滤波处理的对象是随机信号；(2)被处理信号无有用和干扰之分，滤波的目的是要估计出所有被处理信号；确切的说卡尔曼滤波应称作最优估计理论；就实现形式而言，卡尔曼滤波器实质上是一套由数字计算机实现的递推算法。量测量可看作卡尔曼滤波器的输入，估计值可看作输出
(Kalman filtering from the measurement of the quantity relating to the signal is extracted by the algorithm to estimate the desired signal. Kalman filtering process has several characteristics: (1) the object of processing of the Kalman filter is a random signal (2) no useful signal and the interference of the points to be processed, the purpose of the filter is to be estimated for all the signal to be processed exact Kalman filter called optimal estimation theory terms of the forms of the Kalman filter is essentially a digital computer recursive algorithm. Measurement can be regarded as the input for the Kalman filter, it is estimated that the output value can be regarded as)