Kalman Filter是一个高效的递归滤波器，它可以实现从一系列的噪声测量中，估 计动态系统的状态。广泛应用于包含Radar、计算机视觉在内的等工程应用领域，在控制理论和控制系统工程中也是一个非常重要的课题。连同线性均方规划，卡尔曼滤波器可以用于解决LQG(Linear-quadratic-Gaussian control)问题。卡尔曼滤波器，线性均方归化及线性均方高斯控制器，是大部分控制领域基础难题的主要解决途径。(Kalman Filter is an efficient recursive filter that can estimate the state of a dynamic system from a range of noise measurements. It is widely used in engineering applications such as Radar and computer vision, and it is also a very important subject in control theory and control system engineering. Along with linear mean square programming, the Calman filter can be used to solve the LQG (Linear-quadratic-Gaussian, control) problem. Calman filter, linear mean square adaptation and linear mean square Gauss controller are the main solutions to the basic problems in most control fields.)