/kloc-At the beginning of the 9th century, the German mathematician C.F. Gauss put forward the least square estimation, that is, the least square error estimation. From 1920s to 1930s, British statistician R.A. Fisher systematically established the classical estimation theory. In 194 1, the Soviet scientist A.H. Colmo Golov first discussed the prediction problem in discrete time, and in 1942, he deduced the continuous-time filtering. They all use statistical methods to solve the optimal linear filtering problem related to state estimation, which lays the foundation for modern estimation theory. In the early 1960s, R.E. Kalman and others developed Wiener theory, introduced the state variable method into the filtering theory, and expressed the filtering problem by time-domain differential equations, and obtained a recursive filtering algorithm suitable for computer solution and real-time processing, called Kalman filtering, which made the estimation theory applied in many fields. In the early 1980s, the development of optical fiber communication and lidar promoted the development of quantum detection and estimation theory.