卡尔曼滤波由于其在求解时不需要贮存大量的观测数据，并且当得到新的观测数据时可随时算得新的参数滤波值，便于实时的处理观测结果，因此被越来越多的应用于动态数据处理中-Kalman filter because it does not require storage of large amounts of observational data in solving, and when to get new observational data can always be regarded as a new filter parameter values, live processing of observations, so it is increasingly used in dynamic data processing