Kalman Filter Technology And Its Application In Target Tracking

Kalman filter is a data-processing method which is based on linear unbiased minimal variance estimate principle. By virtue of a systematic state estimate and current observation, a new state estimation is obtained by introducing a concept of state space.Firstly, the paper presents the development of Kalman filter, and discusses the problems of non-linear Kalman filter and adaptive Kalman filter. Several new filter methods, such as particle filter and Unscented filter are introduced. Some research shows that different application need different adaptive Kalman filter scheme.The classical Kalman filter and extended Kalman filter are introduced in the second chapter; the extended Kalman filter is a foundation for maneuvering target tracking.The problem of tracking satellite orbit is discussed in the next. The position and velocity of satellite are obtained using extended Kalman filter deriving from information of Radar measurements, then the relation of estimation precision of position and velocity of satellite and system accuracy of the radar is also given.Finally, the paper discusses the adaptive estimation of trajectory coefficient for reentry aircraft, one adaptive scheme is that the trajectory coefficient and position and velocity of reentry aircraft are unknown at the same time, the simulation results show that the adaptive scheme is feasible.