A modified EKF algorithm for GPS point dynamic positioning and velocity measurement

Extended Kalman Filter (EKF) algorithm is widely used in GPS positioning and velocity measurement. As for EKF algorithm, the approximate initial position of the receiver is indispensable; otherwise the time consumption of the first positioning is too high because of the filter's low convergence rate. A modified EKF algorithm named delayed update EKF (DU-EKF) algorithm for GPS point dynamic positioning and velocity measurement is proposed in this paper, which can speed up the convergence rate of the filter without the receiver's approximate initial position. Furthermore, it can improve the accuracy of positioning and velocity measurement. Three kinds of algorithms are used in the simulation of this paper to compare with the modified EKF algorithm: iterative least square (ILS) algorithm, EKF algorithm with the Zero initial state vector (ZEKF) and EKF algorithm with the initial state vector which is Close to the actual situation (CEKF).