State augmentation-based modified iterated extended Kalman filtering
Liu Meihong, Gao Shanfeng, Wei Li, Xie Bin · DOAJ (DOAJ: Directory of Open Access Journals) · 2020
This paper derives a state augmentation-based modified iterated extended Kalman filter(SMIEKF) by making use of the state augmentation technique, in which the state variables are directly augmented with the measurement noise. The improved performance is then demonstrated by a target tracking problem involving radar measurements of an atmospheric re-entry vehicle. Simulation results clearly show that the proposed filtering algorithm exhibits faster convergence rate and better estimate accuracy compared to the modified iterated extended Kalman filter(MIEKF) and traditional extended Kalman filter(EKF).