Title :
Algorithm of maneuvering target tracking for video based on UKF and IMM
Author :
Xu Ha Ning ; Xiao Hui
Author_Institution :
School of Nuclear Engineering and Technology, East China Institute of Technology, Fuzhou, 344000, China
Abstract :
For tracking and measuring maneuvering target for video image, Extended Kalman filter (EKF) based on local linearization of KF is easy to realize, but only has performance in Gaussian and mild nonlinear environment. An algorithm based on Unscented Kalman Filter (UKF) and Interaction Multiple Model (IMM) is proposed for maneuvering target tracking in complex nonlinearity environment or tracking small object in video image. The simulation results show that the tracking performance of UKF and IMM is much better than EKF in complex nonlinearity environment, and the third order tracking precision can be achieved.
Keywords :
Acceleration; Image segmentation; Extended Kalman Filter; Nonlinearity Prediction; Unscented Kalman Filter;
Conference_Titel :
Conference Anthology, IEEE
Conference_Location :
China
DOI :
10.1109/ANTHOLOGY.2013.6784905