Comparing of Target-Tracking Performances of EKF,UKF and PF
Yiming Pi · Radar Science and Technology · 2007
Nonlinear target-tracking methods have been widely researched and used in radar system. Extended Kalman filter(EKF) based on local linearization of KF, is easy to realize and has good performance in Gaussian and mild nonlinear environment. Unscented KF(UKF) utilizes a set of definite samplings to approximate posterior probability density function, while particle filter(PF) uses random particles. Hence, UKF is suitable for any nonlinear environment but Gaussian environment, but PF plays good act in any nonlinear and non-Gaussian environment. By simulation experiments, their performances are compared. The results prove the tracking performance of PF is much better than ones of EKF and UKF in complex environment, but computation of PF is much larger than ones of EKF and UKF.