A New Cubature Kalman Filter Improved by Backward Iterative Algorithm
Wu Bo, Liu Pengyuan · 2015
In order to solve the problem of nonlinear maneuvering target tracking, a new cubature kalman filter (CKF) with constant acceleration model was researched. According to simulation result, CKF presented a problem of excessive delay when tracking maneuvering targets with fierce change on acceleration. In order to solve this problem, a backward iterative algorithm that amend the last state estimation with the predicted current state was applied in CKF (BI-CKF). By the end of this paper, a typical target model with turning maneuvering was applied to CKF and BI-CKF, the effect of the two algorithm were compared. The simulation results show that BI-CKF algorithm was better than CKF algorithm at dynamic characteristic.