Title :
An improvement on the iterated Kalman filter
Author :
Niu Xin-liang ; Zhao Guo-qing ; Liu Yuan-hua ; Chang Hong
Author_Institution :
Res. Inst. of ECM, Xidian Univ., Xi´an
Abstract :
An improved iterated Kalman filter (IKF) is proposed to reduce the sensitivity of the filter to the initial estimate error. According to the essence of the IKF, i.e., the Gauss-Newton method is used to approximate a maximum likelihood estimate, a new update method is obtained. Simulations show that the improved IKF has better performance than the IKF when the initial estimate error is large.
Keywords :
Gaussian processes; Kalman filters; Newton method; iterative methods; maximum likelihood estimation; Gauss-Newton method; iterated Kalman filter; maximum likelihood estimate; Gauss-Newton method; Kalman filter; improvement; iterated method; maximum likelihood estimate;
Conference_Titel :
Radar Conference, 2009 IET International
Conference_Location :
Guilin
Print_ISBN :
978-1-84919-010-7
