Design of UKF with correlative noises based on minimum mean square error estimation

Xiao Xu Wang, Lin Zhao, Quan Pan, Quan Xi Xia, Wei Hong

科研成果: 期刊稿件文章同行评审

13 引用 (Scopus)

摘要

Unscented Kalman filter (UKF) for a class of nonlinear discrete-time systems with correlative noises is designed to overcome the limitation that the conventional UKF calls for system noise and measurement to be irrelative. Recursive filtering equations of UKF with correlative noises are given based on minimum mean square error estimation and orthogonal transformation, and unscented transformation (UT) is applied to calculation the posterior distribution of the nonlinear system state. The proposed UKF solves the problem of nonlinear filtering failure in conventional UKF when system noise is correlated with measurement noise, so it expands the applications of the conventional UKF. A simulation example shows the effectiveness of the designed UKF.

源语言英语
页(从-至)1393-1398
页数6
期刊Kongzhi yu Juece/Control and Decision
25
9
出版状态已出版 - 9月 2010

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