Title :
Research on the estimation to unknown noise statistics Q and R of nonlinear time-varying system
Author :
CHEN, Rui ; Wei, Jinyu ; Zheng, Qingchun ; Bi, Ran ; Gu, Chengkui
Author_Institution :
Sch. of Manage., Tianjin Univ. of Technol., Tianjin
Abstract :
This paper presents a new method to estimate process noise covariances Q and observation noise covariances R of nonlinear time-varying system. Based on the analysis of key factor to estimate noise covariances Q and R for identification and prediction of nonlinear time-varying system using extended Kalman filter based on neural network. Then the paper extends the Mehra approach of noise statistics estimation of constant system to general nonlinear time-varying system based on covariances-matching techniques. The paper verified the effectiveness of the new method by identification and prediction results of two nonlinear time-varying systems at last.
Keywords :
Kalman filters; estimation theory; nonlinear systems; time-varying systems; constant system; covariances-matching techniques; extended Kalman filter; general nonlinear time-varying system; neural network; noise statistics estimation; observation noise covariances; process noise covariances; unknown noise statistics; Automation; Engineering management; Intelligent control; Neural networks; Paper technology; Radio access networks; Statistics; Systems engineering and theory; Technology management; Time varying systems; covariances-matching techniques; estimation; noise covariances Q and R; nonlinear time-varying system;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594348
