Self-tuning measurement fusion white noise deconvolution estimator with correlated noises

作     者：Xiaojun Sun Zili Deng 

作者机构：Department of Automation Heilongjiang University Harbin 150080 R R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2010年第21卷第4期

页      面：666-674页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 071102[理学-系统分析与集成] 0711[理学-系统科学] 0810[工学-信息与通信工程] 081104[工学-模式识别与智能系统] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 0811[工学-控制科学与工程] 081103[工学-系统工程] 

基　　金：supported by the National Natural Science Foundation of China(60874063) Science and Technology Research Foundation of Heilongjiang Education Department(11551355) Key Laboratory of Electronics Engineering,College of Heilongjiang Province(DZZD20105) 

主　　题：multisensor information fusion measurement fusion self-tuning fuser white noise deconvolution asymptotic global optimality Kalman filtering convergence. 

摘      要：For the multisensor linear discrete time-invariant stochastic systems with correlated noises and unknown noise statistics,an on-line noise statistics estimator is presented by using the correlation *** it into the steady-state Riccati equation,the self-tuning Riccati equation is *** the Kalman filtering method,based on the self-tuning Riccati equation,a self-tuning weighted measurement fusion white noise deconvolution estimator is *** the dynamic error system analysis（DESA） method,it is proved that the self-tuning fusion white noise deconvolution estimator converges to the optimal fusion steadystate white noise deconvolution estimator in a realization,so that it has the asymptotic global optimality.A simulation example for Bernoulli-Gaussian input white noise shows its effectiveness.