Time-varying optimal distributed fusion white noise deconvolution estimator

作     者：Xiaojun SUN Guangming YAN 

作者机构：College of Electrical Engineering Heilongjiang University Harbin150080 China 

出 版 物：《Frontiers of Electrical and Electronic Engineering in China》 (中国电气与电子工程前沿（英文版）)

年 卷 期：2012年第7卷第3期

页      面：318-325页

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0835[工学-软件工程] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 

基　　金：Acknowledgements This work was supported by the National Natural Science Foundation of China under Grant No. 61104209  Outstanding Youth Science Foundation of Heilongjiang University under Grant No. JCL201103  and Key Laboratory of Electronics Engineering  College of Heilongjiang Province  under Grant No. DZZD2010-5. The authors wish to thank the reviewers for their constructive comments 

主　　题：multisensor information fusion distributedfusion white noise deconvolution global optimality Kal-man filtering 

摘      要：White noise deconvolution has a wide range of applications including oil seismic exploration, communication, signal processing, and state estimation. Using the Kalman filtering method, the time-varying optimal dis- tributed fusion white noise deconvolution estimator is presented for the multisensor linear discrete time-varying systems. It is derived from the centralized fusion white noise deconvolution estimator so that it is identical to the centralized fuser, i.e., it has the global optimality. It is superior to the existing distributed fusion white noise estimators in the optimality and the complexity of computation. A Monte Carlo simulation for the Bemoulli- Gaussian input white noise shows the effectiveness of the proposed results.