Decoupled Wiener state fuser for descriptor systems
Chenjian RAN
Zili DENG
摘要：By the modem time series analysis method,based on the autoregressive moving average(ARMA)innovation models and white noise estimation theory,using the optimal fusion rule weighted by diagonal matrices.a distributed descriptor Wiener state fuser IS presented by weighting the local Wiener state estimators for the linear discrete stochastic descriptor systems with multisensor.It realizes a decoupled fusion estimation for state components.In order to compute We optimal weights,the formulas of computing the cross-covariances among local estimation errors are presented based on cross-covariances among the local lnnovation processes,input wite noise,and measurement white noises.It can handle the fused filtering,smoothing,and prediction problems in a unifled framework.Its accuracy is higher than that of each local estimator.A Monte Carlo simulation example shows its effectiveness and correctness.
机标关键词：autoregressive moving averageWiener state estimatorsMonte Carlo simulationdescriptor systemsnoise estimationanalysis methodoptimal fusiontime series
资助基金：This work was suppled by the National Natural Science Foundation of China(00874063)the Innonvation Scientific Research Fundation for Graduate Students of Heilongjiang Province(YJSCX2008.018HLJ)
论文发表日期：2008-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：7( 365-371 )
英文信息