Descriptor Wiener state fuser
By the modem time series analysis method, based on the autoregressive moving average (ARMA) innovation model and white noise estimation theory, a new local descriptor Wiener state estimators are presented, and using the optimal fusion rule weighted by diagonal matrices, a distributed decoupled descriptor Wiener state fuser is presented for the linear discrete stochastic descriptor systems with multisensor. It realizes a decoupled fusion estimation for state components. The descriptor Wiener state fuser is obtained by weighting the local Wiener state estimators. In order to compute the optimal weights, the formulas of computing the cross-covariances among local estimation errors are presented. It can handle the fused filtering, smoothing, and prediction problems in a unified framework. Its accuracy is higher than that of each local estimator. A Monte Carlo simulation example shows its effectiveness.
Multisensor information fusion Weighted fusion Decoupled fusion Descriptor system Wiener state fuser White noise estimator Modern time series analysis method and ARMA innovation model
Chenjian Ran Zili Deng
Department of Automation, Heilongjiang University, Harbin 150080
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
2629-2634
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）