Name
Abstract | ||
|---|---|---|
Based on the optimal weighted fusion algorithms in the linear minimum variance sense, the optimal fusion fixed-interval Kalman smoothers are given for discrete time-varying linear stochastic control systems with multiple sensors and correlated noises, which have a three-layer fusion structure. The first and the second fusion layers both have netted parallel structures to determine the cross-covariance matrices of prediction and smoothing errors between any two-sensor subsystems, respectively. The third fusion layer is the fusion centre to determine the optimal weights and obtain the optimal fusion fixed-interval smoothers. Smoothing error cross-covariance matrix between any two-sensor subsystems is derived. Applying it to a tracking system with three-sensors shows the effectiveness. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.inffus.2006.07.001 | Information Fusion |
Keywords | Field | DocType |
fusion centre,optimal information fusion,tracking system,multi-sensor,optimal fusion fixed-interval smoothers,two-sensor subsystems,kalman smoothers,cross-covariance matrix,fusion layer,multi-sensor optimal fusion fixed-interval,smoothing error cross-covariance matrix,three-layer fusion structure,fixed-interval kalman smoother,optimal fusion fixed-interval kalman,optimal weighted fusion algorithm,optimal weight,cross-covariance,covariance matrix,stochastic control,discrete time,cross covariance,minimum variance | Minimum-variance unbiased estimator,Cross-covariance,Control theory,Matrix (mathematics),Fusion,Kalman filter,Sensor fusion,Smoothing,Mathematics,Stochastic control | Journal |
Volume | Issue | ISSN |
9 | 2 | Information Fusion |
Citations | PageRank | References |
8 | 0.64 | 6 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shu-Li Sun | 1 | 10 | 1.36 |