Multi-sensor optimal information fusion Kalman filter
Automatica (Journal of IFAC)
Optimal linear estimation fusion .I. Unified fusion rules
IEEE Transactions on Information Theory
Brief paper: Hybrid method for a general optimal sensor scheduling problem in discrete time
Automatica (Journal of IFAC)
H∞information fusion filtering for discrete-time systems with time-delay sensors
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Optimal fusion reduced-order Kalman estimators for discrete-time stochastic singular systems
Control and Intelligent Systems
| Hi-index | 22.15 |
Based on the optimal fusion criterion in the linear minimum variance sense, a distributed optimal fusion fixed-lag Kalman smoother with a three-layer fusion structure is given for the discrete time-varying linear stochastic control systems with multiple sensors and correlated noises. Its components are estimated by scalar weighting fusion, respectively. It only requires in parallel a series of computations of the weighted scalars, and avoids the computations of the weighted matrices, so that the computational burden can obviously be reduced. Further, the steady-state fusion smoother is also given for the discrete time-invariant linear stochastic control systems. The scalar weights can be obtained by fusing once after all local estimations reach steady state. It can reduce the online computational burden. Also, the computation formulas of smoothing error cross-covariance matrices are given. Two simulation examples show the performance.