Paper: A survey of design methods for failure detection in dynamic systems
Automatica (Journal of IFAC)
Correspondence item: An innovations approach to fault detection and diagnosis in dynamic systems
Automatica (Journal of IFAC)
Distributed optimal fusion steady-state Kalman filter for systems with coloured measurement noises
International Journal of Systems Science
Optimal fusion distributed filter for discrete multichannel ARMA signals
Control and Intelligent Systems
Distributed optimal component fusion deconvolution filtering
Signal Processing
Multisensor switching control strategy with fault tolerance guarantees
Automatica (Journal of IFAC)
Self-tuning decoupled information fusion Wiener state component filters and their convergence
Automatica (Journal of IFAC)
Multi-sensor optimal fusion fixed-interval Kalman smoothers
Information Fusion
Distributed fusion filter for systems with multiplicative noise
ISCGAV'09 Proceedings of the 9th WSEAS international conference on Signal processing, computational geometry and artificial vision
In-car positioning and navigation technologies: a survey
IEEE Transactions on Intelligent Transportation Systems
A novel interacting multiple model algorithm based on multi-sensor optimal information fusion rule
ACC'09 Proceedings of the 2009 conference on American Control Conference
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Self-tuning weighted measurement fusion Wiener filter and its convergence
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Correlated measurement fusion Kalman filters based on orthogonal transformation
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Distributed information fusion Kalman predictor for stochastic systems with uncertain observations
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Distributed fusion filter for time-delay systems with colored measurement noise
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
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
An optimal sequential filter for the linear system with correlated noises
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Average consensus based scalable robust filtering for sensor network
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Optimal fusion reduced-order Kalman estimators for discrete-time stochastic singular systems
Control and Intelligent Systems
Distributed fusion receding horizon filtering in linear stochastic systems
EURASIP Journal on Advances in Signal Processing
Derivation of centralized and distributed filters using covariance information
Computational Statistics & Data Analysis
Random weighting estimation for fusion of multi-dimensional position data
Information Sciences: an International Journal
Brief paper: Multisensor fusion fault tolerant control
Automatica (Journal of IFAC)
Sequential covariance intersection fusion Kalman filter
Information Sciences: an International Journal
State estimation with asynchronous multi-rate multi-smart sensors
Information Sciences: an International Journal
New approach to information fusion steady-state Kalman filtering
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Multi-rate distributed fusion estimation for sensor networks with packet losses
Automatica (Journal of IFAC)
Optimal sequential and distributed fusion for state estimation in cross-correlated noise
Automatica (Journal of IFAC)
International Journal of Sensor Networks
Hi-index | 22.16 |
This paper presents a new multi-sensor optimal information fusion criterion weighted by matrices in the linear minimum variance sense, it is equivalent to the maximum likelihood fusion criterion under the assumption of normal distribution. Based on this optimal fusion criterion, a general multi-sensor optimal information fusion decentralized Kalman filter with a two-layer fusion structure is given for discrete time linear stochastic control systems with multiple sensors and correlated noises. The first fusion layer has a netted parallel structure to determine the cross covariance between every pair of faultless sensors at each time step. The second fusion layer is the fusion center that determines the optimal fusion matrix weights and obtains the optimal fusion filter. Comparing it with the centralized filter, the result shows that the computational burden is reduced, and the precision of the fusion filter is lower than that of the centralized filter when all sensors are faultless, but the fusion filter has fault tolerance and robustness properties when some sensors are faulty. Further, the precision of the fusion filter is higher than that of each local filter. Applying it to a radar tracking system with three sensors demonstrates its effectiveness.