NDLI: A data fusion algorithm for multisensor systems

Content Provider	IEEE Xplore Digital Library
Author	Vershinin, Y.A.
Copyright Year	2002
Description	Author affiliation: Sch. of Eng., Coventry Univ., UK (Vershinin, Y.A.)
Abstract	The new data fusion algorithm presented in this paper allows one to combine information from different sensors in continuous time. Continuous-time decentralized Kalman filters (DKF) are used as data fusion devices on local subsystems. Such a structure gives the flexibility for reconfiguration of a control system. New subsystems can easily be added without needing any redesign of the whole system. The system does not require a central processor and therefore, in the case of failure of local subsystems (each of which includes a local processor, sensors and actuators) the overall system will continue to work. The simulation results show that the performance of the overall system degrades gracefully even if the sensors of subsystems fail or interconnections are broken. Furthermore, local Kalman filters can effectively reduce subsystem and measurement noise.
Starting Page	341
Ending Page	345
File Size	294349
Page Count	5
File Format	PDF
ISBN	0972184414
DOI	10.1109/ICIF.2002.1021172
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-07-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Int. Soc. of Information Fusion
Subject Keyword	Multisensor systems Sensor systems Sensor fusion Feedback Noise measurement Noise reduction Control systems Equations Bayesian methods State estimation
Content Type	Text
Resource Type	Article

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