Abstract
The sensor fusion method 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 some 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 some subsystems fail or interconnections are broken. Furthermore, local Kalman filters can effectively reduce subsystems and measurement noises. Index terms - Sensor fusion, Kalman filtering, data communication, interconnected systems.
| Original language | English |
|---|---|
| Pages (from-to) | 7-9 |
| Number of pages | 3 |
| Journal | International Journal of Electrical, Electronics and Data Communication (IJEEDC) |
| Volume | 6 |
| Issue number | 7 |
| Publication status | Published - Jul 2018 |
Bibliographical note
International Journal of Electrical, Electronics and Data Communication (IJEEDC) is an Open Access International Journal for dissemination of the newest technologies and theoretical research in the area of Electrical ,Electronics and Communication Engineering , aiming at inspiring interdisciplinary research across academia and industry and contributing to the prosperity of modern societies. We publish manuscripts describing original research, with significant results based on experimental, theoretical and numerical work.Fingerprint
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Yuri Vershinin
- School of Future Transport Engineering - Assistant Professor Academic
Person: Teaching and Research