[en] This paper considerably improves the well-known Distributed Kalman Filter (DKF) algorithm by Olfati-Saber (2007) by introducing a novel decentralised consensus value computation scheme, using only local observations of sensors. It has been shown that the state estimates obtained in [8] and [9] approaches those of the Central Kalman Filter (CKF) asymptotically. However, the convergence to the CKF can sometimes be too slow. This paper proposes an algorithm that enables every node in a sensor network to compute the global average consensus matrix of measurement noise covariance in minimum time without accessing global information. Compared with the algorithm in [8], our theoretical analysis and simulation results show that the new algorithm can offer improved performance in terms of time taken for the state estimates to converge to that of the CKF.
Disciplines :
Ingénierie, informatique & technologie: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
Thia, Jerry
Yuan, Ye
Shi, Ling
GONCALVES, Jorge ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Langue du document :
Anglais
Titre :
Distributed Kalman Filter with minimum-time covariance computation
Date de publication/diffusion :
2013
Nom de la manifestation :
IEEE 52nd Annual Conference on Decision and Control
Lieu de la manifestation :
Florence, Italie
Date de la manifestation :
December 10-13, 2013
Titre de l'ouvrage principal :
The proceedings of the IEEE 52nd Annual Conference on Decision and Control
Z. Wang, D. Gu, "Cooperative Target Tracking Control of Multiple Robots", Industrial Electronics, IEEE Transactions on, On page(s): 3232-3240 Volume: 59, Issue: 8, Aug. 2012.
A. Esna Ashari, A. Y. Kibangou, and F. Garin, "Distributed input and state estimation for linear discrete-time systems", in Proceedings of 51st IEEE Conference on Decision and Control, 2012.
P. Maestre Torreblanca, P. Giselsson, A. Rantzer, "Distributed Receding Horizon Kalman Filter", in Proceedings of 50th IEEE Conference on Decision and Control, 2011.
Olfati-Saber, R., Jalalkamali, P., "Coupled Distributed Estimation and Control for Mobile Sensor Networks", Automatic Control, IEEE Transactions on, On page(s): 2609-2614 Volume: 57, Issue: 10, Oct. 2012.
Petitti, A., Di Paola, D., Rizzo, A., Cicirelli, G., "Distributed target tracking for sensor networks with only local communication", Control & Automation (MED), 2011 19th Mediterranean Conference on, On page(s): 662-667.
B. Song, A. T. Kamal, C. Soto, A. K. Roy-Chowdhury, and J. A. Farrell, "Tracking and Activity Recognition Through Consensus in Distributed Camera Networks, " IEEE Transactions on Image Processing, vol. 19, no. 10, pp. 2564-2579, 2010.
B. D. O Anderson and J. B. Moore. Optimal Filtering, Prentice-Hall. Englewood Cliffs. NJ., 1979.
R. Olfati-Saber, "Distributed Kalman filter with embedded consensus filters", 44th IEEE Conference on Decision and Control, 2005 and 2005 European Control Conference (CDC-ECC'05), pages 8179- 8184, Dec. 2005.
R. Olfati-Saber, "Distributed Kalman filtering for sensor networks, " in Proceedings of 46th IEEE Conference on Decision and Control, 2007, pp. 5492-5498.
Y. Yuan, G. Stan, L. Shi, M. Barahona and J. Goncalves, "Decentralised minimum time consensus, " Automatica, 2013.
R. Olfati-Saber and R. M. Murray, "Consensus problems in networks of agents with switching topology and time-delays, " IEEE Transactions on Automatic Control, 2004.
Olfati-Saber, R.; Fax, J.A.; Murray, R.M., "Consensus and Cooperation in Networked Multi-Agent Systems, " Proceedings of the IEEE, vol.95, no.1, pp.215, 233, Jan. 2007.
R. Olfati-Saber and J. S. Shamma. "Consensus filters for sensor networks and distributed sensor fusion", in Proceedings of the 44th Conference on Decision and Control, 2005.
