DocumentCode :
1986527
Title :
Distributed Kalman Filter using fast polynomial filter
Author :
Abdelgawad, A. ; Bayoumi, M.
Author_Institution :
Center for Adv. Comput. Studies, Univ. of Louisiana at Lafayette, Lafayette, LA, USA
fYear :
2011
fDate :
15-18 May 2011
Firstpage :
385
Lastpage :
389
Abstract :
Distributed estimation algorithms have received a lot of attention in the past few years, particularly in the fusion framework of Wireless Sensor Network (WSN). Distributed Kalman Filter (DKF) for WSN is one of the most fundamental distributed estimation algorithms for scalable wireless sensor fusion. In the literature, most of DKF methods rely on consensus filter algorithms. The convergence rate of such distributed consensus algorithms is slow and typically depends on the network topology and the weights given to the edges between neighboring sensors. In this paper, we propose a DKF based on polynomial filter to accelerate the distributed average consensus in the static network topologies. The main contribution of the proposed methodology is to apply a polynomial filter on the network matrix that will shape its spectrum in order to increase the convergence rate by minimizing its second largest eigenvalue. The simulation results show that the proposed algorithm increases the convergence rate of DKF by 4 times compared to the standard iteration. The proposed methodology can contribute in the real time WSN´s applications.
Keywords :
Kalman filters; sensor fusion; telecommunication network topology; wireless sensor networks; distributed Kalman filter; distributed estimation algorithms; fast polynomial filter; network topology; sensor fusion; wireless sensor network; Convergence; Filtering algorithms; Kalman filters; Network topology; Noise; Polynomials; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (ISCAS), 2011 IEEE International Symposium on
Conference_Location :
Rio de Janeiro
ISSN :
0271-4302
Print_ISBN :
978-1-4244-9473-6
Electronic_ISBN :
0271-4302
Type :
conf
DOI :
10.1109/ISCAS.2011.5937583
Filename :
5937583
Link To Document :
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