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State estimation & self-localization using distributed Kalman filter & recursive expectation maximization algorithm in sensor networks

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3 Author(s)
Amirarfaei, F. ; Amirkabir Univ. of Tech, Tehran, Iran ; Ghafoorifard, H. ; Menhaj, M.B.

Knowing the fact that online expectation maximization is a well-known methodology for static parameters estimation in a general state-space model, this paper describes fully how a decentralized version of online EM algorithm can be implemented in a sensor network for the self-localization problem. This is done through the propagation of messages that are exchanged between neighboring nodes of network. The algorithms used for state/parameter estimation are performed in a fully collaborative manner. Comparing parameter estimation formulas of On-line EM algorithm with RML method easily shows the simplicity of the former, while the results are approximately the same for both.

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Date of Conference:

18-23 May 2009