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Approximate distributed Kalman filtering in sensor networks with quantifiable performance

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3 Author(s)
Spanos, D.P. ; Control & Dynamical Syst., California Inst. of Technol., Pasadena, CA, USA ; Olfati-Saber, R. ; Murray, R.M.

We analyze the performance of an approximate distributed Kalman filter proposed in recent work on distributed coordination. This approach to distributed estimation is novel in that it admits a systematic analysis of its performance as various network quantities such as connection density, topology, and bandwidth are varied. Our main contribution is a frequency-domain characterization of the distributed estimator's steady-state performance; this is quantified in terms of a special matrix associated with the connection topology called the graph Laplacian, and also the rate of message exchange between immediate neighbors in the communication network.

Published in:

Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on

Date of Conference:

15 April 2005