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Approximate distributed Kalman filtering in sensor networks with quantifiable performance

Spanos, Demetri P. and Olfati-Saber, Reza and Murray, Richard M. (2005) Approximate distributed Kalman filtering in sensor networks with quantifiable performance. In: Fourth International Symposium on Information Processing in Sensor Networks, 2005 (IPSN 2005). IEEE , Los Alamitos, CA, pp. 133-139. ISBN 0-7803-9201-9.

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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.

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Murray, Richard M.0000-0002-5785-7481
Additional Information:© Copyright 2005 IEEE. Reprinted with permission.
Subject Keywords:approximate distributed Kalman filter; connection topology; distributed coordination; frequency-domain characterization graph Laplacian matrix; message exchange; quantifiable performance; sensor network; steady-state performance
Record Number:CaltechAUTHORS:SPAipsn05
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:5148
Deposited By: Archive Administrator
Deposited On:03 Oct 2006
Last Modified:08 Nov 2021 20:23

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