A distributed minimum variance estimator for sensor networks
2008 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 26, no 4, 609-621 p.Article in journal (Refereed) Published
A distributed estimation algorithm for sensor networks is proposed. A noisy time-varying signal is jointly tracked by a network of sensor nodes, in which each node computes its estimate as a weighted sum of its own and its neighbors' measurements and estimates. The weights are adaptively updated to minimize the variance of the estimation error. Both estimation and the parameter optimization is distributed; no central coordination of the nodes is required. An upper bound of the error variance in each node is derived. This bound decreases with the number of neighboring nodes. The estimation properties of the algorithm are illustrated via computer simulations, which are intended to compare our estimator performance with distributed schemes that were proposed previously in the literature. The results of the paper allow to trading-off communication constraints, computing efforts and estimation quality for a class of distributed filtering problems.
Place, publisher, year, edition, pages
2008. Vol. 26, no 4, 609-621 p.
distributed estimation, sensor networks, convex optimization, parallel, and distributed computation, in-network processing, cooperative, communication
IdentifiersURN: urn:nbn:se:kth:diva-17478DOI: 10.1109/jsac.2008.080504ISI: 000255317700004ScopusID: 2-s2.0-43349105673OAI: oai:DiVA.org:kth-17478DiVA: diva2:335522
QC 201005252010-08-052010-08-052012-03-20Bibliographically approved