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Distributed Blind Calibration in Lossy Sensor Networks via Output Synchronization
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2015 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 60, no 12, 3257-3262 p.Article in journal (Refereed) Published
Abstract [en]

A novel distributed algorithm for blind macrocalibration of large sensor networks is introduced. The algorithm is in the form of a system of gradient-type recursions for estimating parameters of local sensor calibration functions. The method does not require any fusion center. The convergence analysis is based on diagonal dominance of the dynamical systems with block matrices. It is proved that the asymptotic consensus is achieved for all the equivalent sensor gains and offsets (in the mean square sense and with probability one) in lossy sensor networks with possible communication outages and additive communication noise. An illustrative simulation example is provided.

Place, publisher, year, edition, pages
IEEE Press, 2015. Vol. 60, no 12, 3257-3262 p.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-165966DOI: 10.1109/TAC.2015.2426272ISI: 000367284600010Scopus ID: 2-s2.0-84960877204OAI: oai:DiVA.org:kth-165966DiVA: diva2:809215
Funder
Knut and Alice Wallenberg FoundationSwedish Research Council
Note

QC 20160209

Available from: 2015-04-30 Created: 2015-04-30 Last updated: 2017-12-04Bibliographically approved

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Johansson, Karl

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