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A Consensus-Based distributed calibration algorithm for sensor networks
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2016 (English)In: Serbian Journal of Electrical Engineering, ISSN 1451-4869, Vol. 13, no 1, 111-132 p.Article in journal (Refereed) Published
Abstract [en]

In this paper a novel distributed algorithm for blind macro-calibration in sensor networks based on consensus is proposed. The algorithm is formulated as a set of gradient-type recursions for estimating parameters of sensor calibration functions, starting from local criteria defined as weighted sums of mean square differences between the outputs of neighboring sensors. It is proved that the algorithm achieves asymptotic agreement for sensor gains and offsets in the mean square sense and with probability one. In the case of additive measurement noise, additive inter-agent communication noise and communication outages, a modification of the original algorithm is proposed. It is proved using stochastic approximation arguments that the modified algorithm achieves asymptotic consensus for sensor gains and offsets in the mean square sense and with probability one. Special attention is paid to the situation when one sensor is selected as a reference. Illustrative simulation examples are provided.

Place, publisher, year, edition, pages
University of Kragujevac, Faculty of Science , 2016. Vol. 13, no 1, 111-132 p.
Keyword [en]
Calibration, Consensus, Convergence, Sensor networks, Stochastic approximation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-216834DOI: 10.2298/SJEE1601111SScopus ID: 2-s2.0-85018881385OAI: oai:DiVA.org:kth-216834DiVA: diva2:1161247
Note

Export Date: 24 October 2017; Article. QC 20171129

Available from: 2017-11-29 Created: 2017-11-29 Last updated: 2017-11-29Bibliographically approved

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Johansson, Karl H.

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  • apa
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  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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