Distributed calibration for sensor networks under communication errors and measurement noise
2012 (English)In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC), IEEE conference proceedings, 2012, 1380-1385 p.Conference paper (Refereed)
In this paper a new distributed calibration algorithm based on consensus is proposed for sensor networks. The algorithm is basically formulated as a set of stochastic gradient type recursions for estimating parameters of local sensor calibration functions, starting from local criteria defined as weighted sums of mean square errors between the outputs of neighboring sensors. It is proved that the proposed algorithm provides asymptotic consensus in the space of the sensor gains and offsets. In the case of communication dropouts and additive communication and measurement noise, a modification of the instrumental variable type of the original calibration scheme is proposed. It is proved using stochastic approximation arguments that in this case the proposed algorithm achieves asymptotic consensus in the mean square sense and with probability one. Some illustrative simulation examples are provided.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2012. 1380-1385 p.
, IEEE Conference on Decision and Control. Proceedings, ISSN 0191-2216
Calibration, Convergence, Eigenvalues and eigenfunctions, Noise, Noise measurement, Random variables, Wireless sensor networks
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-111460DOI: 10.1109/CDC.2012.6426180ISI: 000327200401123ScopusID: 2-s2.0-84874271244ISBN: 978-1-4673-2064-1OAI: oai:DiVA.org:kth-111460DiVA: diva2:586443
51st IEEE Conference on Decision and Control, CDC 2012; Maui, HI; United States; 10 December 2012 through 13 December 2012
QC 201301162013-02-152013-01-112013-12-20Bibliographically approved