Open AccessDistributed asynchronous consensus‐based algorithm for blind calibration of sensor networks with autonomous gain correction
Author(s) -
Stanković Maja
Publication year - 2018
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2018.5417
Subject(s) - recursion (computer science) , asynchronous communication , offset (computer science) , algorithm , computer science , convergence (economics) , wireless sensor network , control theory (sociology) , stochastic approximation , mathematics , artificial intelligence , computer network , control (management) , economics , programming language , economic growth
In this study, a new algorithm is proposed for distributed asynchronous consensus‐based blind calibration of sensor networks with noisy communications and measurements. The algorithm consists of one autonomous recursion of the instrumental variable type for gain correction and one additional recursion of gradient type for offset correction based on the corrected gains. It is proved using asynchronous stochastic approximation arguments that the algorithm achieves asymptotic consensus with regard to both the corrected sensor gains and offsets in the mean square sense and with probability one. The algorithm is more flexible than the existing similar algorithms for blind macro‐calibration and provides a superior convergence rate, especially when used in networks with one fixed reference node. Simulation results confirm the main theoretical statements.