Consensus based distributed change detection using generalized likelihood ratio methodology
2011 (English)In: 19th Mediterranean Conference on Control and Automation, MED 2011, 2011, 1170-1175 p.Conference paper (Refereed)
In this paper a novel distributed recursive algorithm based on the Generalized Likelihood Ratio methodology is proposed for real time change detection using sensor networks. The algorithm is based on a combination of recursively generated local statistics and a global consensus strategy, and does not require any fusion center, so that the state of any node can be tested w.r.t. a given common threshold. Two different problems are discussed: detection of an unknown change in the mean and in the variance of an observed random process. Performance of the algorithm for change detection in the mean is analyzed in the sense of a measure of the error with respect to the corresponding centralized algorithm. The analysis encompasses constant and randomly time varying matrices describing communications in the network. Simulation results illustrate characteristic properties of the algorithms.
Place, publisher, year, edition, pages
2011. 1170-1175 p.
Consensus; Convergence; Distributed change detection; Generalized Likelihood Ratio; Sensor networks
IdentifiersURN: urn:nbn:se:kth:diva-89725DOI: 10.1109/MED.2011.5983148ScopusID: 2-s2.0-80052369880ISBN: 978-145770125-2OAI: oai:DiVA.org:kth-89725DiVA: diva2:503443
Mediterranean Conference on Control and Automation, Corfu, Greece
QC 201202192012-02-152012-02-152012-02-19Bibliographically approved