Consensus based distributed change detection using Generalized Likelihood Ratio methodology
2012 (English)In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 92, no 7, 1715-1728 p.Article in journal (Refereed) Published
In this paper a novel distributed algorithm derived from the Generalized Likelihood Ratio 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. The problem of detection of an unknown change in the mean of an observed random process is discussed and the performance of the algorithm is analyzed in the sense of a measure of the error with respect to the corresponding centralized algorithm. The analysis encompasses asymmetric constant and randomly time varying matrices describing communications in the network, as well as constant and time varying forgetting factors in the underlying recursions. An analogous algorithm for detection of an unknown change in the variance is also proposed. Simulation results illustrate characteristic properties of the algorithms including detection performance in terms of detection delay and false alarm rate. They also show that the theoretical analysis connected to the problem of detecting change in the mean can be extended to the problem of detecting change in the variance.
Place, publisher, year, edition, pages
2012. Vol. 92, no 7, 1715-1728 p.
Sensor networks, Distributed change detection, Generalized Likelihood Ratio, Consensus, Convergence
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-93631DOI: 10.1016/j.sigpro.2012.01.007ISI: 000301694100017ScopusID: 2-s2.0-84857452366OAI: oai:DiVA.org:kth-93631DiVA: diva2:517217
FunderICT - The Next Generation
QC 201204232012-04-232012-04-232013-04-11Bibliographically approved