GLRT Based Anomaly Detection for Sensor Network Monitoring

Fouzi Harrou, Ying Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Proper operation of antenna arrays requires continuously monitoring their performances. When a fault occurs in an antenna array, the radiation pattern changes and can significantly deviate from the desired design performance specifications. In this paper, the problem of fault detection in linear antenna arrays is addressed within a statistical framework. Specifically, a statistical fault detection method based on the generalized likelihood ratio (GLR) principle is utilized for detecting potential faults in linear antenna arrays. The proposed method relies on detecting deviations in the radiation pattern of the monitored array with respect to a reference (fault-free) one. To assess the abilities of the GLR based fault detection method, three case studies involving different types of faults have been performed. The simulation results clearly illustrate the effectiveness of the GLR-based fault detection method in monitoring the performance of linear antenna arrays.
Original languageEnglish (US)
Title of host publication2015 IEEE Symposium Series on Computational Intelligence
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages398-403
Number of pages6
ISBN (Print)9781479975600
DOIs
StatePublished - Jan 11 2016

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