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Distributed detection with non-identical wireless sensors for industrial applications
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics. School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Sweden.ORCID iD: 0000-0001-8387-3779
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.ORCID iD: 0000-0001-5429-7223
School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Sweden.
2019 (English)In: Proceedings of the IEEE International Conference on Industrial Technology, IEEE, 2019, p. 1403-1408Conference paper, Published paper (Refereed)
Abstract [en]

There has been very little exploration when it comes to design distributed detection techniques and data fusion rules with non-identical sensors. This concept can be utilized in many possible applications within industrial automation, surveillance and safety. Here, for a global event, some of the sensors/detectors in the network can observe the full set of the hypotheses, whereas the remaining sensors infer more than one hypotheses as a single hypothesis. The local decisions are sent to the decision fusion center (DFC) over a multiple access wireless channel. In this paper, a fusion rule based on minimization of variance of the local mis-detection is proposed. The presence of sensors with limited detection capabilities is found to have a positive impact on the overall system performance, both in terms of probability of detection and transmit power consumption. Additionally, when the DFC is equipped with a large antenna array, the overall transmit power consumption can be reduced without sacrificing the detection performance. 

Place, publisher, year, edition, pages
IEEE, 2019. p. 1403-1408
Keywords [en]
Large antenna array, Mac fusion rule, Multiple hypotheses, Non-identical local detectors, Wireless sensor network, Accident prevention, Antenna arrays, Data fusion, Electric power utilization, Detection performance, Distributed detection, Fusion rule, Industrial automation, Large antennas, Multiple hypothesis, Non-identical, Probability of detection, Wireless sensor networks
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-30587DOI: 10.1109/ICIT.2019.8755012ISI: 000490548300221Scopus ID: 2-s2.0-85069036657ISBN: 978-1-5386-6376-9 (electronic)OAI: oai:DiVA.org:hig-30587DiVA, id: diva2:1345636
Conference
2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne; Australia; 13-15 February 2019
Available from: 2019-08-26 Created: 2019-08-26 Last updated: 2019-11-29Bibliographically approved

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Panigrahi, Smruti RanjanBjörsell, Niclas

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