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Distributed detection with non-identical wireless sensors for industrial applications
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.2019.8755012Scopus 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: 2019-08-26Bibliographically approved

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Panigrahi, Smruti RanjanBjörsell, Niclas

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