Decision Fusion Supported by Correlated Auxiliary Data in Wireless Sensor Networks

Yu Bao, Xiexing Miao, Yanqun Zhang and Aijuan Zhang

International Journal of Distributed Sensor Networks, 2014, vol. 10, issue 12, 319093

Abstract: Leakage monitoring is different from sudden incident monitoring because most of the leakage cases involve a slow process that lasts for a long time. During this case monitoring, sensors suffer long exposure to erosion and may lead to errors in the measurement. An approach is proposed to make use of a soft-decision fusion approach according to the Neyman-Pearson criterion to accumulate auxiliary data from multiple sensors. The proposed method optimizes the soft-function and adjusts its range of sensors, which provide auxiliary data to improve the fusion center confidence for making a global decision. The new method encompasses the collection of useful data and weights and combines them according to the corresponding confidence level to make a global decision. In the simulation case of Rayleigh-distributed observations of leakage monitoring, it is proved that the proposed method has a good performance.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2014/319093 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:10:y:2014:i:12:p:319093

DOI: 10.1155/2014/319093

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().