Fusion of Threshold Rules for Target Detection in Wireless Sensor Networks

Authors

Michelle Zhu, Montclair State UniversityFollow
Song Ding, University of Memphis
Qishi Wu, New Jersey Institute of TechnologyFollow
Richard R. Brooks, Clemson UniversityFollow
Nageswara S.V. Rao, Oak Ridge National LaboratoryFollow
S. Sitharama Iyengar, Florida International UniversityFollow

Document Type

Article

Publication Date

2-1-2010

Abstract

We propose a binary decision fusion rule that reaches a global decision on the presence of a target by integrating local decisions made by multiple sensors. Without requiring a priori probability of target presence, the fusion threshold bounds derived using Chebyshev's inequality ensure a higher hit rate and lower false alarm rate compared to the weighted averages of individual sensors. The Monte Carlo-based simulation results show that the proposed approach significantly improves target detection performance, and can also be used to guide the actual threshold selection in practical sensor network implementation under certain error rate constraints.

DOI

10.1145/1689239.1689248

Montclair State University Digital Commons Citation

Zhu, Michelle; Ding, Song; Wu, Qishi; Brooks, Richard R.; Rao, Nageswara S.V.; and Iyengar, S. Sitharama, "Fusion of Threshold Rules for Target Detection in Wireless Sensor Networks" (2010). Department of Computer Science Faculty Scholarship and Creative Works. 299.
https://digitalcommons.montclair.edu/compusci-facpubs/299