Fusion of threshold rules for target detection in wireless sensor networks

Journal Article · Mon Mar 01 00:00:00 EST 2010 · ACM Transactions on Sensor Networks

DOI:https://doi.org/10.1145/1689239.1689248· OSTI ID:982137

Zhu, Mengxia ^[1]; Ding, Shi-You ^[1]; Brooks, Richard R ^[1]; Wu, Qishi ^[1]; Rao, Nageswara S ^[1]

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1. ORNL

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.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
• DOE Contract Number: DE-AC05-00OR22725
• OSTI ID: 982137
• Journal Information: ACM Transactions on Sensor Networks, Vol. 6, Issue 2; ISSN 1550-4859
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICAL METHODS AND COMPUTING
SENSORS
DETECTION
PERFORMANCE
TARGETS
MONTE CARLO METHOD