Fusion of Threshold Rules for Target Detection in Wireless Sensor Networks.

Autor:	Mengxia Zhu, Song Ding, Qishi Wu, Brooks, R. R., Rao, N. S. V., Iyengar, S. S.
Předmět:	BINARY number system COMPUTER arithmetic ARTIFICIAL intelligence COMPUTER software WIRELESS sensor networks MONTE Carlo method ERROR rates DATA corruption RECEIVER operating characteristic curves
Zdroj:	ACM Transactions on Sensor Networks; Feb2010, Vol. 6 Issue 2, p18-18:7, 7p, 1 Chart
Abstrakt:	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. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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