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doi:10.1016/j.inffus.2005.06.003 
Copyright © 2005 Elsevier B.V. All rights reserved.
Received 9 November 2004;
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Abstract
A distributed detection and decision fusion scheme is proposed for a wireless sensor network (WSN) consisting of a large number of sensors. At the fusion center, the total number of detections reported by local sensors are employed for hypothesis testing. Based on the assumption that the received signal power decays as the distance from the target increases, system level detection performance measures, namely probabilities of detection and false alarm, are derived analytically through approximation by using the central limit theorem (CLT). If the number of sensors is sufficiently large, the proposed fusion rule can provide very good system level detection performance, in the absence of the knowledge of local sensors’ performances and at low signal to noise ratio (SNR). It is shown that for all the different system parameters we have explored, this fusion rule is equivalent to the optimal fusion rule, which requires much more prior information. To achieve a better system level detection performance, the local sensor level decision threshold should be designed optimally. Numerical methods are employed to find the optimal local sensor level threshold for different sets of system parameters. Guidelines on selecting the optimal local sensor level decision threshold are also provided.
Keywords: Wireless sensor networks; Distributed detection; Decision fusion; Signal attenuation model
Article Outline
- 1. Introduction
- 2. Problem formulation
- 3. Decision fusion
- 4. Performance analysis
- 4.1. Calculation of Pfa
- 4.2. Calculation of Pd
- 4.3. Evaluation of system performance via simulations
- 4.4. System performance vs. number of sensors
- 4.5. Optimality of the decision fusion rule
- 5. Determination of the threshold for local sensors
- 6. Conclusions and discussion
- Acknowledgements
- References
