Student's t-distribution is utilized to derive a novel method for event detection in wireless sensor networks. Numerical analysis is used to show that under the same conditions, the proposed event detection method is comparable to likelihood ratio-based detection method and that it significantly outperforms energy detection method in terms of detection performance. Moreover, the proposed method does not require perfect knowledge of noise variance to set up a decision threshold in terms of a false alarm probability as the likelihood ratio based detection and the energy detection do.
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