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Decision fusion using fuzzy threshold scheme for target detection in sensor networks

机译:基于模糊阈值方案的传感器网络目标融合决策融合

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Spectrum sensing is a fundamental surveillance task and is used to detect target signal. Energy detection is a popular spectrum sensing technique. But detection performance of energy detector deteriorates in low signal-to-noise ratio (SNR) conditions and under noise uncertainty. In this paper, we proposed an energy detector with fuzzy threshold scheme for spectrum sensing, in which each sensor node sends local decision to the fusion center depending on the region in which the observed energy lies. Fusion center then makes a final global decision by combining local decisions. Analysis and simulations show that the proposed fuzzy threshold scheme could improve the detect probability effectively under 'OR','AND' and 'K-out-of-N' fusion rules, and overcome the confused region problem. Monte Carlo Simulation results also show that proposed scheme achieves better detection performance and outperforms both conventional energy detector of both single and double threshold, respectively. (C) 2017 Elsevier B.V. All rights reserved.
机译:频谱感测是一项基本的监视任务,用于检测目标信号。能量检测是一种流行的频谱感测技术。但是,在低信噪比(SNR)的条件下以及在噪声不确定的情况下,能量检测器的检测性能会下降。在本文中,我们提出了一种具有模糊阈值方案的能量检测器,用于频谱传感,其中每个传感器节点根据所观察到的能量所在的区域将局部决策发送到融合中心。然后,融合中心通过结合本地决策来做出最终的全球决策。分析和仿真表明,所提出的模糊阈值方案可以有效地提高“或”,“与”和“ K-out-of-N”融合规则下的检测概率,克服了混淆区域的问题。蒙特卡罗仿真结果还表明,该方案具有更好的检测性能,并且分别优于传统的单阈值和双阈值能量检测器。 (C)2017 Elsevier B.V.保留所有权利。

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