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Robust Gaussian kernel based signal detection in the presence of non-Gaussian noise

机译:基于强大的高斯内核基于非高斯噪声的信号检测

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This letter presents a robust Gaussian kernel based detector for the detection of random signal distorted by non-Gaussian noise. The proposed detection scheme does not need any prior information of the signal, noise and channel. The GKD detector is shown to be asymptotic energy detection (ED) as the width of Gaussian kernel becomes sufficiently large. The asymptotic null distribution of the GKD statistic is derived, enabling us to determine the detection threshold. Simulation results illustrate that in terms of receiver operating characteristic (ROC) curve and detection probability, the GKD detector not only performs comparably with ED in the presence of Gaussian noise, but also achieves better performance than the state-of-the-art detectors whether the noise is pure Gaussian or non-Gaussian.
机译:这封信提供了一种基于高斯内核基于高斯内核的探测器,用于检测由非高斯噪声失真的随机信号。所提出的检测方案不需要信号,噪声和信道的任何先前信息。由于高斯内核的宽度变得足够大,但GKD检测器被显示为渐近能量检测(ED)。导出GKD统计的渐近空分布,使我们能够确定检测阈值。仿真结果说明,在接收器操作特征(ROC)曲线和检测概率方面,GKD检测器不仅在高斯噪声的存在下与ED相当地执行,而且还可以实现比最先进的探测器更好的性能噪音是纯粹的高斯或非高斯。

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