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本文提出了一种利用高阶统计量对加性噪声中的确定性信号及非高斯随机信号进行检测的方法。这种检测方法对加性噪声是否有色或是否为高斯分布并不敏感，而只要求噪声具有对称的概率密度函数，在信号波形未知而造成匹配滤波器性能恶化时，利用这种方法对确定性信号进行检测的性能与已知彼形时匹配滤波器的检测性能相近。在色噪声话密度未知且噪声港与信号谱重叠程度最大时，这种方法的性能优于匹配滤波器。利用这种方法还非常易于实现非高斯随机信号的检测。因此，这种检测方法弥补了匹配滤波器必须有先验知识才能达到良好检测效果的不足。
This paper presents a method for detecting deterministic and non-Gaussian random signals in additive noise using higher-order statistics. This method of detection is not sensitive to whether the additive noise is colored or not Gaussian, but only requires that the noise has a symmetric probability density function. When the signal waveform is unknown, the performance of the matched filter deteriorates, this method is used to determine the certainty The performance of the signal detection is similar to that of the known matched filter. This method outperforms the matched filter when the density of colored noise is unknown and the noise floor overlaps with the signal spectrum to the maximum. Using this method is also very easy to achieve non-Gaussian random signal detection. Therefore, this detection method to make up for the matched filter must have a priori knowledge in order to achieve good detection of deficiencies.