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针对工程测试中较常见的具有Ｇａｕｓｓ 分布的平稳随机信号，提出了一种基于极性相关方法的计算信号间标准化互相关函数的快速算法． 理论分析和实际运行都表明该算法可以有效缩短标准化互相关函数的计算时间，适用于在线逐点跟踪信号样本的变化．仿真实验表明该方法可较好地用于上限截止频率为１００ Ｈｚ 左右的Ｇａｕｓｓ 分布随机信号的在线相关分析．
Aiming at the stationary random signal with Gauss distribution, which is more common in engineering testing, a fast algorithm for calculating the normalized cross-correlation function between signals based on the polarity correlation method is proposed. Both theoretical analysis and practical operation show that the algorithm can effectively shorten the calculation time of the normalized cross-correlation function and is suitable for on-line tracking of the signal samples point by point. Simulation results show that this method can be applied to the online correlation analysis of Gaussian distributed random signals whose upper cut-off frequency is about 100 Hz.