论文标题
两个非narrow带时间信号之间的相似性和延迟
Similarity and delay between two non-narrow-band time signals
论文作者
论文摘要
相关系数通常用于测量两个时间信号之间的相关度。但是，如果信号发出信号，其性能将下降甚至失败。基于正常时频变换（NTFT）提供的时频阶段光谱（TFP），即使信号是噪声，也提出了相似系数来测量两个非核乐波信号之间的相似性。相似性系数的基本思想是将信号F1（t）TFPS的兴趣部分沿时间轴转换为与信号F2（t）的TFP的夫妇。如果F1（T）和F2（T）在时间频结构上确实相似，则此类耦合将产生最大值。如果归一化，则称为相似性系数。最大的位置表示F1（t）和F2（t）之间的时间延迟。数值结果表明，相似系数在测量两个NOIDER信号之间的相关程度时，相似性系数优于相关系数。基于相似性分析的时间延迟估计（TDE）的精度和准确性要比基于互相关方法（CC）方法和广义CC（GCC）方法（在低SNR下）好得多。
Correlation coefficient is usually used to measure the correlation degree between two time signals. However, its performance will drop or even fail if the signals are noised. Based on the time-frequency phase spectrum (TFPS) provided by normal time-frequency transform (NTFT), similarity coefficient is proposed to measure the similarity between two non-narrow-band time signals, even if the signals are noised. The basic idea of the similarity coefficient is to translate the interest part of signal f1(t)'s TFPS along the time axis to couple with signal f2(t)'s TFPS. Such coupling would generate a maximum if f1(t)and f2(t) are really similar to each other in time-frequency structure. The maximum, if normalized, is called similarity coefficient. The location of the maximum indicates the time delay between f1(t) and f2(t). Numerical results show that the similarity coefficient is better than the correlation coefficient in measuring the correlation degree between two noised signals. Precision and accuracy of the time delay estimation (TDE) based on the similarity analysis are much better than those based on cross-correlation (CC) method and generalized CC (GCC) method under low SNR.
