Alignment of noisy signals
Alignment of noisy signals
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DOI：
10.1109/19.903892
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发表时间：
2001-02-01
影响因子：
5.6
通讯作者：
Hale, P
中科院分区：
文献类型：
--
作者：
Coakley, KJ;Hale, P
我们;研究了各种一维噪声信号调准方法的相对性能。假设不知道失调信号的形状。我们模拟了被加性噪声和时序抖动噪声破坏的信号，其复杂性与NIST收集的鼻对鼻示波器校准信号相似。在一种方法中，我们将两个信号的相对位移估计为它们估计的质心之差，提出了一种新的自适应质心估计算法。我们还估计了三种不同的互相关分析实现的相对偏移。在一个完整的实现中，对于N个信号，从所有N(N - 1)/2个不同的信号对中估计相对位移。在朴素实现中，相对移位仅从（N - 1）对信号估计。在迭代自适应实现中，我们估计每个信号相对于模板信号的相对位移，在每次迭代中，该模板信号等于对齐信号的信号平均值。在模拟实验中；产生100个错位信号。对于所有噪声水平，完全互相关方法产生最准确的相对位移估计。其他方法的相对性能取决于噪声水平。
We;study the relative performance of various methods for aligning noisy one-dimensional signals. No knowledge of the shape of the misaligned signals is assumed. We simulate signals corrupted by both additive noise and timing jitter noise which are similar in complexity to nose-to-nose oscilloscope calibration signals collected at NIST. In one method, we estimate the relative shift of two signals as the difference of their estimated centroids, We present a new adaptive algorithm for centroid estimation. We also estimate relative shifts from three different implementations of cross-correlation analysis. In a complete implementation, for N signals, relative shifts are estimated from all N(N - 1)/2 distinct pairs of signals. In a naive implementation, relative shifts are estimated from just (N - 1) pairs of signals. In an iterative adaptive implementation, we estimate the relative shift of each signal with respect to a template signal which, at each iteration, is equated to the signal average of the aligned signals. In simulation experiments; 100 misaligned signals are generated. For all noise levels, the complete cross-correlation method yields the most accurate estimates of the relative shifts. The relative performance of the other methods depends on the noise levels.