The Nearest-Neighbor Cross-Correlation (NNCC), Translating Apertures (TA), and Near-Field Signal Redundancy (NFSR) algorithms have a common feature: they all calculate cross-correlation functions between signals that are assumed to be highly correlated (matched signals), and then derive the aberration profile from the peak positions of these cross-correlation functions. One of the major differences between them is the way matched signals are collected. In this paper, a sub-signal analysis of matched signals is performed to demonstrate the different sub-signal components in matched signals collected with these three algorithms. The sub-signal components of matched signals influence the similarity between them and they have significant impact on the performance of an algorithm. The similarity between matched signals collected with these three algorithms is experimentally compared by calculating the cross-correlation coefficient between matched signals. Signals are collected from a phantom with a modified ATL Ultramark(R) 8 ultrasound scanner. It shows that the degree of similarity between matched signals in these algorithms is in the following order (from more to less similar): NFSR, TA, and NNCC. It also shows that, when phase aberrations exist, the cross-correlation coefficients between matched signals in the NNCC and TA algorithms decrease more dramatically than those in the NFSR algorithm.
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