ABSTRACT We previously presented a novel time-delay estimator that uses cubic splines to estimate continuous time delays from sampled data. Previous simulation results showed that the spline-based algorithm yields superior performance when compared to the normalized correlation and the sum squared differences (SSD) algorithms implementing a variety of subsample interpolators.
In this short communication, we present additional simulation results that compare the spline-based time-delay estimator to well-known phase-domain estimators. Under comparable conditions, spline-based methods exhibit biases approximately one tenth and standard deviation only one hundredth of those observed for the phase-based approaches.
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