Journal Article10.1109/29.1562
Adaptive time delay estimation with constraints
P. C. Ching,Yiu-Tong Chan +1 more
36
TL;DR: The time (shift) delay parameter between two signals is modeled as a finite-impulse response filter whose coefficients are samples of a sinc function, which involves less computation and the elimination of interpolation needed in previous approaches to obtain nonintegral time-delay estimates.
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Abstract: The time (shift) delay parameter between two signals is modeled as a finite-impulse response filter whose coefficients are samples of a sinc function. The time-domain LMS (least-mean-squares) adaptive algorithm is used, but only the weight with the largest magnitude is updated, which involves less computation. The result is a faster adaptation and the elimination of interpolation needed in previous approaches to obtain nonintegral (multiples of sampling period) time-delay estimates. >
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Citations
Time delay estimation in room acoustic environments: an overview
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References
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TL;DR: In this paper, a maximum likelihood estimator is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise, where the role of the prefilters is to accentuate the signal passed to the correlator at frequencies for which the signal-to-noise (S/N) ratio is highest and suppress the noise power.
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Time delay estimation for passive sonar signal processing
TL;DR: In this article, an overview of applied research in passive sonar signal processing estimation techniques for naval systems is presented, where the authors present a discussion of this problem in terms of estimating the position and velocity of a moving acoustic source.
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Time delay estimation using the LMS adaptive filter--Dynamic behavior
F. Reed,P. Feintuch,N. Bershad +2 more
TL;DR: In this article, a new application of the LMS adaptive filter, that of determining the time delay in a signal between two split-array outputs, is described, where this time delay can be converted to the bearing of the target radiating the signal.
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A parameter estimation approach to time-delay estimation and signal detection
Yiu-Tong Chan,J. Riley,J. Plant +2 more
TL;DR: In this paper, it was shown that the least square estimation of the filter coefficients is equivalent to estimating the Roth processor, and that the parameter estimation approach is expected to have a smaller variance since it avoids the need for spectra estimation.
147
On the advantages of the LMS spectrum analyzer over nonadaptive implementations of the sliding-DFT
TL;DR: Based on the least mean squares (LMS) algorithm, the LMS spectrum analyzer can be used to recursively calculate the discrete Fourier transform (DFT) of a sliding window of data.
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