Proceedings Article10.1109/SSAP.1994.572438
On Time Delay Estimation
Hagit Messer,P.M. Schultheiss +1 more
- 26 Jun 1994
- pp 67-70
81
TL;DR: In this article, the authors considered the time-delay estimation problem in continuous and discrete time, where the unknown time origin of the signal is assumed to be unknown, and the maximum likelihood estimate of signal delay is determined by the most fundamental expression of the maximization procedure.
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Abstract: An important signal parameter estimation problem is time-delay estimation. Here the unknown is the time origin of the signal: s (l, θ) = s (l − θ). The duration of the signal (the domain over which the signal is de ned) is assumed brief compared with the observation interval L. Although in continuous time the signal delay is a continuous-valued variable, in discrete time it is not. Consequently, the maximum likelihood estimate cannot be found by di erentiation, and we must determine the maximum likelihood estimate of signal delay by the most fundamental expression of the maximization procedure. Assuming Gaussian noise, the maximum likelihood estimate of delay is the solution of
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References
The generalized correlation method for estimation of time delay
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.
4.8K
Signal Detection in Non-Gaussian Noise
S.A. Kassam
TL;DR: Signal detection in non-Gaussian noise is covered in this book. The noise is not necessarily Gaussian.
762
Some lower bounds on signal parameter estimation
Jacob Ziv,Moshe Zakai +1 more
TL;DR: New bounds are presented for the maximum accuracy with which parameters of signals imbedded in white noise can be estimated, which are independent of the bias and include explicitly the dependence on the a priori interval.
379
Time delay estimation in unknown Gaussian spatially correlated noise
Chrysostomos L. Nikias,R. Pan +1 more
TL;DR: It is demonstrated that estimation techniques based on higher-order cumulants suppress the effect of correlated Gaussian noise sources and therefore exhibit improved performance over generalized cross-correlation methods.
184
On time delay estimation with unknown spatially correlated Gaussian noise using fourth-order cumulants and cross cumulants
TL;DR: The problem of estimating the difference in arrival times of a linear non-Gaussian signal at two spatially separated sensors is considered, and the fourth-order cumulant statistics of the noisy measurements are exploited to obtain the time delay estimate.
66