Approximate maximum-likelihood period estimation from sparse, noisy timing data

Clarkson, I.V.L (2008) Approximate maximum-likelihood period estimation from sparse, noisy timing data. IEEE Transactions on Signal Processing, 56 5: 1779-1787. doi:10.1109/TSP.2007.912268

Author Clarkson, I.V.L
Title Approximate maximum-likelihood period estimation from sparse, noisy timing data
Journal name IEEE Transactions on Signal Processing   Check publisher's open access policy
ISSN 1053-587X
Publication date 2008-05-05
Year available 2008
Sub-type Article (original research)
DOI 10.1109/TSP.2007.912268
Open Access Status Not yet assessed
Volume 56
Issue 5
Start page 1779
End page 1787
Total pages 9
Editor A. H. Sayed
Place of publication Piscataway, New Jersey, USA
Publisher IEEE
Language eng
Subject C1
970101 Expanding Knowledge in the Mathematical Sciences
970109 Expanding Knowledge in Engineering
090609 Signal Processing
Abstract The problem of estimating the period of a series of periodic events is considered under the condition where the measurements of the times of occurrence are noisy and sparse. The problem is common to bit synchronisation in telecommunications and pulse-train parameter estimation in electronic support, among other applications. Two new algorithms are presented which represent different compromises between computational and statistical efficiency. The first extends the separable least squares line search (SLS2) algorithms of Sidiropoulos et al., having very low computational complexity while attaining good statistical accuracy. The second is an approximate maximum-likelihood algorithm, based on a low complexity lattice search, and is found to achieve excellent accuracy.
Keyword Baud Rate estimation
Cramer-Rao lower bound
Maximum Likehood
nearest lattice point problem
period estimation
pulse repetition interval
time of arrival
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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