Access the full text.
Sign up today, get DeepDyve free for 14 days.
C. Tropea (1995)
Laser Doppler anemometry: recent developments and future challengesMeasurement Science and Technology, 6
J. Roberts, M. Gaster (1980)
On the estimation of spectra from randomly sampled signals: a method of reducing variabilityProceedings of the Royal Society of London. A. Mathematical and Physical Sciences, 371
F. Frontera, F. Fuligni (1978)
The effect of dead time on the power spectral density estimates of discrete time seriesNuclear Instruments and Methods, 157
H. Nobach (2002)
Local time estimation for the slotted correlation function of randomly sampled LDA dataExperiments in Fluids, 32
F. Durst, A. Melling, J. Whitelaw, C. Wang (1976)
Principles and practice of laser-Doppler anemometry
R. Adrian, C. Yao (1985)
Power spectra of fluid velocities measured by laser Doppler velocimetryExperiments in Fluids, 5
M. Gaster, J. Roberts (1975)
Spectral Analysis of Randomly Sampled SignalsIma Journal of Applied Mathematics, 15
R. Blackman, J. Tukey (1958)
The Measurement of Power Spectra from the Point of View of Communications Engineering
S. Moreau, G. Plantier, J. Valière, H. Bailliet, Laurent Simon (2011)
Estimation of power spectral density from laser Doppler data via linear interpolation and deconvolutionExperiments in Fluids, 50
H. Maanen, H. Nobach, L. Benedict (1999)
Improved estimator for the slotted autocorrelation function of randomly sampled LDA dataMeasurement Science and Technology, 10
E. Masry (1978)
Alias-free sampling: An alternative conceptualization and its applicationsIEEE Trans. Inf. Theory, 24
W. George, P. Beuther, J. Lumley (1978)
Processing of Random Signals
H. Albrecht, M. Borys, N. Damaschke, C. Tropea (2002)
Laser Doppler and Phase Doppler Measurement Techniques
(1998)
Correlation estimator for two-channel, non-coincidence laser-Doppler-anemometer
M Tummers, D Passchier (1996)
Spectral estimation using a variable window and the slotting technique with local normalizationMeasurement Science and Technology, 7
Laurent Simon, J. Fitzpatrick (2004)
An improved sample-and-hold reconstruction procedure for estimation of power spectra from LDA dataExperiments in Fluids, 37
J. Mayo, Shay T., Riter T. (1974)
The Development of New Digital Data Processing Techniques for Turbulence Measurements with a Laser Velocimeter
J. Roberts, J. Downie, M. Gaster (1980)
Spectral analysis of signals from a laser Doppler anemometer operating in the burst modeJournal of Physics E: Scientific Instruments, 13
Correlation estimator for two point laser Doppler anemometry . Proceedings of the SPIE
C. Velte, P. Buchhave, W. George (2014)
Dead time effects in laser Doppler anemometry measurementsExperiments in Fluids, 55
P. Buchhave, W. George, J. Lumley (1979)
The Measurement of Turbulence with the Laser-Doppler AnemometerAnnual Review of Fluid Mechanics, 11
M Gaster, JB Roberts (1975)
Spectral analysis of randomly sampled signalsJ Inst Math Appl, 15
M. Gaster, J. Roberts (1977)
The spectral analysis of randomly sampled records by a direct transformProceedings of the Royal Society of London. A. Mathematical and Physical Sciences, 354
C. Velte, W. George, P. Buchhave (2014)
Estimation of burst-mode LDA power spectraExperiments in Fluids, 55
W. Zhang, K. Jahoda, J. Swank, E. Morgan, A. Giles (1995)
Dead-Time Modifications to Fast Fourier Transform Power SpectraThe Astrophysical Journal, 449
(2014)
The effect of dead time on randomly sampled power spectral estimatesExperiments in Fluids, 55
HS Shapiro, RA Silverman (1960)
Alias-free sampling of random noiseJ Soc Ind Appl Math, 8
L. Benedict, H. Nobach, C. Tropea (2000)
Estimation of turbulent velocity spectra from laser Doppler dataMeasurement Science and Technology, 11
We consider the origin of noise and distortion in power spectral estimates of randomly sampled data, specifically velocity data measured with a burst-mode laser Doppler anemometer. The analysis guides us to new ways of reducing noise and removing spectral bias, e.g., distortions caused by modifications of the ideal Poisson sample rate caused by dead time effects and correlations between velocity and sample rate. The noise and dead time effects for finite records are shown to tend to previous results for infinite time records and ensemble averages. For finite records, we show that the measured sampling function can be used to correct the spectra for noise and dead time effects by a deconvolution process. We also describe a novel version of a power spectral estimator based on a fast slotted autocovariance algorithm.
Experiments in Fluids – Springer Journals
Published: Apr 1, 2015
Access the full text.
Sign up today, get DeepDyve free for 14 days.