Spectral analysis methods for Poisson sampled measurements

The velocity measurements for turbulent flow regimes obtained with laser Doppler anemometry are not only affected by random noise but are also unevenly spaced in time. The usual spectral estimators rely on evenly spaced data points. It would appear then that the measurement data requires adjustment...

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Bibliographic Details
Published inIEEE transactions on instrumentation and measurement Vol. 46; no. 4; pp. 882 - 887
Main Author Banning, R.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.08.1997
Institute of Electrical and Electronics Engineers
Subjects
Density functional theory
Diffusion processes
Exact sciences and technology
Fluid dynamics
Fundamental areas of phenomenology (including applications)
Instrumentation for fluid dynamics
Linear discriminant analysis
Measurement techniques
Noise measurement
Physics
Spectral analysis
Stochastic processes
Stochastic resonance
Velocity measurement
White noise
Lagrangian model
Turbulent flow
Sampled signal
Error estimation
Power spectra
Stochastic systems
Discrete Fourier transforms
Laser Doppler anemometers
Kalman filtering
Velocity measurement
Poisson process
Spectral analysis
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Summary:The velocity measurements for turbulent flow regimes obtained with laser Doppler anemometry are not only affected by random noise but are also unevenly spaced in time. The usual spectral estimators rely on evenly spaced data points. It would appear then that the measurement data requires adjustment before it can be passed on to these estimators. In this paper, both an analysis method with a novel adjustment scheme as well as an analysis method which does not rely on the use of adjustment schemes, are presented.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0018-9456
1557-9662
DOI:10.1109/19.650793