Applying the Hilbert-Huang Decomposition to Horizontal Light Propagation C2n data

Abstract

The Hilbert Huang Transform is a new technique for the analysis of non-stationary signals. It comprises two distinct parts: Empirical Mode Decomposition (EMD) and the Hilbert Transform of each of the modes found from the first step to produce a Hilbert Spectrum. The EMD is an adaptive decomposition of the data, which results in the extraction of Intrinsic Mode Functions (IMFs). We discuss the application of the EMD to the calibration of two optical scintillometers that have been used to measure C2n over horizontal paths on a building rooftop, and discuss the advantage of using the Marginal Hilbert Spectrum over the traditional Fourier Power Spectrum.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
ADA472216

Entities

People

  • Carlos O. Font
  • Charmaine Gilbreath
  • Erick A. Roura
  • Eun Oh
  • Mark P. Chang

Organizations

  • United States Naval Research Laboratory

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  • Abstracts
  • Algorithms
  • Data Science
  • Data Sets
  • Decomposition
  • Distribution Functions
  • Estimators
  • Frequency
  • Frequency Domain
  • Information Science
  • Power Spectra
  • Puerto Rico
  • Spectra
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  • Stationary
  • Statistical Algorithms
  • Turbulence

Readers

  • Calculus or Mathematical Analysis
  • Neural Network Machine Learning.
  • Spectroscopy.