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Atomic Emission Spectroscopy: Overview01:20

Atomic Emission Spectroscopy: Overview

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Spectral probability density as a tool for ambient noise analysis.

Nathan D Merchant1, Tim R Barton, Paul M Thompson

  • 1Department of Physics, University of Bath, Bath, BA2 7AY, United Kingdom. n.d.merchant@bath.ac.uk

The Journal of the Acoustical Society of America
|April 6, 2013
PubMed
Summary

This study introduces a new method using empirical probability density of power spectral density to evaluate passive acoustic monitoring systems. It reveals system limitations and improves underwater noise analysis for better performance assessment.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Environmental Monitoring

Background:

  • Passive acoustic monitoring (PAM) systems are crucial for underwater noise assessment.
  • Conventional methods may miss critical performance limitations in PAM systems.
  • Understanding underwater noise distribution is vital for ecological and industrial applications.

Purpose of the Study:

  • To present the empirical probability density of the power spectral density (PSD) as a novel tool for assessing PAM system field performance.
  • To identify limitations in PAM systems, such as tonal components and dynamic range issues.
  • To propose an integrated method for presenting ambient noise spectra.

Main Methods:

  • Calculating the empirical probability density of the power spectral density from PAM data.
  • Analyzing example datasets to demonstrate the method's capabilities.
  • Combining the empirical probability density with spectral averages and percentiles.

Main Results:

  • The empirical probability density method effectively reveals limitations missed by conventional techniques.
  • Persistent tonal components and insufficient dynamic range were identified in example datasets.
  • The influence of noise level distributions on spectral averages and percentiles was illustrated.

Conclusions:

  • The empirical probability density of PSD is a valuable tool for evaluating PAM system performance.
  • This method enhances the detection of subtle system limitations.
  • An integrative approach combining empirical probability density with spectral metrics offers a standardized way to present ambient noise spectra.