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Related Experiment Video

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Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

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Maximum entropy approach to statistical inference for an ocean acoustic waveguide.

D P Knobles¹, J D Sagers, R A Koch

¹Applied Research Laboratories, The University of Texas at Austin, Austin, Texas 78713-8029, USA. knobles@arlut.utexas.edu

The Journal of the Acoustical Society of America

|February 23, 2012

Summary

This study introduces a new method using maximum entropy to estimate ocean seabed properties from acoustic data, providing conservative uncertainty estimates for sound speed and source levels.

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Area of Science:

Geophysics
Oceanography
Acoustics

Background:

Estimating seabed parameters from acoustic data is crucial for oceanographic research.
Traditional methods often involve complex Bayesian inference, requiring likelihood functions.

Purpose of the Study:

To derive a conditional probability distribution for seabed parameters using a maximum entropy principle.
To provide a conservative estimation of parameter uncertainty without explicit likelihood functions.

Main Methods:

Maximum entropy principle applied to constrain an error function's expectation value.
Derivation of a conditional probability distribution and subsequent marginal distributions.
Application to sparse ocean acoustic measurement data.

Main Results:

A canonical probability distribution was derived, offering conservative uncertainty estimates.
Marginal distributions for sound speed ratio and source levels were obtained.
The method was successfully applied to real-world acoustic data from the New Jersey continental shelf.

Conclusions:

The maximum entropy approach offers an alternative to traditional Bayesian methods for acoustic inversion.
This method provides reliable statistical estimates of ocean seabed properties.
The approach is effective even with sparse acoustic data.