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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.
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.
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