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Using Fisher information to quantify uncertainty in environmental parameters estimated from correlated ambient noise
Shane C Walker1, Caglar Yardim, Aaron Thode
1Marine Physical Laboratory, Scripps Institution of Oceanography, La Jolla, California 92093-0238, USA. scwalker@ucsd.edu
The Journal of the Acoustical Society of America
|April 6, 2013
Summary
Estimating environmental parameters from ambient noise is challenging due to noise fluctuations. This study quantifies estimation uncertainty, finding an optimal sensor separation minimizes errors in speed and attenuation measurements.
Area of Science:
- Acoustics
- Environmental Sensing
- Signal Processing
Background:
- Characterizing environmental parameters using ambient noise is crucial but limited by inherent noise uncertainty.
- Stochastic fluctuations in ambient noise introduce significant challenges for accurate parameter estimation.
Purpose of the Study:
- To calculate the Fisher information and Cramer-Rao bound for unbiased correlated ambient noise parameter estimates.
- To determine lower bounds on the error covariance for medium speed and attenuation parameters in a 2D isotropic noise scenario.
Main Methods:
- Theoretical calculation of Fisher information and Cramer-Rao bounds.
- Application to a two-dimensional isotropic ambient noise model.
- Validation through simulated parameter inversions.
Main Results:
- An optimal sensor separation was identified to achieve minimum error in parameter estimation.
- Lower bounds for error covariance of speed and attenuation were derived.
- Simulated inversions validated the theoretical predictions.
Conclusions:
- The study provides a framework for quantifying uncertainty in ambient noise-based environmental sensing.
- Optimal sensor configuration is key to minimizing estimation errors.
- Factors like record length, bandwidth, signal-to-noise ratio, and spatial resolution influence estimation accuracy.
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