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Parametric Optimization Design Method for Friction Plates of Hydro-Viscous Clutches

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Published on: July 22, 2025

Optimum array design to maximize Fisher information for bearing estimation.

Saurav R Tuladhar¹, John R Buck

¹Department of Electrical and Computer Engineering, University of Massachusetts Dartmouth, 285 Old Westport Road, North Dartmouth, Massachusetts 02747-2300, USA. stuladhar@umassd.edu

The Journal of the Acoustical Society of America

|November 18, 2011

Summary

Optimized sensor array placement minimizes bearing estimation error in noisy ocean environments. This array design improves signal-to-noise ratio by 2-5 dB compared to uniform arrays.

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Area of Science:

Acoustics and Signal Processing
Array Signal Processing
Oceanography

Background:

Source bearing estimation using linear sensor arrays is crucial in applications like underwater acoustics.
The Cramer-Rao bound (CRB) defines the theoretical lower limit for the mean square error (MSE) of unbiased bearing estimates.
Traditional array designs optimized for spatially white noise are suboptimal in realistic shallow water environments with correlated ambient noise.

Purpose of the Study:

To design a fixed aperture linear sensor array that maximizes bearing Fisher information (FI) under cylindrically isotropic noise conditions.
To minimize the mean square error (MSE) of bearing estimates in shallow water environments.
To investigate the trade-offs between array bearing sensitivity and output noise power variation.

Main Methods:

Formulated the problem of sensor array design to maximize Fisher Information (FI), which is the inverse of the Cramer-Rao bound (CRB).
Modeled correlated ambient noise in shallow water environments as cylindrically isotropic.
Determined the optimal sensor element positions by balancing bearing sensitivity and noise power variation.

Main Results:

The optimized array positions sensors closer to the ends than uniform spacing, but not as extreme as in the white noise case.
Maximizing Fisher Information (FI) leads to minimizing the achievable Mean Square Error (MSE) for bearing estimation.
The optimized array offers a performance improvement equivalent to a 2-5 dB gain in signal-to-noise ratio (SNR) over a uniform array.

Conclusions:

A fixed aperture linear array optimized for cylindrically isotropic noise conditions significantly improves bearing estimation accuracy.
The optimal array design represents a trade-off, enhancing sensitivity while managing noise power variations.
This research provides a practical array configuration for improved underwater acoustic source localization in challenging environments.