High-precision array element localization for bottom-mounted horizontal line arrays in the deep oceana).

Area of Science:

• Oceanography
• Acoustics
• Signal Processing

Background:

• High-precision array element localization (AEL) is critical for bottom-mounted horizontal line arrays.
• Deployment uncertainties and environmental factors like sound-speed variability degrade performance in deep-ocean acoustics.

Purpose of the Study:

• To develop an improved AEL method for deep-ocean environments.
• To enhance localization accuracy and source-timing estimation by accounting for complex acoustic propagation and environmental variability.

Main Methods:

• Formulated AEL as a simultaneous localization and mapping problem within a Bayesian framework.
• Incorporated a ray propagation model (RPM) to utilize direct and surface-reflected paths, accounting for sound-speed profile variations.
• Employed an extended Kalman filter for joint estimation of array geometry, source trajectory, emission time, and sound-speed bias.

Main Results:

• The RPM-based method achieved comparable horizontal localization accuracy to the linear propagation model (LPM).
• Significantly improved vertical localization performance and source-timing estimation compared to LPM.
• Demonstrated robustness to sound-speed profile uncertainty through sensitivity and consistency analyses.
• Array calibration reduced bearing estimation RMSE from 4.36° to 0.29°, improving beamforming gain by 2.1 dB.

Conclusions:

• The RPM-based Bayesian approach enhances AEL accuracy in challenging deep-ocean conditions.
• This method offers significant improvements in vertical localization and source-timing estimation.
• Effective array calibration is vital for practical applications, leading to substantial performance gains.