A particle filtering approach for spatial arrival time tracking in ocean acoustics.

Area of Science:

• Ocean acoustics
• Signal processing
• Array processing

Background:

• Accurate estimation of acoustic signal arrival times and amplitudes is crucial for underwater applications.
• Existing methods, like maximum likelihood estimators, often fail to leverage spatial information from multiple receivers effectively.

Purpose of the Study:

• To develop and evaluate a novel particle filtering approach for joint arrival time and amplitude estimation.
• To compare the performance of the particle filter against a maximum likelihood estimator in ocean acoustic signal processing.

Main Methods:

• A particle filtering algorithm was developed to track acoustic arrival times as 'targets' across spatially separated hydrophones.
• The method models arrival time gradients and incorporates amplitude estimation.
• Performance was assessed using Monte Carlo simulations.

Main Results:

• The particle filter demonstrated a significant advantage over the maximum likelihood estimator in accuracy.
• The proposed method effectively utilizes spatial information from neighboring receivers.
• Posterior probability density functions for arrival times and amplitudes were readily obtained.

Conclusions:

• Particle filtering offers a superior approach for acoustic signal parameter estimation in ocean environments.
• The method's ability to provide probability density functions enhances the reliability of estimated parameters.