Tracking of multiple surface vessels based on passive acoustic underwater arrays

Area of Science:

• Marine acoustics
• Underwater surveillance
• Signal processing

Background:

• Tracking non-cooperative surface vessels is crucial for maritime security and situational awareness.
• Passive acoustic sensing offers a covert method for vessel detection and localization.
• Existing methods may struggle with unknown numbers of targets and complex acoustic environments.

Purpose of the Study:

• To develop and validate an approach for localizing and tracking an unknown number of non-cooperative surface vessels.
• To utilize passive acoustic data from hydrophones for vessel detection.
• To apply a Bayesian framework for multi-object tracking to Time-Difference of Arrival (TDOA) measurements.

Main Methods:

• Employing passive acoustic sensing to capture underwater noise radiated by surface vessels.
• Extracting Time-Difference of Arrival (TDOA) measurements from pairs of hydrophones.
• Utilizing a Bayesian framework for multi-object tracking to process TDOA data for vessel detection and tracking.
• Using a three-dimensional compact hydrophone array towed by an autonomous vehicle for data acquisition.

Main Results:

• Demonstrated successful detection and tracking of non-cooperative surface vessels using the proposed method.
• Validated the effectiveness of the Bayesian multi-object tracking framework with TDOA measurements.
• Confirmed the feasibility of localizing and tracking vessels based solely on their radiated underwater noise.

Conclusions:

• The developed passive acoustic sensing approach is effective for localizing and tracking unknown numbers of non-cooperative surface vessels.
• The Bayesian tracking framework provides a robust method for multi-object tracking in this context.
• This technology has significant implications for underwater surveillance and maritime domain awareness.