Quantifying the influence of source motion on the ray-based blind deconvolution algorithm.

Area of Science:

• Underwater acoustics
• Signal processing
• Geophysics

Background:

• The ray-based blind deconvolution algorithm (RBD) estimates channel responses and signals from opportunistic sources.
• RBD performance is currently limited by its assumption of stationary sources, such as shipping vessels.

Purpose of the Study:

• To investigate the impact of source motion on RBD algorithm performance.
• To develop and validate a theoretical correction for Doppler effects caused by source movement.

Main Methods:

• Developed a simplified moving source model to derive a theoretical correction for Doppler shifts.
• Quantified biases in estimated arrival angles and travel times introduced by source motion.
• Numerically validated the correction using environmental data from the SBCeX16 experiment.

Main Results:

• Source motion significantly biases arrival angle and travel time estimations in RBD.
• The proposed Doppler correction effectively quantifies and mitigates these biases.
• Numerical validation confirmed the correction's efficacy in real-world environmental data.

Conclusions:

• Source motion is a critical factor affecting RBD accuracy for passive acoustic monitoring.
• The developed correction enhances the reliability of RBD for source localization and passive acoustic tomography.
• This work advances the application of RBD for analyzing data from mobile acoustic sources.