Time-angle sensitivity kernels for sound-speed perturbations in a shallow ocean.

Area of Science:

• Ocean acoustics
• Geophysics
• Wave propagation

Background:

• Acoustic waves in shallow-water waveguides create multiple paths.
• These paths are traditionally characterized by travel time (TT).
• Direction of arrival (DOA) and direction of departure (DOD) are geometric properties of these paths.

Purpose of the Study:

• To introduce the use of DOA and DOD as additional observables for tracking sound-speed perturbations.
• To combine TT, DOA, and DOD for improved characterization of oceanic waveguides.
• To develop a method for modeling TT, DOA, and DOD variations caused by sound-speed changes.

Main Methods:

• Utilized first-order Born approximation and Fréchet kernels to link signal fluctuations to sound-speed perturbations.
• Employed a double-beamforming algorithm to convert time-domain signal variations into an eigenray domain (time, reception angle, launch angle).
• Applied a first-order Taylor development to extract TT, DOA, and DOD variations from the processed signals.

Main Results:

• Defined time-angle sensitivity kernels that quantify the relationship between observable variations and sound-speed perturbations.
• Established a linear model connecting variations in TT, DOA, and DOD to sound-speed perturbations.
• Validated the methodology using parabolic-equation simulations in a shallow-water ocean environment.

Conclusions:

• DOA and DOD provide valuable complementary information to TT for acoustic tomography in shallow water.
• The developed method offers a robust framework for inverting acoustic data to map sound-speed variability.
• This approach enhances the capability to monitor and understand dynamic processes within oceanic waveguides.