Orthogonal subspace approach for underwater acoustic wave-vector direction estimation based on acousto-optic sensing

Area of Science:

• Acoustics
• Optics
• Signal Processing

Background:

• High-precision wave-vector direction estimation is crucial for underwater applications like positioning and tracking.
• Traditional methods using acoustic arrays require large apertures, and single sensors struggle at mid-to-high frequencies due to phase consistency issues.

Purpose of the Study:

• To develop a novel acoustic vector sensing method using the acousto-optic effect for improved wave-vector direction estimation.
• To overcome the limitations of existing methods, particularly at mid-to-high frequencies.

Main Methods:

• Utilized the acousto-optic effect for non-contact, multidimensional acoustic vector sensing.
• Developed an orthogonal-subspace wave-vector direction estimation algorithm (MUSIC-L) based on the MUSIC method and acousto-optic sensing.
• Validated the MUSIC-L algorithm through simulations and experimental measurements using a prototype acousto-optic vector hydrophone.

Main Results:

• Simulations demonstrated robustness and angle independence, achieving a root mean square error of 1.4° at 10 dB SNR with 80 snapshots.
• Experimental results with the prototype hydrophone showed estimation errors below 1° with a standard deviation of approximately 0.23°.

Conclusions:

• The acousto-optic sensing approach offers a viable solution for high-precision wave-vector direction estimation in underwater acoustics.
• The MUSIC-L algorithm effectively leverages acousto-optic sensing for accurate and robust direction finding at mid-to-high frequencies.