Particle velocity gradient based acoustic mode beamforming for short linear vector sensor arrays

Area of Science:

• Acoustics
• Signal Processing
• Array Signal Processing

Background:

• Conventional beamforming methods often require large apertures or are sensitive to noise.
• Particle velocity sensors offer an alternative to pressure sensors for acoustic measurements.
• Extracting acoustic modes from particle velocity data presents unique challenges.

Purpose of the Study:

• To introduce a novel subtractive beamforming algorithm for short linear arrays of particle velocity sensors.
• To demonstrate the algorithm's ability to extract highly directional acoustic modes.
• To evaluate the performance of the proposed beamformer against conventional methods.

Main Methods:

• Utilizing spatial gradients of the particle velocity field measured by closely spaced sensors.
• Implementing a subtractive beamforming approach to isolate acoustic modes.
• Conducting theoretical analysis and numerical simulations for validation.

Main Results:

• The acoustic mode beamformer achieves directivity comparable to differential microphone arrays of equivalent aperture.
• The proposed method requires 70%-85% shorter apertures than conventional delay-and-sum beamformers.
• Demonstrated high front-back discrimination, frequency/direction independent response, and noise robustness.

Conclusions:

• The proposed subtractive beamforming algorithm is effective for short linear arrays of particle velocity sensors.
• The method offers significant advantages in aperture size, directivity, and robustness.
• The compact nature of the beamformer makes it suitable for space-constrained applications like hearing aids and underwater platforms.