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Memory-efficient approximate three-dimensional beamforming.

Nicholas R Rypkema1, Erin M Fischell1, Henrik Schmidt2

  • 1Applied Ocean Physics & Engineering, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA.

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|December 31, 2020
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Summary
This summary is machine-generated.

This study introduces a memory-efficient method for localizing acoustic sources using sensor arrays. The new approach improves direction resolution for three-dimensional (3D) direction-of-arrival (DOA) estimation in systems with limited memory.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Array Signal Processing

Background:

  • Acoustic source localization commonly uses direction-of-arrival (DOA) estimation via beamforming.
  • Conventional beamforming (CBF) faces memory and resolution trade-offs due to pre-computed time delays.
  • Limited memory in embedded systems restricts the number of directions that can be analyzed.

Purpose of the Study:

  • To present a novel, memory-efficient method for 3D acoustic source localization.
  • To enhance direction resolution in DOA estimation for resource-constrained platforms.
  • To enable real-time acoustic localization in embedded systems.

Main Methods:

  • Developed a method that reduces 3D look directions (azimuth/inclination angles) to a single conical angle variable.
  • Treated the sensor array as a collection of sensor pairs for computational efficiency.
  • Compared the new method against conventional beamforming (CBF) for accuracy, speed, and memory usage.

Main Results:

  • The proposed method significantly improves memory efficiency for 3D beamforming applications.
  • Achieved enhanced direction resolution by reducing the dimensionality of look directions.
  • Demonstrated comparable accuracy to CBF, with notable computational speedup and memory savings.

Conclusions:

  • The novel DOA localization method offers substantial memory and computational benefits for 3D beamforming.
  • This technique is particularly suitable for real-time acoustic localization on embedded systems with limited resources.
  • The method's gain limitations restrict its application to strong acoustic sources.