Resolution improvement of dipole source localization for artificial lateral lines based on multiple signal...

Area of Science:

• Biomimetics and Sensor Technology
• Acoustic Signal Processing
• Robotics and Underwater Systems

Background:

• The lateral line system in fish is crucial for sensing the environment.
• Developing artificial lateral line systems for underwater vehicles is an active research area.
• Accurate dipole source localization is essential for evaluating these artificial systems.

Purpose of the Study:

• To introduce and evaluate the Multiple Signal Classification (MUSIC) method for high-resolution dipole source localization.
• To present an improved Minimum Variance Distortionless Response (MVDR) method.
• To compare the performance of MUSIC and MVDR in an artificial lateral line system.

Main Methods:

• Spatial spectrum estimation using the MUSIC algorithm.
• An improved MVDR algorithm based on Capon's method.
• Experimental validation on a linear prototype of a lateral line canal.

Main Results:

• The MUSIC method achieved a 10.4% improvement in localization resolution compared to MVDR, with similar accuracy.
• MUSIC can localize two closer incoherent dipole sources (20 mm separation) than MVDR (70 mm separation).
• Both MUSIC and MVDR demonstrated robustness to dipole source vibrations.

Conclusions:

• The MUSIC method offers a promising approach for high-resolution and multi-source dipole localization in artificial lateral line systems.
• This advancement can enhance the sensing capabilities of underwater vehicles.
• The MUSIC method provides a robust solution for underwater navigation and environmental monitoring.