Localization of acoustic sensors from passive Green's function estimation

Area of Science:

• Acoustics
• Signal Processing
• Sensor Technology

Background:

• Passive localization methods often assume diffuse acoustic fields.
• Diffuse field models may not accurately represent complex acoustic environments with reflections.

Purpose of the Study:

• To present a more general model for passive acoustic sensor localization using equipartition fields.
• To compare the performance of equipartition fields against diffuse field models.
• To investigate the relevance of the equipartition approach under various boundary conditions.

Main Methods:

• Developed a theoretical framework for equipartition fields, accounting for boundary reflections and scatterers.
• Analyzed the fundamental differences between diffuse and equipartition field models.
• Conducted experimental validation with two distinct boundary conditions.

Main Results:

• The equipartition field model is more robust than the diffuse field model, particularly for wideband noise sources.
• Experimental results confirm the enhanced performance of the equipartition approach when acoustic sensors are positioned near boundaries.
• The model's effectiveness is demonstrated across different boundary conditions.

Conclusions:

• The equipartition field model provides a more accurate and robust framework for passive acoustic sensor localization in complex environments.
• This generalized approach significantly improves localization accuracy, especially in scenarios with significant reflections or when sensors are near boundaries.
• The findings highlight the limitations of diffuse field assumptions and advocate for the use of equipartition fields in practical applications.