Wideband compressive beamforming tomography for drive-by large-scale acoustic source mapping

Area of Science:

• Acoustics
• Signal Processing
• Environmental Science

Background:

• Urban noise pollution requires effective identification of noise hotspots.
• Sound visualization tools like noise-mapping are crucial for targeted noise control measures.

Purpose of the Study:

• To develop a high-resolution wideband acoustic source mapping methodology.
• To enable joint localization and power spectrum estimation of sparse acoustic sources over large regions.

Main Methods:

• Utilized a portable microphone array for data acquisition.
• Employed tomographic imaging with multi-frequency delay-and-sum beamforming.
• Applied compressive sensing techniques (group LASSO, sparse Bayesian learning) for group sparsity promotion across multiple frequency bands.

Main Results:

• Generated two-dimensional tomographic maps with high resolution.
• Successfully demonstrated the methodology with experimental data from a mobile microphone array.
• Validated the technique for mapping acoustic sources in an open field environment.

Conclusions:

• The developed methodology provides an effective tool for high-resolution acoustic source mapping.
• This approach is vital for identifying and addressing urban environmental noise pollution.
• The technique shows promise for real-world applications in noise management.