An intrusive Gibbs sampling method for implementing the nonsynchronous measurements of microphone array
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Summary
This summary is machine-generated.Nonsynchronous microphone array measurements enable high-density arrays by recovering missing phase information. A novel Bayesian approach using intrusive Gibbs sampling effectively reconstructs acoustical sources.
Area Of Science
- Acoustics
- Signal Processing
- Computational Physics
Background
- Nonsynchronous microphone array measurements offer a solution for achieving large arrays or high microphone density through sequential scanning.
- This technique overcomes the frequency limitations imposed by traditional array aperture and microphone density.
Purpose Of The Study
- To address the critical challenge of recovering missing phase information in nonsynchronous measurements.
- To investigate the problem as solving a system of equations within a Bayesian framework.
Main Methods
- The intrusive Gibbs sampling method is proposed for source reconstruction.
- Convergence diagnostics for the Markov chain are illustrated using three distinct approaches.
- Acoustical source reconstruction error is analyzed concerning frequency range, signal-to-noise ratio, measurement distances, and sequential movement shift distance.
Main Results
- The proposed Gibbs sampling method yields results comparable to the expectation maximization algorithm for nonsynchronous measurements.
- Numerical simulations demonstrate the convergence of the Markov chain.
- Experimental validation in a semi-anechoic chamber confirms the method's effectiveness.
Conclusions
- The Bayesian approach with intrusive Gibbs sampling is an effective method for acoustical source reconstruction using nonsynchronous microphone array measurements.
- The study validates the proposed method's performance across various parameters and through experimental testing.
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