Beamforming Microphone Arrays With Wind Buffeting Protection
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Solution Overview
Problem
Existing noise reduction methods for microphone arrays with small spacing struggle with wind buffeting and microphone tolerances, leading to degraded performance in beam forming applications, especially in environments like vehicles where wind turbulence and microphone sensitivity differences cause disturbances.
Innovation Solution
A method that transforms sound signals from microphones into complex-valued frequency-domain signals, calculates wind reduction spectra and beam focus spectra, and applies attenuation factors to reduce wind buffeting and compensate for microphone tolerances, using a Characteristic Function to limit beam focus values and prevent signal degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If small microphone spacing is used in microphone arrays, then the device size is reduced and portability is improved, but wind buffeting effects increase and signal quality degrades
Solution Approach 1:
The patent segments the microphone array into multiple individual microphone channels, each processed independently through separate transfer functions and spectral analysis. This allows selective attenuation of wind buffeting frequencies for each microphone while preserving the overall compact array structure and small spacing configuration.
Solution Approach 2:
The patent applies frequency-dependent transfer functions that dynamically adjust attenuation parameters based on the spectral characteristics of each microphone signal. By changing the filtering parameters adaptively across different frequency bands, the system reduces wind buffeting effects at specific frequencies while maintaining signal integrity at other frequencies, enabling small microphone spacing to be used effectively.
2Measurement precision
If microphone spacing is increased to improve voice pick-up distinction, then signal differentiation is improved, but device size increases and wind buffeting exposure increases
Solution Approach 1:
The patent replaces the mechanical solution of increasing microphone spacing with a signal processing approach using transfer functions and spectral attenuation. Instead of physically separating microphones to differentiate voice signals, the system uses digital signal processing to achieve signal differentiation while maintaining compact microphone spacing, thereby reducing device size and wind buffeting exposure.
3Device complexity
If simple noise subtraction is applied between microphones, then processing complexity is reduced, but noise reduction effectiveness decreases due to unknown noise impact direction
Solution Approach 1:
The patent implements a feedback mechanism where the output of each microphone channel is processed through transfer functions and spectral analysis, with the results fed back into adaptive attenuation calculations. This feedback loop allows the system to learn and adapt to the actual noise characteristics and directions, improving noise reduction effectiveness while maintaining manageable processing complexity through systematic feedback control.
4Measurement precision
If advanced spectral processing is applied to reduce wind buffeting, then signal quality is improved, but processing complexity and computational load increase
Solution Approach 1:
The patent applies local quality processing by implementing frequency-selective attenuation where different processing strategies are applied to different frequency bands. Critical frequency ranges affected by wind buffeting receive advanced spectral processing, while other frequency ranges use simpler processing. This localized approach improves signal quality in problematic frequency regions while minimizing overall processing complexity and computational load.
Data Source
AI summary
A method and apparatus are provided for generating a directional output signal from sound received by at least two microphones arranged as microphone array. The method includes transforming the sound received by each of said microphones and represented by analog-to-digital converted time-domain signals provided by each of said microphones into corresponding complex-valued frequency-domain microphone signals each having a frequency component value for each of a plurality of frequency components, calculating, for each of the plurality of frequency components, real-valued Wind Reduction Factors as minima of the reciprocal and non-reciprocal frequency components of a plurality of real-valued Deviation Spectra if said minimum is below a preselected deviation threshold and set to one if said minimum is above or equal to said deviation threshold, and for each of the plurality of frequency components, forming a frequency-domain wind-reduced output signal.


