Multi-Microphone ANC Decoupling Background Noise
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Solution Overview
Problem
Active noise cancellation systems in earpiece-based audio devices face challenges in accurately modeling the acoustic path due to the dynamic and diverse nature of the surrounding environment, leading to residual noise and interference with the desired sound.
Innovation Solution
A multi-faceted analysis is performed using an array of monitoring microphones to decouple background noise from the acoustic wave generated by the audio transducer, forming a difference signal that indicates the acoustic energy level of the background noise, which is then used to determine the characteristics of the acoustic path and adjust the feedforward signal for optimal noise cancellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a reference microphone is used to capture background noise for feedforward ANC, then noise cancellation capability is improved, but the system cannot accurately distinguish between background noise and acoustic waves generated by the audio transducer in dynamic environments
Solution Approach 1:
The patent divides the monitoring function into multiple microphones positioned at different locations within the earpiece. By spatially segmenting the noise monitoring task, the system can capture acoustic signals from different positions and use signal processing to separate background noise from transducer-generated acoustic waves, thereby improving measurement precision while maintaining noise cancellation capability
Solution Approach 2:
The patent introduces an error microphone as an intermediary element that captures the actual acoustic environment at the listening position. This error microphone signal serves as a mediator to verify and adjust the transfer function model, allowing the system to distinguish between background noise and transducer output by comparing modeled versus actual acoustic conditions
2Reliability
If the transfer function is adjusted to improve noise cancellation, then residual noise is reduced, but the system becomes sensitive to environmental changes and unstable
Solution Approach 1:
The patent implements dynamic adaptation by continuously monitoring the error microphone signal and adjusting the transfer function parameters in real-time based on changing environmental conditions. This allows the system to maintain optimal noise cancellation performance across diverse acoustic environments by adapting to variations in background noise characteristics and acoustic paths
Solution Approach 2:
The patent employs feedback control by using the error microphone signal to continuously monitor the effectiveness of noise cancellation and adjust the feedforward filter coefficients accordingly. This closed-loop feedback mechanism enables the system to maintain stability while adapting to environmental changes, as the feedback signal provides real-time information about residual noise and system performance
3Measurement precision
If multiple microphones are used to monitor acoustic signals, then measurement accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent assigns specific functional roles to each microphone in the array, with the reference microphone dedicated to background noise capture and the error microphone dedicated to verification and transfer function adjustment. This functional segmentation simplifies the overall system architecture by clearly defining the purpose of each sensor, reducing the complexity that would otherwise arise from having multiple microphones with overlapping or ambiguous functions
Solution Approach 2:
The error microphone serves as an intermediary verification element that validates the transfer function model without directly participating in the primary noise cancellation feedforward path. This intermediary role simplifies the system by providing a dedicated verification channel that separates the modeling function from the cancellation function, reducing the computational and architectural complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for accurate modeling of the acoustic path and achieves optimal noise cancellation, enhancing the quality and robustness of active noise cancellation in diverse acoustic environments by selectively attenuating contributions from the audio transducer.
Implementation Method 1
A first monitoring signal and a second monitoring signal are received from a first monitoring microphone and a second monitoring microphone, respectively
Implementation Method 2
The anti-noise acoustic wave is intended to attenuate or eliminate the background noise at the listening position via destructive interference
Data Source
AI summary
The present technology provides systems and methods for robust feedforward active noise cancellation which can overcome or substantially alleviate problems associated with the diverse and dynamic nature of the surrounding acoustic environment. A multi-faceted analysis decouples the background noise within the earpiece from the acoustic wave (e.g. the anti-noise and desired audio) generated by an audio transducer within the earpiece. A difference signal is formed utilizing monitoring signals captured by array of monitoring microphones within the earpiece. The difference signal is formed such that contributions due to the acoustic wave generated by the audio transducer are selectively attenuated. As a result, the difference signal indicates an acoustic energy level of the background noise within the earpiece.