Recursive IIR Filter Training for Low-Power Active Noise Control
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Solution Overview
Problem
Existing active noise control (ANC) systems face significant power consumption issues with finite impulse response (FIR) filters and accumulate errors when converting to infinite impulse response (IIR) filters due to estimation of transfer functions, which is impractical for wireless devices.
Innovation Solution
Directly calculating IIR filters based on secondary path measurements without estimating primary path transfer functions, recursively updating coefficients using reference and error signals to improve noise suppression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FIR filters are used for noise cancellation, then noise suppression quality is improved, but power consumption increases significantly
Solution Approach 1:
The patent changes the filter type parameter from FIR to IIR, fundamentally altering the filter's impulse response characteristics. This parameter change enables the system to achieve comparable noise suppression with significantly reduced computational complexity and power consumption, as IIR filters require fewer coefficients and operations per sample
2Use of energy by moving object
If FIR filters are converted to IIR filters to reduce power consumption, then power efficiency is improved, but estimation errors and mapping errors accumulate
Solution Approach 1:
The patent performs preliminary action by directly calculating the IIR filter coefficients from the acoustic response measurement before the filtering operation begins. This preliminary calculation of accurate IIR coefficients based on measured acoustic characteristics eliminates the need for subsequent FIR-to-IIR mapping, preventing error accumulation while maintaining power efficiency
Solution Approach 2:
The patent substitutes the conventional FIR filter mechanism with an IIR filter mechanism that is directly optimized for the acoustic path. By replacing the FIR filtering approach with a directly calculated IIR filter, the system eliminates the intermediate mapping step that introduces errors, achieving both power efficiency and accuracy
3Adaptability or versatility
If transfer function estimation is performed to design filters, then filter adaptability to acoustic environment is improved, but system complexity and error accumulation increase
Solution Approach 1:
The patent extracts only the essential acoustic response characteristics needed for IIR filter design, eliminating unnecessary intermediate steps. By directly measuring the acoustic response and calculating IIR coefficients from this measurement, the system removes the complex transfer function estimation and FIR filter design stages, reducing overall system complexity while maintaining adaptability
Data Source
AI summary
This disclosure provides methods, devices, and systems for active noise control (ANC). The present implementations more specifically relate to filter adaptation techniques for recursively training an infinite impulse response (IIR) filter to convert a reference audio signal to an anti-noise signal. In some aspects, an ANC system may record, via a feedforward microphone, a reference audio signal representing external noise, and may further record, via a feedback microphone, an error signal representing residual noise resulting from passive attenuation of the external noise via a primary path between the microphones. The ANC system may further estimate an IIR filter that converts the reference audio signal to the error signal based on a secondary path. In some implementations, the ANC system may recursively update the IIR filter coefficients based, at least in part, on the coefficients associated with previous frames of the reference audio signal and the error signal.