Real-Time Acoustic Processor for Low-Latency Active Noise Cancellation
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Solution Overview
Problem
Active noise cancellation (ANC) technologies face challenges in quickly reacting to ambient noise changes, leading to latency and erroneous noise amplification, especially when music is present, and struggle to distinguish noise from low-frequency music, resulting in incorrect cancellation of audio signals.
Innovation Solution
An acoustic processing network comprising a Digital Signal Processor (DSP) operating at a lower frequency and a Real-Time Acoustic Processor (RAP) operating at a higher frequency, where the DSP generates noise filters and the RAP quickly implements them to reduce latency, using biquad filters and compressor circuits to control amplifier adjustments and prioritize ambient awareness by enhancing specific frequency bands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single processor operates at lower frequency to generate noise filters, then processing complexity is reduced, but latency increases and noise cancellation accuracy deteriorates
Solution Approach 1:
The system divides processing into two segments: a first processor (DSP) operating at lower frequency for generating noise filters, and a second processor (RAP) operating at higher frequency for real-time anti-noise signal generation. This segmentation allows each processor to be optimized for its specific function, reducing overall latency while maintaining manageable complexity.
Solution Approach 2:
The noise filter generated by the first processor acts as an intermediary that transfers critical processing parameters to the second processor. This intermediary enables the high-frequency processor to rapidly generate anti-noise signals without performing complex filter generation calculations, thus reducing latency while maintaining processing simplicity.
2Reliability
If correction circuits react quickly to ambient noise changes, then noise cancellation accuracy improves, but erroneous noise amplification and signal artifacts increase
Solution Approach 1:
The system dynamically adjusts processing based on ambient noise characteristics. The high-frequency processor rapidly adapts to changing noise conditions while the noise filter from the low-frequency processor provides stable baseline parameters, enabling quick response without overreacting to transient variations that cause artifacts.
Solution Approach 2:
The system changes processing parameters dynamically by transferring updated noise filter coefficients from the first processor to the second processor. This allows the high-frequency processor to adjust its operation in response to changing noise conditions while maintaining stability through the structured parameter transfer mechanism.
3Device complexity
If ANC processes all frequency bands uniformly, then processing simplicity is maintained, but low-frequency music is erroneously canceled along with noise
Solution Approach 1:
The system applies different processing qualities to different frequency bands. The noise filter generated by the first processor and applied by the second processor enables selective processing that preserves low-frequency music while canceling noise in other frequency ranges, achieving frequency-specific optimization.
Solution Approach 2:
The first processor performs preliminary analysis of the noise signal and generates appropriate noise filters before the second processor generates anti-noise signals. This preliminary action allows the system to distinguish between noise and music components in advance, preventing erroneous cancellation of audio signals.
Data Source
AI summary
The disclosure includes an acoustic processing network comprising a Digital Signal Processor (DSP) operating at a first frequency and a Real-Time Acoustic Processor (RAP) operating at a second frequency higher than the first frequency. The DSP receives a noise signal from at least one microphone. The DSP then generates a noise filter based on the noise signal. The RAP receives the noise signal from the microphone and the noise filter from the DSP. The RAP then generates an anti-noise signal based on the noise signal and the noise filter for use in Active Noise Cancellation (ANC).