Virtual Microphone ANC Using Time-Frequency Subband Filtering
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Solution Overview
Problem
Conventional virtual microphone (VM) algorithms for active noise cancellation in vehicles face structural limitations in broadband noise reduction, particularly high-frequency noise, and impose significant computational burdens on computational resources.
Innovation Solution
A Time Frequency Subband Virtual Microphone (TFSVM) algorithm that processes signals in frequency subbands, using subband adaptive filtering to reduce computational demand and enhance noise cancellation performance, particularly in high-frequency ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional FXLMS algorithm is used for virtual microphone processing, then noise cancellation can be achieved, but computational resources are significantly burdened
Solution Approach 1:
The patent divides the frequency domain into multiple subbands and processes each subband separately using independent adaptive filters. This segmentation reduces the computational complexity of processing the entire frequency spectrum at once, while maintaining effective noise cancellation across the full bandwidth through the combined effect of all subband filters.
2Speed
If FXLMS algorithm processes signals sample-by-sample, then real-time noise cancellation is achieved, but computational power requirement increases
Solution Approach 1:
The signal processing is segmented into frequency subbands, allowing parallel processing of multiple frequency ranges simultaneously. This approach maintains real-time processing capability by distributing computational load across multiple subband filters rather than processing all samples sequentially through a single full-band filter.
Solution Approach 2:
The patent transitions from time-domain sample-by-sample processing to frequency-domain block processing using FFT. By transforming the processing dimension from time to frequency domain and organizing processing in blocks rather than individual samples, the system achieves real-time performance with reduced instantaneous computational power requirements.
3Reliability
If conventional VM algorithms are used, then broadband noise cancellation is attempted, but high-frequency noise reduction is limited due to structural limitations
Solution Approach 1:
The frequency spectrum is segmented into multiple subbands, each processed by dedicated adaptive filters. This segmentation allows each filter to be optimized for specific frequency ranges, particularly improving high-frequency noise reduction by providing specialized filtering capability rather than relying on a single full-band filter with inherent structural limitations.
Solution Approach 2:
Different subbands are processed with locally optimized filter parameters and adaptive algorithms tailored to the characteristics of each frequency range. This local optimization enables superior high-frequency noise cancellation by applying processing strategies specifically suited to high-frequency signal characteristics rather than using a uniform approach across all frequencies.
Data Source
AI summary
Methods and systems are disclosed for a vehicle audio system including, in one example, a method for noise cancellation in a vehicle having a reference sensor configured to acquire a reference signal, a plurality of speakers configured to emit a noise cancellation signal, and a plurality of error microphones configured to acquire a residual signal. The method processes the reference signal with a time domain adaptive weight filter to produce the noise cancellation signal, estimates a frequency domain filtered virtual microphone signal from the noise cancellation signal and the residual signal, and a frequency domain filtered reference signal from the reference signal. The method decomposes the frequency domain filtered virtual microphone signal and the frequency domain filtered reference signal into a plurality of frequency domain subband signals, and updates the time domain adaptive weight filter based on a weight transformation of a plurality of frequency domain subband adaptive filter weights.