Virtual Microphone Subband Filtering for Vehicle ANC
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional virtual microphone (VM) algorithms for active noise cancellation face structural limitations in broadband noise cancellation, particularly for high-frequency noise, and impose significant computational burdens on automotive systems.
Innovation Solution
A Time Frequency Subband Virtual Microphone (TFSVM) algorithm that processes signals in subbands, using frequency domain subband adaptive filters to update filters individually across frequency ranges, reducing computational load and enhancing noise reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional FXLMS algorithm is used for virtual microphone noise cancellation, then noise cancellation is achieved, but computational resources and processing burden are significantly increased
Solution Approach 1:
The patent segments the broadband noise cancellation problem into multiple frequency subbands. Instead of processing the entire frequency spectrum simultaneously with a single FXLMS algorithm, the system divides the signal into separate frequency bands and applies individual adaptive filters to each subband. This segmentation reduces the computational complexity of each filter while maintaining overall noise cancellation effectiveness across the full bandwidth.
2Speed
If FXLMS algorithm processes signals sample-by-sample, then real-time noise cancellation is achieved, but computational burden and power consumption increase significantly
Solution Approach 1:
The patent applies segmentation by dividing the frequency domain signals into multiple subbands. This allows the system to process fewer samples per subband compared to processing the entire spectrum at once, reducing the total number of computational operations required while maintaining real-time performance capability.
Solution Approach 2:
The patent implements partial action by focusing computational resources on processing only the necessary frequency subbands with reduced sampling rates. Instead of applying full computational effort to every sample across the entire frequency spectrum, the system applies adaptive filtering selectively to each subband, reducing overall power consumption while achieving adequate noise cancellation performance.
3Reliability
If conventional VM algorithms are used, then noise cancellation is attempted, but performance in reducing high frequency noise is limited due to structural limitations
Solution Approach 1:
The patent segments the frequency spectrum into multiple subbands, allowing dedicated adaptive filtering for high-frequency components. This segmentation enables the system to address high-frequency noise cancellation specifically, overcoming the structural limitations of conventional single-band VM algorithms that struggle with high-frequency performance.
Solution Approach 2:
The patent applies local quality by implementing frequency-dependent processing where each subband receives tailored adaptive filtering appropriate to its characteristics. High-frequency subbands receive processing optimized for their specific noise characteristics, improving overall high-frequency noise reduction performance compared to uniform processing approaches.
Data Source
Figure 1
Figure 2
Figure 3
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.