Systems and methods for subband virtual path calculation in active noise cancellation
View Patent ↗Methods and systems are disclosed for a vehicle audio system. In one example, a method for noise cancellation in a vehicle having a physical microphone configured to acquire a physical microphone signal, and a plurality of virtual microphones acquiring a residual signal is provided, including processing the physical microphone signal with an adaptive weight filter to estimate a virtual secondary path from the physical microphone to the plurality of virtual microphones, decomposing the residual signal and the physical microphone signal into a plurality of subband signals, determining a subband gradient for each subband, determining a subband virtual path convergence speed based on a normalized step size for each subband, determining a subband virtual path for each subband based on the normalized step size and the subband gradient, and applying a weight transformation process to each subband virtual path to update the adaptive weight filter and verify the subband virtual path.
1 . A method for noise cancellation in a vehicle having a physical microphone configured to acquire a physical microphone signal correlated to a filtered noise signal within a vehicle cabin, and a plurality of virtual microphones positioned within the vehicle cabin acquiring a residual signal, the method comprising:
processing the physical microphone signal with an adaptive weight filter to estimate a virtual secondary path from the physical microphone to the plurality of virtual microphones;
applying a set of analysis filters to decompose the residual signal into a plurality of subband error signals and to decompose the physical microphone signal into a plurality of subband physical microphone signals;
determining a subband gradient for each subband based on a subband physical microphone signal and a subband error signal;
calculating a normalized step size for each subband, based on a constant value that is adjusted based on a threshold normalized step size, the threshold normalized step size a non-zero, positive value threshold determined via a calibration operation;
determining a subband virtual path convergence speed based on the normalized step size for each subband;
determining a subband virtual path for each subband based on the normalized step size and the subband gradient; and
applying a subband weight transformation process to each subband virtual path to update the adaptive weight filter and verify the subband virtual path.
2 . The method of claim 1 , wherein the set of analysis filters includes a plurality of subband filters derived from a prototype filter using a window-based lowpass filter, each subband filter corresponding to a distinct frequency range within a residual noise spectrum of the vehicle cabin.
3 . The method of claim 2 , wherein the method further comprises selecting a window function for the prototype filter based on a predetermined frequency response characteristic for each subband.
4 . The method of claim 1 , wherein determining the normalized step size for each subband is based on a power contribution the subband physical microphone signal.
5 . The method of claim 1 , wherein the constant value is adjusted to exceed the threshold normalized step size.
6 . The method of claim 1 , wherein the subband gradient for each subband comprises performing a complex conjugate multiplication of the subband physical microphone signal and the subband error signal.
7 . The method of claim 1 , wherein the subband weight transformation process comprises performing a fast Fourier transformation on each subband virtual path to obtain a frequency-domain subband virtual path.
8 . The method of claim 7 , wherein the subband weight transformation process further comprises applying an inverse fast Fourier transformation to the frequency-domain subband virtual path to obtain the adaptive weight filter in a time-domain.
9 . The method of claim 1 , wherein the virtual secondary path is a time-domain estimated virtual secondary path.
10 . A noise cancellation system for a vehicle, comprising:
a physical microphone configured to acquire a physical microphone signal correlated to a filtered noise signal within a vehicle cabin;
a plurality of virtual microphones positioned within the vehicle cabin and configured to acquire a residual signal;
an adaptive weight filter in electronic communication with the physical microphone signal, configured to apply an adaptive filtering process to the physical microphone signal to estimate a virtual secondary path from the physical microphone to the plurality of virtual microphones; and
a signal processing unit in electronic communication with the physical microphone and the plurality of virtual microphones, wherein the signal processing unit comprises:
a non-transitory memory storing a set of analysis filters, and instructions; and
a processor, wherein, when executing the instructions, the processor is configured to:
apply the set of subband analysis filters to decompose the residual signal into a plurality of subband error signals and to decompose the physical microphone signal into a plurality of subband physical microphone signals;
determine a subband gradient for each subband based on a subband physical microphone signal and a subband error signal;
calculate a normalized step size for each subband, based on a constant value that is adjusted based on a threshold normalized step size, the threshold normalized step size a non-zero, positive value threshold determined via a calibration operation;
determine a subband virtual path convergence speed based on the normalized step size for each subband;
determine a subband virtual path for each subband based on the normalized step size and the subband gradient; and
apply a subband weight transformation process to each subband virtual path to update the adaptive weight filter and verify the subband virtual path.
11 . The noise cancellation system of claim 10 , wherein the set of analysis filters includes a plurality of subband filters derived from a prototype filter using a window-based lowpass filter, each subband filter corresponding to a distinct frequency range within a residual noise spectrum of the vehicle cabin.
12 . The noise cancellation system of claim 11 , wherein the prototype filter comprises a window function, the window function selected based on a predetermined frequency response characteristic for each subband.
13 . The noise cancellation system of claim 10 , wherein the normalized step size for each subband comprises a power contribution of the subband physical microphone signal.
14 . The noise cancellation system of claim 10 , wherein the subband gradient for each subband comprises a complex conjugate multiplication of the subband physical microphone signal and the subband error signal.
15 . The noise cancellation system of claim 10 , wherein the subband weight transformation process comprises a fast Fourier transformation of each subband virtual path to obtain a frequency-domain subband virtual path.
16 . The noise cancellation system of claim 15 , wherein the subband weight transformation process further comprises an inverse fast Fourier transformation of the frequency-domain subband virtual path to obtain the adaptive weight filter in a time-domain.
17 . The noise cancellation system of claim 10 , wherein the physical microphone signal comprises a product of filtering road noise by an anti-noise signal produced by a transducer.
18 . A method comprising:
acquiring a physical microphone signal using a physical microphone, wherein the physical microphone signal is correlated with a filtered noise signal in a vehicle cabin;
processing the physical microphone signal with an adaptive weight filter to estimate a virtual secondary path from the physical microphone to a plurality of virtual microphones;
acquiring a residual signal from the plurality of virtual microphones positioned in the vehicle cabin;
decomposing the physical microphone signal and the residual signal into a plurality of subband signals;
calculating a subband gradient for each subband based on a decomposed physical signal and a decomposed residual signal;
calculating a normalized step size for each subband based on a power contribution of the physical microphone signal and a constant value that is adjusted based on a threshold normalized step size, the threshold normalized step size a non-zero, positive value threshold determined via a calibration operation;
updating a set of subband virtual path weights based on the subband gradient and the normalized step size;
weight transforming the updated set of subband virtual path weights to a time domain using an Inverse Fast Fourier Transform (IFFT); and
processing the residual signal based on the transformed subband virtual weights to reduce noise in the vehicle cabin.
19 . The method of claim 18 , wherein the subband gradient for each subband comprises a complex conjugate multiplication of a subband physical microphone signal and a subband error signal.
20 . The method of claim 18 , wherein the decomposing comprises filtering the residual signal and the physical microphone signal through an analysis filter bank comprising a plurality of subband filters, each subband filter corresponding to a distinct frequency range within a residual noise spectrum of the vehicle cabin.