WO2023050253A1 - 一种噪声控制的方法和装置 - Google Patents

一种噪声控制的方法和装置 Download PDF

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Publication number
WO2023050253A1
WO2023050253A1 PCT/CN2021/122033 CN2021122033W WO2023050253A1 WO 2023050253 A1 WO2023050253 A1 WO 2023050253A1 CN 2021122033 W CN2021122033 W CN 2021122033W WO 2023050253 A1 WO2023050253 A1 WO 2023050253A1
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signal
filter
noise
filtered signal
filtered
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PCT/CN2021/122033
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English (en)
French (fr)
Inventor
周朝辉
邹海山
石黎
陶建成
吴晟
仲旭
邱小军
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华为技术有限公司
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Priority to CN202180102814.4A priority Critical patent/CN118043883A/zh
Priority to PCT/CN2021/122033 priority patent/WO2023050253A1/zh
Publication of WO2023050253A1 publication Critical patent/WO2023050253A1/zh

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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase

Definitions

  • the present application relates to the field of artificial intelligence, and more specifically, to a noise control method and device.
  • German physicist Lueg first proposed the concept of active noise control (ANC), which uses the principle of destructive interference of sound waves to reduce noise.
  • ANC active noise control
  • the main application areas are: active noise reduction headphones, active control of vehicle noise.
  • active control of machine noise active sound barriers, active control of building openings, etc.
  • Active noise control can be divided into feedforward active noise control and feedback active noise control, where the performance of feedforward active noise control depends on the coherence between the reference signal and the primary noise signal.
  • feedforward active noise control depends on the coherence between the reference signal and the primary noise signal.
  • the hardware cost and algorithm complexity are high.
  • the installation position of the reference accelerometer needs a lot of experimental measurements to be optimized. The workload is relatively large.
  • the feedback active noise control system has a simple structure and does not need a reference signal. However, the system has a water bed effect, that is, noise reduction in a specific frequency band will cause noise amplification in other frequency bands.
  • the present application provides a noise control method and device, which help to suppress the water bed effect generated in the noise control process.
  • a noise control method which is characterized in that it includes: acquiring an error signal, and the error signal is collected by an error sensor; determining a first reference signal according to the error signal; Stage path transfer function filtering to obtain the first filtered signal; the first filtered signal and the error signal are respectively filtered by the first filter to obtain the second filtered signal and the third filtered signal, and the amplitude-frequency response of the first filter It is associated with the power spectral density of the original noise signal; according to the second filtered signal and the third filtered signal, the coefficients of the feedback filter are updated; the first reference signal is filtered by the updated feedback filter to obtain the first noise signal.
  • the first reference signal is passed through the updated feedback filter by filtering the first filter signal and the error signal respectively through the first filter, and updating the coefficients of the feedback filter according to the filtered signal. Filter the noise signal.
  • the first filter is obtained through the power spectral density of the original noise signal, without manually observing the position of the water bed effect, which helps to control the noise amplification caused by the water bed effect.
  • the noise control method in the embodiments of the present application may be applied to vehicles.
  • the above-mentioned vehicles may include one or more different types of vehicles, and may also include one or more different types of vehicles on land (for example, roads, roads, railways, etc.), water surfaces (for example: waterways, rivers, etc.) , ocean, etc.) or means of transport or movable objects that operate or move in space.
  • a vehicle may include a car, a bicycle, a motorcycle, a train, a subway, an airplane, a ship, an aircraft, a robot, or other types of transportation means or movable objects, which are not limited in this embodiment of the present application.
  • the square of the amplitude-frequency response of the first filter is equal to the reciprocal of the power spectral density of the original noise signal.
  • the first filter is a whitening filter.
  • the method further includes: filtering the first filtered signal and the error signal through a second filter to obtain a fourth filtered signal and a fifth filtered signal,
  • the absolute value of the difference between the amplitude of the first noise reduction frequency band and the amplitude of the second noise reduction frequency band is greater than or equal to the preset difference; wherein, according to the second filter signal and the third filter A signal to update the coefficients of the feedback filter includes: updating the coefficients of the feedback filter according to the second filtered signal, the third filtered signal, the fourth filtered signal and the fifth filtered signal.
  • the second filter may be a spectrum shaping filter.
  • updating the coefficients of the feedback filter according to the second filtered signal, the third filtered signal, the fourth filtered signal and the fifth filtered signal includes: updating the coefficients of the feedback filter according to the following formula:
  • w b (n+1) w b (n)-2 ⁇ b [e A (n)r A_b (n)+ ⁇ e'(n)r' b (n)]
  • w b (n+1) is the updated coefficient of the feedback filter
  • w b (n) is the coefficient before the update of the feedback filter
  • ⁇ b is the iteration step size of the feedback control filter
  • ⁇ is the sensitivity amplitude constraint weight
  • r' b (n) is the second filtered signal
  • e' (n) is the third filtered signal
  • r A_b (n) is the fourth filtered signal
  • e A (n) is the fifth filtered signal.
  • the updated first reference signal by filtering the first filter signal and the error signal through the first filter and the second filter respectively, and updating the coefficient of the feedback filter according to the filtered signal, the updated first reference signal.
  • the noise signal is filtered by the feedback filter, which helps to control the noise amplification caused by the water bed effect.
  • the method further includes: acquiring a second reference signal picked up by the reference sensor; filtering the second reference signal through the secondary path transfer function to obtain a sixth filtered signal; the sixth filtered signal is filtered by the second filter to obtain the seventh filtered signal; according to the fifth filtered signal and the seventh filtered signal, the coefficient of the feedforward filter is updated; the second reference signal is passed through The updated feedforward filter filters to obtain the second noise signal.
  • the method further includes: obtaining a third noise signal according to the first noise signal and the second noise signal; and sending the third noise signal to a secondary sound source.
  • the secondary sound source may be a loudspeaker.
  • the embodiment of the present application provides a feedback-forward mixed noise control system, which is an adaptive feedback-forward mixed noise control system and can be used in a real-time adaptive system.
  • the noise amplification caused by the water bed effect is constrained by the first filter, and the noise reduction frequency band is selected by the second filter, so as to achieve a better noise reduction effect.
  • the method further includes: filtering the sixth filtered signal through the first filter to obtain an eighth filtered signal; wherein, according to the fifth filtered signal and the seventh filtered signal, updating the coefficients of the feedforward filter includes: updating the coefficients of the feedforward filter according to the third filtered signal, the fifth filtered signal, the seventh filtered signal and the eighth filtered signal .
  • updating the coefficients of the feedforward filter according to the third filtered signal, the fifth filtered signal, the seventh filtered signal and the eighth filtered signal includes:
  • w f (n+1) w f (n)-2 ⁇ f [e A (n)r A_f (n)+ ⁇ e'(n)r' f (n)]
  • w f (n+1) is the updated coefficient of the feedforward filter
  • w f (n) is the coefficient before the update of the feedforward filter
  • ⁇ f is the iteration step size of the feedforward control filter
  • ⁇ is the sensitivity amplitude Value constraint weight
  • r A_f (n) is the seventh filtered signal
  • e'(n) is the third filtered signal
  • r' f (n) is the eighth filtered signal
  • e A (n) is the fifth filtered signal.
  • the method before determining the first reference signal according to the error signal, the method further includes: acquiring a fourth noise signal, and the error signal is passed through by the fourth noise signal The signal obtained after the secondary path is superimposed on the original noise signal; wherein, according to the error signal, determining the first reference signal includes: filtering the fourth noise signal through the secondary path transfer function to obtain the ninth Filtered signal: Obtain the first reference signal according to the ninth filtered signal and the error signal.
  • the fourth noise signal may be a noise signal at a previous moment.
  • a noise control device which includes: a first acquiring unit, configured to acquire an error signal; a determining unit, configured to determine a first reference signal according to the error signal; a first filtering unit configured to The first reference signal is filtered by a secondary path transfer function to obtain a first filtered signal; the second filtering unit is configured to filter the first filtered signal and the error signal through a first filter respectively to obtain a second filtered signal signal and a third filtered signal, the amplitude-frequency response of the first filter is associated with the power spectral density of the original noise signal; the first processing unit is configured to update the feedback filter according to the second filtered signal and the third filtered signal The coefficient of the filter; the third filtering unit, which filters the first reference signal through the updated feedback filter to obtain the first noise signal.
  • the second filtering unit is further configured to filter the first filtered signal and the error signal through a second filter to obtain a fourth filtered signal and a first filtered signal.
  • Five filtered signals the absolute value of the difference between the amplitude of the first noise reduction frequency band and the amplitude of the second noise reduction frequency band in the second filter is greater than or equal to the preset difference; wherein the first processing unit is specifically used to : Update coefficients of the feedback filter according to the second filtered signal, the third filtered signal, the fourth filtered signal and the fifth filtered signal.
  • the device further includes: a second acquisition unit, configured to acquire a second reference signal picked up by the reference sensor; a fourth filtering unit, configured to use the second reference signal The signal is filtered by the secondary path transfer function to obtain a sixth filtered signal; the fifth filtering unit is configured to filter the sixth filtered signal through the second filter to obtain a seventh filtered signal; the second processing unit, according to the The fifth filtered signal and the seventh filtered signal update the coefficients of the feedforward filter; the sixth filtering unit is used to filter the second reference signal through the updated feedforward filter to obtain a second noise signal; Three processing units, configured to obtain a third noise signal according to the first noise signal and the second noise signal; and a sending unit, configured to send the third noise signal to a secondary sound source.
  • a second acquisition unit configured to acquire a second reference signal picked up by the reference sensor
  • a fourth filtering unit configured to use the second reference signal The signal is filtered by the secondary path transfer function to obtain a sixth filtered signal
  • the fifth filtering unit is configured to filter the
  • the fifth filtering unit is configured to filter the sixth filtered signal through the first filter to obtain an eighth filtered signal; wherein the second processing unit Specifically, it is used for: updating the coefficients of the feedforward filter according to the third filtered signal, the fifth filtered signal, the seventh filtered signal and the eighth filtered signal.
  • the device further includes: a third acquisition unit, configured to acquire a fourth noise signal, and the error signal is obtained by passing the fourth noise signal through a secondary path The signal is obtained by superimposing the original noise signal; wherein, the determination unit is specifically configured to: filter the fourth noise signal through the secondary path transfer function to obtain a ninth filtered signal; according to the ninth filtered signal and the error signal , to obtain the first reference signal.
  • the square of the amplitude-frequency response of the first filter is equal to the reciprocal of the power spectral density of the original noise signal.
  • a device for noise control which includes: a memory for storing computer programs; a processor for executing the computer programs stored in the memory, so that the device performs the above-mentioned first aspect. method.
  • a vehicle in a fourth aspect, includes the device described in any one of the second aspect or the third aspect above.
  • a computer program product comprising: computer program code, when the computer program code is run on a computer, the computer is made to execute the method in the above first aspect.
  • a computer-readable medium stores program codes, and when the computer program codes are run on a computer, the computer is made to execute the method in the above-mentioned first aspect.
  • an embodiment of the present application provides a chip system, the chip system includes a processor, configured to call a computer program or a computer instruction stored in a memory, so that the processor executes the method described in any one of the above aspects.
  • the processor is coupled to the memory through an interface.
  • the system on a chip further includes a memory, where computer programs or computer instructions are stored in the memory.
  • Fig. 1 is a schematic structural diagram of a noise control device provided by an embodiment of the present application.
  • Fig. 2 is a schematic diagram of a feedforward noise control system provided by an embodiment of the present application.
  • Fig. 3 is a schematic diagram of a feedback noise control system provided by an embodiment of the present application.
  • Fig. 4 is a schematic diagram of a feedback-forward mixed noise control method provided by an embodiment of the present application.
  • Fig. 5 is a schematic diagram of a feedback-forward mixed noise control system provided by an embodiment of the present application.
  • FIG. 6 is a schematic diagram of an amplitude-frequency response of a spectrum shaping filter provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of the amplitude-frequency response of the whitening filter provided by the embodiment of the present application.
  • FIG. 8 is a schematic diagram of power spectral densities of noise signals before and after noise reduction provided by an embodiment of the present application.
  • Fig. 9 is a schematic diagram of the amplitude-frequency response of the sensitivity function of the feedback-forward mixed noise control system provided by the embodiment of the present application.
  • Fig. 10 is a schematic flowchart of a noise control method provided by an embodiment of the present application.
  • Fig. 11 is a schematic flowchart of a noise control device provided by an embodiment of the present application.
  • Fig. 12 is another schematic flowchart of the noise control device provided by the embodiment of the present application.
  • FIG. 1 is a schematic structural diagram of a noise control device 100 provided by an embodiment of the present application.
  • the device 100 may include a sensor 110 and a processor 120 .
  • the sensor 110 may include a reference sensor 111 and an error sensor 112, the reference sensor 111 is used to obtain a reference signal and send the reference signal to the processor, and the error sensor 112 is used to obtain an error signal and send the error signal to the processor.
  • the processor 120 is configured to process the reference signal and the error signal, and send the processed signal to the secondary sound source (for example, a loudspeaker).
  • the secondary sound source for example, a loudspeaker
  • the reference sensor 111 may be a reference accelerometer.
  • the error sensor 112 may be an error microphone.
  • the above-mentioned device 100 may be a device located in an active noise reduction earphone, an active control system for vehicle noise, or an active control system for machine noise, an active sound barrier, or an active control system for building openings device in .
  • the active control system for vehicle noise may be located in an active noise reduction headrest.
  • the above-mentioned vehicles may include one or more different types of vehicles, and may also include one or more different types of vehicles on land (for example, roads, roads, railways, etc.), water surfaces (for example: waterways, rivers, etc.) , ocean, etc.) or means of transport or movable objects that operate or move in space.
  • a vehicle may include a car, a bicycle, a motorcycle, a train, a subway, an airplane, a ship, an aircraft, a robot, or other types of transportation means or movable objects, which are not limited in this embodiment of the present application.
  • Fig. 2 shows a schematic structural diagram of a feedforward noise control system provided by an embodiment of the present application.
  • the processor obtains the feedforward reference signal x f (n) and the error signal e(n) picked up by the reference sensor and the error sensor respectively, and transmits the feedforward reference signal x f (n) through the secondary path model function Filtering obtains a filtered signal x 1 .
  • the processor filters the error signal e(n) and the filtered signal x1 through the spectrum shaping filter A(z) and the whitening filter F(z) respectively.
  • the error signal e(n) is filtered by the spectrum shaping filter A(z) to obtain a filtered signal e A (n) and filtered by a whitening filter F(z) to obtain a filtered signal e'(n).
  • the filtered signal x 1 is filtered by the spectrum shaping filter A(z) to obtain the filtered signal r A_f (n) and filtered by the whitening filter F(z) to obtain the filtered signal r f' (n).
  • the processor can update the coefficients of the feed-forward filter LMS 1 according to the filtered signals e A (n), e'(n), r A_f (n) and r f' (n).
  • the processor may filter the reference signal x f (n) through a feed-forward filter whose coefficients are updated, so as to output a control signal y 1 (n) that is fed back to the secondary sound source.
  • the reference signal and the error signal may also be filtered through a spectrum shaping filter instead of a whitening filter.
  • the coefficients of the feedforward filter are updated by the filtered signal obtained after filtering by the spectrum shaping filter.
  • w f (n+1) is the feed-forward filter coefficient at time n+1
  • w f (n) is the feed-forward filter coefficient at time n
  • ⁇ f is the iteration step size of the feed-forward control filter
  • ⁇ is the feed-forward
  • r A_f (n) is the feedforward reference signal x f (n) filtered by the secondary path model and A(z) signal
  • r f' (n) is the feedforward reference signal x f (n) is the signal filtered by the secondary path model and F(z).
  • the spectrum shaping filter A(z) is used to select a frequency band for noise reduction, and the spectrum shaping filter A(z) can be designed according to the frequency band that needs noise reduction. For example, the amplitude in the target noise reduction frequency band A(z) is larger, and the amplitude in the non-target noise reduction frequency band A(z) is smaller.
  • the absolute value of the difference between the amplitude of the target frequency band and the amplitude of the non-target frequency band may be set to be greater than or equal to a certain preset amplitude (for example, 20dB).
  • the target noise reduction frequency band may be [100 Hz, 1000 Hz]
  • the non-target noise reduction frequency band may be [0 Hz, 100 Hz).
  • the coefficients of the whitening filter F(z) can be calculated by linear prediction.
  • the coefficients of the whitening filter F(z) can be obtained by the reciprocal of the power spectral density of the primary noise signal x b (n).
  • FIG. 2 also shows the process of obtaining the primary noise signal x b (n) in the feedforward noise control.
  • the control signal y 1 (n) fed back to the secondary sound source passes through the secondary path model transfer function After filtering, a filtered signal x 2 is obtained.
  • the primary noise signal x b (n) can be obtained by subtracting the filtered signal x 2 from the error signal e(n) picked up by the error sensor.
  • the error signal e(n) may be obtained by superimposing the signal obtained after the control signal y 1 (n) passes through the secondary path C(z) and the original noise signal p(n) in the air.
  • the sensitivity amplitude constraint weight ⁇ of the feedforward filter or the feedback filter can also be set as required.
  • a sensitivity constraint penalty item is added to the cost function.
  • the sensitivity constraint weight ⁇ is used to give a weight to the sensitivity constraint penalty term in the cost function. If ⁇ is small, the penalty term has little effect, and the water bed effect is not constrained well; if ⁇ is large, the penalty term accounts for a large proportion, and the error signal energy accounts for a small proportion, which affects the noise reduction effect.
  • ⁇ can be determined by calculating the autocorrelation matrix of the original noise signal.
  • ⁇ may take 1/100 of the maximum eigenvalue of the autocorrelation matrix of the original noise signal.
  • the processor obtains the primary noise signal x b (n) and the error signal e(n) picked up by the error sensor, and passes the primary noise signal x b (n) through the secondary path model transfer function Filtering results in a filtered signal x 3 .
  • the processor filters the error signal e(n) and the filtered signal x3 through the spectrum shaping filter A(z) and the whitening filter F(z) respectively.
  • the error signal e(n) is filtered by the spectrum shaping filter A(z) to obtain a filtered signal e A (n) and filtered by a whitening filter F(z) to obtain a filtered signal e'(n).
  • the filtered signal x 3 is filtered by the spectrum shaping filter A(z) to obtain the filtered signal r A_b (n) and filtered by the whitening filter F(z) to obtain the filtered signal r b '(n).
  • the processor can update the coefficients of the feedback filter LMS 2 according to the filtered signals e A (n), e'(n), r A_b (n) and r' b (n).
  • the processor can filter the primary noise signal x b (n) through a feedback filter whose coefficients are updated, so as to output a control signal y 2 (n) that is fed back to the secondary sound source.
  • the feedback filter system can be iterated according to the following formula (2):
  • w b (n+1) w b (n)-2 ⁇ b [e A (n)r A_b (n)+ ⁇ e'(n)r' b (n)] (2)
  • w b (n+1) is the feedback filter coefficient at time n+1
  • w b (n) is the feedback filter coefficient at time n
  • ⁇ b is the iteration step size of the feedback control filter
  • ⁇ is the sensitivity of the feedback filter Amplitude constraint weight
  • r A_b (n) is the primary noise signal x b (n) after the secondary path model and A(z) filtered signal
  • r' b (n) is the primary noise signal x b (n) after the Secondary path model and F(z) filtered signal.
  • FIG. 3 also shows the process of obtaining the primary noise signal x b (n) in the feedback noise control.
  • the control signal y 2 (n) fed back to the secondary sound source passes through the secondary path model transfer function After filtering, a filtered signal x 2 is obtained.
  • the primary noise signal x b (n) can be obtained by subtracting the filtered signal x 2 from the error signal e(n) picked up by the error sensor.
  • the error signal e(n) may be obtained by superimposing the signal obtained after the control signal y 2 (n) passes through the secondary path C(z) and the original noise signal p(n) in the air.
  • the feedback-forward mixed noise control method may include the above-mentioned feedforward noise control and feedback noise control.
  • the feed-forward noise control uses a reference sensor to pick up a reference signal, and the reference signal passes through a secondary path model to obtain a filtered signal x 1 .
  • the filtered signal x1 and the error signal are respectively filtered by a spectrum shaping filter and a whitening filter before being used for updating the coefficients of the feedforward filter.
  • the reference signal is filtered by a feed-forward filter with updated coefficients to obtain a first control signal (for example, the above y 1 (n)).
  • Feedback noise control can be based on an internal model control (IMC) structure
  • the primary noise signal can be used as a reference signal for the feedback part
  • the primary noise signal and error signal can be filtered by spectrum shaping before being used for updating the feedback filter coefficients filter and whitening filter.
  • the primary noise signal is filtered by a feedback filter with updated coefficients to obtain a second control signal (for example, the above y 2 (n)).
  • the third control signal y(n) is obtained by superimposing the first control signal output in the feedforward noise control and the second control signal output in the feedback noise control, so that the third control signal is fed back to the secondary source.
  • the feedback-forward mixed noise control system shown in FIG. 5 may be a combination of the feed-forward noise control system shown in FIG. 2 and the feedback noise control system shown in FIG. 3 .
  • the primary noise signal x b (n) can be obtained by subtracting the filtered signal x 2 from the error signal e(n) picked up by the error sensor.
  • the control signal y 1 (n) obtained by feedforward noise control and the control signal y 2 (n) obtained by feedback noise control are superimposed to obtain the control signal y(n) at time n, and the control signal y(n) passes through Secondary path model transfer function After filtering, the filtered signal x 2 can be obtained.
  • the coefficient (or amplitude-frequency response) of the whitening filter may be obtained according to the spectral characteristics of the original noise (for example, taking the reciprocal of the power spectral density of the original noise).
  • the feedback-forward mixed noise control system can also continuously iterate the parameters of the feed-forward filter and the feedback filter, so that the cost function in the following formula (3) is minimized:
  • the noise reduction effect of the embodiment of the present application will be described below by taking the noise reduction simulation of the measured vehicle interior noise and the measured transfer function of the active headrest in the vehicle when the test vehicle is driving on a rough road at a speed of 50 km/h as an example.
  • the system includes a secondary sound source and an error microphone.
  • the error microphone is about 8cm away from the center of the diaphragm of the secondary sound source.
  • Eleven 3-axis accelerometers are arranged at the main connection between the vehicle load-bearing frame and the body structure to pick up reference signals. Eight acceleration signals are used as reference signals, and the sampling rate is set to 12500Hz.
  • the spectrum shaping filter A(z) used to select the noise reduction frequency band is set to a cutoff frequency of 70Hz, the transition band is 30Hz, and the stopband attenuation is about 20dB high-pass filter.
  • the amplitude-frequency response of the spectrum shaping filter A(z) is shown in Figure 6.
  • the magnitude-frequency response of the whitening filter F(z) obtained through linear prediction calculation using the primary noise signal is shown in Fig. 7 .
  • the length of the feedback filter is set to 512
  • the length of the feed-forward filter is 512
  • the filter length of the spectrum shaping filter A(z) is 1024
  • the filter length of the whitening filter F(z) is 1024
  • the sensitivity function The amplitude constraint weight factor ⁇ is 53.8
  • the iterative step size ⁇ f of the feedforward filter is 0.1
  • the iterative step size ⁇ b of the feedback filter is 0.8.
  • the total duration of the initial noise recording is 93.6s.
  • (a) in Figure 8 shows the power spectral density of the noise signal before and after noise reduction in the frequency band [0Hz, 1000Hz] of the signal from 83.6s to 93.6s of the noise recording, and gives the feedforward noise The noise reduction results of the control system and the feedback noise control system are compared.
  • (b) in Fig. 8 shows the noise signal power spectral density before and after noise reduction in the [70Hz, 500Hz] frequency band. In Fig.
  • Primary represents the noise signal before noise reduction
  • Feedback represents the signal after noise reduction using the feedback noise control system provided by the embodiment of the present application
  • Feedforward represents the signal after noise reduction of the feedforward noise control system provided by the embodiment of the present application
  • Hybrid represents the signal after noise reduction using the feedback noise control system provided by the embodiment of the present application
  • the feedback-forward mixed noise control system in the embodiment of this application can further significantly reduce the residual noise in the 70Hz to 300Hz frequency band on the basis of the feedforward noise control system, and its noise reduction in the 70Hz to 500Hz target frequency range is 9.1dB, which is high Compared with 5.2dB of feedback noise control system and 5.3dB of feedforward noise control system.
  • the noise reduction amount of the feedback-forward mixed noise control system in the embodiment of the present application is a maximum of 18.1dB at 171Hz, which is higher than the maximum value of 12.2dB of the feedforward noise control system and the maximum value of 14.9dB of the feedback noise control system, and effectively
  • the peak value of the noise amplification in the full frequency band is limited below 4.4dB, and the amplitude-frequency response of the sensitivity function is shown in Fig. 9 .
  • Fig. 10 shows a schematic flowchart of a noise control method 1000 provided by an embodiment of the present application. As shown in Fig. 10, the method 1000 includes:
  • the error sensor may be an error microphone.
  • the error signal may be e(n).
  • the first reference signal may be x b (n).
  • control signal y 2 (n) fed back to the secondary sound source passes through the secondary path model transfer function After filtering, a filtered signal x 2 is obtained.
  • the first reference signal x b (n) can be obtained by subtracting the filtered signal x 2 from the error signal e(n) picked up by the error sensor.
  • the first filtered signal may be the first reference signal x b (n) through the secondary path model transfer function The resulting signal after filtering.
  • the first filter is a whitening filter.
  • the difference between the square of the amplitude-frequency response of the first filter and the reciprocal of the power spectral density of the original noise signal is less than or equal to a preset value.
  • the square of the amplitude-frequency response of the first filter is equal to the reciprocal of the power spectral density of the original noise signal.
  • the coefficients of the feedback filter may be updated according to the second filtered signal r' b (n) and the third filtered signal e'(n).
  • the method further includes: filtering the first filtered signal and the error signal through a second filter respectively to obtain a fourth filtered signal and a fifth filtered signal, in which the first noise reduction frequency band in the second filter
  • the absolute value of the difference between the amplitude and the amplitude of the second noise reduction frequency band is greater than or equal to the preset difference; wherein, according to the second filtered signal and the third filtered signal, updating the coefficient of the feedback filter includes: according to The second filtered signal, the third filtered signal, the fourth filtered signal and the fifth filtered signal update coefficients of the feedback filter.
  • the fourth filtered signal may be r A_b (n), and the fifth filtered signal may be e A (n).
  • the first noise reduction frequency band may be a target noise reduction frequency band.
  • the target noise reduction frequency band may be [100Hz, 1000Hz].
  • the second noise reduction frequency band may be a non-target noise reduction frequency band.
  • the target noise reduction frequency band may be [0 Hz, 100 Hz].
  • the second filter may be a spectrum shaping filter.
  • updating the coefficients of the feedback filter according to the second filtered signal, the third filtered signal, the fourth filtered signal and the fifth filtered signal includes: updating the coefficients of the feedback filter according to the following formula:
  • w b (n+1) w b (n)-2 ⁇ b [e A (n)r A_b (n)+ ⁇ e'(n)r' b (n)]
  • w b (n+1) is the updated coefficient of the feedback filter
  • w b (n) is the coefficient before the update of the feedback filter
  • ⁇ b is the iteration step size of the feedback control filter
  • ⁇ is the sensitivity amplitude constraint weight
  • the updated first reference signal by filtering the first filter signal and the error signal through the first filter and the second filter respectively, and updating the coefficient of the feedback filter according to the filtered signal, the updated first reference signal.
  • the noise signal is filtered by the feedback filter. This helps control noise amplification caused by the water bed effect.
  • the first reference signal is passed through the updated feedback filter by filtering the first filter signal and the error signal respectively through the first filter, and updating the coefficients of the feedback filter according to the filtered signal. Filter the noise signal.
  • the first filter is obtained through the power spectral density of the original noise signal, which helps to control the noise amplification caused by the water bed effect.
  • the method further includes: acquiring a second reference signal picked up by the reference sensor; filtering the second reference signal through the secondary path transfer function to obtain a sixth filtered signal; passing the sixth filtered signal through the second filter to obtain a seventh filtered signal; update the coefficients of the feedforward filter according to the fifth filtered signal and the seventh filtered signal; filter the second reference signal through the updated feedforward filter to obtain the seventh Two noise signals.
  • the reference sensor may be an accelerometer, or, the reference sensor may be an accelerometer and a microphone.
  • the second filter may be a spectrum shaping filter.
  • the second reference signal may be x f (n), and the seventh filtered signal may be r A_f (n).
  • the eighth filtered signal may be r' f (n).
  • updating the coefficients of the feedforward filter according to the third filtered signal, the fifth filtered signal, the seventh filtered signal and the eighth filtered signal includes: updating the coefficients of the feedforward filter according to the following formula :
  • w f (n+1) w f (n)-2 ⁇ f [e A (n)r A_f (n)+ ⁇ e'(n)r' f (n)]
  • w f (n+1) is the updated coefficient of the feedforward filter
  • w f (n) is the coefficient before the update of the feedforward filter
  • ⁇ f is the iteration step size of the feedforward control filter
  • ⁇ is the sensitivity amplitude Value constraint weight
  • the method before determining the first reference signal according to the error signal, the method further includes: acquiring a fourth noise signal, wherein the error signal is obtained from the fourth noise signal through a secondary path and the original noise signals are superimposed; wherein, according to the error signal, determining the first reference signal includes: filtering the fourth noise signal through the secondary path transfer function to obtain a ninth filtered signal; according to the ninth filtered signal and The error signal is derived from the first reference signal.
  • the fourth noise signal may be y(n).
  • the embodiment of the present application provides a feedback-forward mixed noise control system, which is an adaptive feedback-forward mixed noise control system and can be used in a real-time adaptive system.
  • the noise amplification caused by the water bed effect is constrained by the first filter, and the noise reduction frequency band is selected by the second filter, so as to achieve a better noise reduction effect.
  • Fig. 11 shows a schematic block diagram of a noise control device 1100 provided by an embodiment of the present application. As shown in Figure 11, the device 1100 includes:
  • the first acquiring unit 1101 is configured to acquire an error signal.
  • the determining unit 1102 is configured to determine a first reference signal according to the error signal.
  • the first filtering unit 1103 is configured to filter the first reference signal through a secondary path transfer function to obtain a first filtered signal.
  • the second filtering unit 1104 is configured to filter the first filter signal and the error signal through a first filter to obtain a second filter signal and a third filter signal, and the amplitude-frequency response of the first filter is the same as the original noise signal associated with the power spectral density.
  • the first processing unit 1105 is configured to update the coefficients of the feedback filter according to the second filtered signal and the third filtered signal.
  • the third filtering unit 1106 is configured to filter the first reference signal through the updated feedback filter to obtain a first noise signal.
  • the second filtering unit is further configured to filter the first filtered signal and the error signal through a second filter respectively to obtain a fourth filtered signal and a fifth filtered signal, and the first filtered signal in the second filter
  • the absolute value of the difference between the amplitude of the noise reduction frequency band and the amplitude of the second noise reduction frequency band is greater than or equal to a preset difference; wherein, the first processing unit is specifically configured to: according to the second filtering signal, the third filtering signal, the fourth filtered signal and the fifth filtered signal, and update the coefficients of the feedback filter.
  • the device further includes: a second acquiring unit, configured to acquire a second reference signal picked up by the reference sensor; a fourth filtering unit, configured to filter the second reference signal through the secondary path transfer function to obtain the second reference signal Six filtered signals; the fifth filtering unit is configured to filter the sixth filtered signal through the second filter to obtain a seventh filtered signal; the second processing unit updates the Coefficients of the feedforward filter; the sixth filtering unit is used to filter the second reference signal through the updated feedforward filter to obtain a second noise signal; the third processing unit is used to obtain the second noise signal according to the first noise signal and the second noise signal to obtain a third noise signal; the sending unit is configured to send the third noise signal to the secondary sound source.
  • a second acquiring unit configured to acquire a second reference signal picked up by the reference sensor
  • a fourth filtering unit configured to filter the second reference signal through the secondary path transfer function to obtain the second reference signal Six filtered signals
  • the fifth filtering unit is configured to filter the sixth filtered signal through the second filter to obtain a seventh
  • the fifth filtering unit is further configured to filter the sixth filtered signal through the first filter to obtain an eighth filtered signal; wherein the second processing unit is specifically configured to: according to the third filtered signal, The fifth filtered signal, the seventh filtered signal and the eighth filtered signal update the coefficients of the feedforward filter.
  • the device further includes: a third obtaining unit, configured to obtain a fourth noise signal, and the error signal is obtained by superimposing a signal obtained after the fourth noise signal passes through the secondary path and the original noise signal; wherein, The determining unit is specifically configured to: filter the fourth noise signal through the secondary path transfer function to obtain a ninth filtered signal; obtain the first reference signal according to the ninth filtered signal and the error signal.
  • a third obtaining unit configured to obtain a fourth noise signal, and the error signal is obtained by superimposing a signal obtained after the fourth noise signal passes through the secondary path and the original noise signal
  • the determining unit is specifically configured to: filter the fourth noise signal through the secondary path transfer function to obtain a ninth filtered signal; obtain the first reference signal according to the ninth filtered signal and the error signal.
  • the square of the amplitude-frequency response of the first filter is equal to the reciprocal of the power spectral density of the original noise signal.
  • the embodiment of the present application also provides a device, the device includes a processing unit and a storage unit, wherein the storage unit is used to store instructions, and the processing unit executes the instructions stored in the storage unit, so that the device performs the noise control in the above-mentioned embodiments method.
  • Fig. 12 shows a schematic block diagram of a noise control device 1200 provided by an embodiment of the present application.
  • the device 1200 includes a memory 1201 for storing computer programs; a processor 1202 for executing the computer programs stored in the memory, so that The apparatus 1200 implements the above noise control method.
  • the embodiment of the present application also provides a terminal device, and the terminal device may include the foregoing apparatus 1100 or apparatus 1200 .
  • the terminal device may be a vehicle.
  • the embodiment of the present application also provides a computer program product, the computer program product including: computer program code, when the computer program code is run on the computer, the computer is made to execute the method executed by the server or the first device.
  • the embodiment of the present application also provides a computer-readable medium, the computer-readable medium stores program codes, and when the computer program codes are run on a computer, the computer is made to execute the above method.
  • each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software.
  • the methods disclosed in the embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.
  • the software module can be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, register.
  • the storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware. To avoid repetition, no detailed description is given here.
  • the processor may be a central processing unit (central processing unit, CPU), and the processor may also be other general-purpose processors, digital signal processors (digital signal processor, DSP), dedicated integrated Circuit (application specific integrated circuit, ASIC), off-the-shelf programmable gate array (field programmable gate array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.
  • the memory may include a read-only memory and a random access memory, and provide instructions and data to the processor.
  • sequence numbers of the above-mentioned processes do not mean the order of execution, and the execution order of the processes should be determined by their functions and internal logic, and should not be used in the embodiments of the present application.
  • the implementation process constitutes any limitation.
  • the disclosed systems, devices and methods may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • the computer software product is stored in a storage medium and includes several instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (read-only memory, ROM), random access memory (random access memory, RAM), magnetic disk or optical disc and other media that can store program codes. .

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Abstract

一种噪声控制的方法和装置，该方法包括：获取误差信号（1001），该误差信号由误差传感器采集；根据该误差信号，确定第一参考信号（1002）；将该第一参考信号经过次级路径传递函数滤波，得到第一滤波信号（1003）；将该第一滤波信号和该误差信号分别经过第一滤波器滤波，得到第二滤波信号和第三滤波信号（1004），该第一滤波器的幅频响应与原始噪声信号的功率谱密度相关联；根据该第二滤波信号和该第三滤波信号，更新反馈滤波器的系数（1005）；将该第一参考信号经过更新后的该反馈滤波器滤波，得到第一噪声信号（1006）。有助于抑制噪声控制过程中所产生的水床效应。

Description

一种噪声控制的方法和装置 技术领域
本申请涉及人工智能领域，并且更具体地，涉及一种噪声控制的方法和装置。
背景技术
1936年德国物理学家Lueg首先提出了有源噪声控制(active noise control，ANC)的概念，利用声波相消性干涉原理降噪。随着模拟电路和数字电路的进步，有源噪声控制技术取得了长足的进步，也应用在了很多的领域。目前主要应用的领域有：有源降噪耳机、车辆噪声的有源控制。在许多其他领域也有大量尝试应用：机器噪声的有源控制、有源声屏障、建筑物开口的有源控制等。
有源噪声控制可分为前馈有源噪声控制和反馈有源噪声控制，其中，前馈有源噪声控制的性能依赖于参考信号与初级噪声信号之间的相干性。在许多ANC系统的应用场景中，很难获取高质量的参考信号，导致降噪性能弱或无法降噪。例如，在汽车噪声的有源控制领域，需要使用多个参考加速度计在车底拾取参考信号，硬件成本和算法复杂度都很高，此外参考加速度计的安装位置需要大量实验测量才能优选得到，工作量比较大。
反馈有源噪声控制系统的结构简单，无需参考信号。然而该系统存在水床效应，即在某特定频段降噪的同时会引起其他频段噪声放大。
发明内容
本申请提供一种噪声控制的方法和装置，有助于抑制噪声控制过程中所产生的水床效应。
第一方面，提供了一种噪声控制的方法，其特征在于，包括：获取误差信号，该误差信号由误差传感器采集；根据该误差信号，确定第一参考信号；将该第一参考信号经过次级路径传递函数滤波，得到第一滤波信号；将该第一滤波信号和该误差信号分别经过第一滤波器滤波，得到第二滤波信号和第三滤波信号，该第一滤波器的幅频响应与原始噪声信号的功率谱密度相关联；根据该第二滤波信号和该第三滤波信号，更新反馈滤波器的系数；将该第一参考信号经过更新后的该反馈滤波器滤波，得到第一噪声信号。
本申请实施例中，通过将第一滤波信号和误差信号分别经过第一滤波器滤波，并根据滤波后得到的信号更新反馈滤波器的系数，进而将第一参考信号经过更新后的反馈滤波器滤波得到噪声信号。通过原始噪声信号的功率谱密度获得第一滤波器，无需人工观察水床效应的位置，有助于控制水床效应引起的噪声放大。
在一些可能的实现方式中，本申请实施例中的噪声控制的方法可以应用车辆中。
可选地，上述车辆可以包括一种或多种不同类型的交通工具，也可以包括一种或多种不同类型的在陆地(例如，公路，道路，铁路等)，水面(例如：水路，江河，海洋等)或者空间上操作或移动的运输工具或者可移动物体。例如，车辆可以包括汽车，自行车， 摩托车，火车，地铁，飞机，船，飞行器，机器人或其它类型的运输工具或可移动物体等，本申请实施例对此不作限定。
结合第一方面，在第一方面的某些实现方式中，该第一滤波器的幅频响应的平方与该原始噪声信号的功率谱密度的倒数相等。
结合第一方面，在第一方面的某些实现方式中，该第一滤波器为白化滤波器。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：将该第一滤波信号和该误差信号分别经过第二滤波器滤波，得到第四滤波信号和第五滤波信号，该第二滤波器中第一降噪频段的幅值与第二降噪频段的幅值之差的绝对值大于或者等于预设差值；其中，该根据该第二滤波信号和该第三滤波信号，更新反馈滤波器的系数，包括：根据该第二滤波信号、该第三滤波信号、该第四滤波信号和该第五滤波信号，更新该反馈滤波器的系数。
在一些可能的实现方式中，该第二滤波器可以为频谱整形滤波器。
在一些可能的实现方式中，该根据第二滤波信号、第三滤波信号、第四滤波信号和第五滤波信号，更新反馈滤波器的系数，包括：根据如下公式更新反馈滤波器的系数：
w b(n+1)＝w b(n)-2μ b[e A(n)r A_b(n)+αe'(n)r’ b(n)]
其中，w b(n+1)为反馈滤波器更新后的系数，w b(n)为反馈滤波器更新前的系数，μ b为反馈控制滤波器迭代步长，α为灵敏度幅值约束权重，r’ b(n)为第二滤波信号，e'(n)为第三滤波信号，r A_b(n)为第四滤波信号，e A(n)为第五滤波信号。
本申请实施例中，通过将第一滤波信号和误差信号分别经过第一滤波器和第二滤波器滤波并根据滤波后的信号来更新反馈滤波器的系数，进而将第一参考信号经过更新后的反馈滤波器滤波得到噪声信号，这样有助于控制水床效应引起的噪声放大。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：获取参考传感器拾取的第二参考信号；将该第二参考信号经过该次级路径传递函数滤波，得到第六滤波信号；将该第六滤波信号经过该第二滤波器滤波，得到第七滤波信号；根据该第五滤波信号和该第七滤波信号，更新前馈滤波器的系数；将该第二参考信号经过更新后的该前馈滤波器滤波，得到第二噪声信号。
在一些可能的实现方式中，该方法还包括：根据该第一噪声信号和该第二噪声信号，得到第三噪声信号；将该第三噪声信号发送给次级声源。
在一些可能的实现方式中，该次级声源可以为扬声器。
本申请实施例中提供了前反馈混合噪声控制系统，该前反馈混合噪声控制系统为自适应前反馈混合噪声控制系统，可以用于实时自适应系统。通过第一滤波器来约束水床效应产生的噪声放大，通过第二滤波器来选择降噪频段，从而达到更好的降噪效果。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：将该第六滤波信号经过该第一滤波器滤波，得到第八滤波信号；其中，该根据该第五滤波信号和该第七滤波信号，更新前馈滤波器的系数，包括：根据该第三滤波信号、该第五滤波信号、该第七滤波信号和该第八滤波信号，更新该前馈滤波器的系数。
在一些可能的实现方式中，该根据该第三滤波信号、该第五滤波信号、该第七滤波信号和该第八滤波信号，更新该前馈滤波器的系数，包括：
根据如下公式更新所述前馈滤波器的系数：
w f(n+1)＝w f(n)-2μ f[e A(n)r A_f(n)+αe'(n)r’ f(n)]
其中，w f(n+1)为前馈滤波器更新后的系数，w f(n)为前馈滤波器更新前的系数，μ f为前馈控制滤波器迭代步长，α为灵敏度幅值约束权重，r A_f(n)为第七滤波信号，e'(n)为第三滤波信号，r’ f(n)为第八滤波信号，e A(n)为第五滤波信号。
本申请实施例中，通过将前馈噪声控制中的参考信号和误差信号经过第一滤波器和第二滤波器滤波，且反馈噪声控制中的参考信号和误差信号经过第一滤波器和第二滤波器滤波，可以使得前馈噪声控制和反馈噪声控制中的代价函数统一，有助于简化计算的复杂度，提升计算效率，从而有助于达到更好的降噪效果。
结合第一方面，在第一方面的某些实现方式中，该根据该误差信号，确定第一参考信号之前，该方法还包括：获取第四噪声信号，该误差信号由该第四噪声信号经过次级路径后得到的信号与该原始噪声信号进行叠加得到；其中，该根据该误差信号，确定第一参考信号，包括：将该第四噪声信号经过该次级路径传递函数滤波，得到第九滤波信号；根据该第九滤波信号和该误差信号，得到该第一参考信号。
在一些可能的实现方式中，该第四噪声信号可以为上一时刻的噪声信号。
第二方面，提供了一种噪声控制的装置，该装置包括：第一获取单元，用于获取误差信号；确定单元，用于根据该误差信号，确定第一参考信号；第一滤波单元，用于将该第一参考信号经过次级路径传递函数滤波，得到第一滤波信号；第二滤波单元，用于将该第一滤波信号和该误差信号分别经过第一滤波器滤波，得到第二滤波信号和第三滤波信号，该第一滤波器的幅频响应与原始噪声信号的功率谱密度相关联；第一处理单元，用于根据该第二滤波信号和该第三滤波信号，更新反馈滤波器的系数；第三滤波单元，将该第一参考信号经过更新后的该反馈滤波器滤波，得到第一噪声信号。
结合第二方面，在第二方面的某些实现方式中，该第二滤波单元，还用于将该第一滤波信号和该误差信号分别经过第二滤波器滤波，得到第四滤波信号和第五滤波信号，该第二滤波器中第一降噪频段的幅值与第二降噪频段的幅值之差的绝对值大于或者等于预设差值；其中，该第一处理单元具体用于：根据该第二滤波信号、该第三滤波信号、该第四滤波信号和该第五滤波信号，更新该反馈滤波器的系数。
结合第二方面，在第二方面的某些实现方式中，该装置还包括：第二获取单元，用于获取参考传感器拾取的第二参考信号；第四滤波单元，用于将该第二参考信号经过该次级路径传递函数滤波，得到第六滤波信号；第五滤波单元，用于将该第六滤波信号经过该第二滤波器滤波，得到第七滤波信号；第二处理单元，根据该第五滤波信号和该第七滤波信号，更新前馈滤波器的系数；第六滤波单元，用于将该第二参考信号经过更新后的该前馈滤波器滤波，得到第二噪声信号；第三处理单元，用于根据该第一噪声信号和该第二噪声信号，得到第三噪声信号；发送单元，用于将该第三噪声信号发送给次级声源。
结合第二方面，在第二方面的某些实现方式中，该第五滤波单元用于将该第六滤波信号经过该第一滤波器滤波，得到第八滤波信号；其中，该第二处理单元具体用于：根据该第三滤波信号、该第五滤波信号、该第七滤波信号和该第八滤波信号，更新该前馈滤波器的系数。
结合第二方面，在第二方面的某些实现方式中，该装置还包括：第三获取单元，用于获取第四噪声信号，该误差信号由该第四噪声信号经过次级路径后得到的信号与该原始噪 声信号进行叠加得到；其中，该确定单元具体用于：将该第四噪声信号经过该次级路径传递函数滤波，得到第九滤波信号；根据该第九滤波信号和该误差信号，得到该第一参考信号。
结合第二方面，在第二方面的某些实现方式中，该第一滤波器的幅频响应的平方与该原始噪声信号的功率谱密度的倒数相等。
第三方面，提供了一种噪声控制的装置，该装置包括：存储器，用于存储计算机程序；处理器，用于执行该存储器中存储的计算机程序，以使得该装置执行上述第一方面中的方法。
第四方面，提供了一种车辆，该车辆包括上述第二方面或者第三方面中任一项所述的装置。
第五方面，提供了一种计算机程序产品，所述计算机程序产品包括：计算机程序代码，当所述计算机程序代码在计算机上运行时，使得计算机执行上述第一方面中的方法。
需要说明的是，上述计算机程序代码可以全部或者部分存储在第一存储介质上，其中第一存储介质可以与处理器封装在一起的，也可以与处理器单独封装，本申请实施例对此不作具体限定。
第六方面，提供了一种计算机可读介质，所述计算机可读介质存储有程序代码，当所述计算机程序代码在计算机上运行时，使得计算机执行上述第一方面中的方法。
第七方面，本申请实施例提供了一种芯片系统，该芯片系统包括处理器，用于调用存储器中存储的计算机程序或计算机指令，以使得该处理器执行上述任一方面所述的方法。
结合第七方面，在一种可能的实现方式中，该处理器通过接口与存储器耦合。
结合第七方面，在一种可能的实现方式中，该芯片系统还包括存储器，该存储器中存储有计算机程序或计算机指令。
附图说明
图1是本申请实施例提供的噪声控制的装置的示意性结构图。
图2是本申请实施例提供的前馈噪声控制系统的示意图。
图3是本申请实施例提供的反馈噪声控制系统的示意图。
图4是本申请实施例提供的前反馈混合噪声控制方法的示意图。
图5是本申请实施例提供的前反馈混合噪声控制系统的示意图。
图6是本申请实施例提供的频谱整形滤波器的幅频响应的示意图。
图7是本申请实施例提供的白化滤波器的幅频响应的示意图。
图8是本申请实施例提供的降噪前后噪声信号功率谱密度的示意图。
图9是本申请实施例提供的前反馈混合噪声控制系统灵敏度函数幅频响应的示意图。
图10是本申请实施例提供的噪声控制方法的示意性流程图。
图11是本申请实施例提供的噪声控制装置的示意性流程图。
图12是本申请实施例提供的噪声控制装置的另一示意性流程图。
具体实施方式
下面将结合附图，对本申请中的技术方案进行描述。
图1是本申请实施例提供的噪声控制的装置100的示意性结构图。如图1所示，该装置100中可以包括传感器110和处理器120。其中，传感器110中可以包括参考传感器111和误差传感器112，参考传感器111用于获取参考信号并向处理器发送该参考信号，误差传感器112用于获取误差信号并向处理器发送该误差信号。处理器120用于对该参考信号和误差信号进行处理，并将处理后得到的信号发送给次级声源(例如，扬声器)。
一个实施例中，该参考传感器111可以为参考加速度计。
一个实施例中，该误差传感器112可以为误差麦克风。
应理解，上述装置100可以是位于有源降噪耳机、车辆噪声的有源控制系统中的装置，也可以是机器噪声的有源控制系统、有源声屏障、建筑物开口的有源控制系统中的装置。示例性的，以装置100是汽车噪声的有源控制系统中的装置为例，车辆噪声的有源控制系统可以位于有源降噪头枕中。
可选地，上述车辆可以包括一种或多种不同类型的交通工具，也可以包括一种或多种不同类型的在陆地(例如，公路，道路，铁路等)，水面(例如：水路，江河，海洋等)或者空间上操作或移动的运输工具或者可移动物体。例如，车辆可以包括汽车，自行车，摩托车，火车，地铁，飞机，船，飞行器，机器人或其它类型的运输工具或可移动物体等，本申请实施例对此不作限定。
还应理解，图1中装置100的结构不应理解为对本申请实施例的限制。
下面结合附图对上述处理器对信号处理的过程进行详细介绍。
图2示出了本申请实施例提供的前馈噪声控制系统的结构示意图。如图2所述，处理器分别获取参考传感器和误差传感器拾取的前馈参考信号x f(n)和误差信号e(n)，将前馈参考信号x f(n)经过次级路径模型传递函数
Figure PCTCN2021122033-appb-000001
滤波得到滤波信号x 1。处理器将误差信号e(n)和滤波信号x 1分别经过频谱整形滤波器A(z)和白化滤波器F(z)滤波。误差信号e(n)经过频谱整形滤波器A(z)滤波得到滤波信号e A(n)且经过白化滤波器F(z)滤波得到滤波信号e'(n)。滤波信号x 1经过频谱整形滤波器A(z)滤波得到滤波信号r A_f(n)且经过白化滤波器F(z)滤波得到滤波信号r f'(n)。处理器可以根据滤波信号e A(n)、e'(n)、r A_f(n)和r f'(n)更新前馈滤波器LMS 1的系数。处理器可以将参考信号x f(n)经过系数更新后的前馈滤波器滤波，从而输出反馈给次级声源的控制信号y 1(n)。
一个实施例中，图2所示的前馈噪声控制系统中，也可以将参考信号和误差信号分别经过频谱整形滤波器进行滤波，而不经过白化滤波器进行滤波。通过频谱整形滤波器滤波后得到的滤波信号对前馈滤波器的系数进行更新。
一个实施例中，可以根据如下公式(1)对前馈滤波器系统进行迭代：
w f(n+1)＝w f(n)-2μ f[e A(n)r A_f(n)+αe'(n)r’ f(n)]     (1)
其中，w f(n+1)为n+1时刻前馈滤波器系数，w f(n)为n时刻前馈滤波器系数，μ f为前馈控制滤波器迭代步长，α为前馈滤波器的灵敏度幅值约束权重，r A_f(n)为前馈参考信号x f(n)经过次级路径模型及A(z)滤波后的信号，r f'(n)为前馈参考信号x f(n)经过次级路径模型及F(z)滤波后的信号。
一个实施例中，频谱整形滤波器A(z)用于选择降噪的频段，可以根据需要降噪的频段设计频谱整形滤波器A(z)。例如，在目标降噪频段A(z)的幅值较大，在非目标降噪频段A(z) 的幅值较小。示例性的，可以设置目标频段的幅度与非目标频段的幅值之差的绝对值大于或者等于某个预设幅值(例如，20dB)。
示例性的，目标降噪频段可以为[100Hz，1000Hz]，非目标降噪频段可以为[0Hz，100Hz)。
一个实施例中，可以通过线性预测计算白化滤波器F(z)的系数。白化滤波器F(z)的系数可以通过初级噪声信号x b(n)的功率谱密度的倒数得到。
图2中还示出了前馈噪声控制中获取初级噪声信号x b(n)的过程。反馈给次级声源的控制信号y 1(n)经过次级路径模型传递函数
Figure PCTCN2021122033-appb-000002
滤波后的得到滤波信号x 2。使用误差传感器拾取的误差信号e(n)减去滤波信号x 2就可以得到初级噪声信号x b(n)。本申请实施例中，误差信号e(n)可以是控制信号y 1(n)经过次级路径C(z)后得到的信号与空气中的原始噪声信号p(n)进行叠加得到的。
一个实施例中，还可以根据需要设置前馈滤波器或者反馈滤波器的灵敏度幅值约束权重α。
本申请实施例中在代价函数中增加了灵敏度约束惩罚项。灵敏度约束权重α用于在代价函数中给灵敏度约束惩罚项一个权重。若α很小，则该惩罚项作用小，水床效应约束得不好；若α很大，则惩罚项占比大，误差信号能量占比小，影响降噪效果。
一个实施例中，可以根据计算原始噪声信号的自相关矩阵来确定α。示例性的，α可以取原始噪声信号的自相关矩阵的最大特征值的1/100。
以上结合图2介绍了通过前馈噪声控制系统的示意图，下面结合图3介绍本申请实施例中反馈噪声控制系统的示意图。
处理器获取初级噪声信号x b(n)以及误差传感器拾取的误差信号e(n)，将初级噪声信号x b(n)经过次级路径模型传递函数
Figure PCTCN2021122033-appb-000003
滤波得到滤波信号x 3。处理器将误差信号e(n)和滤波信号x 3分别经过频谱整形滤波器A(z)和白化滤波器F(z)滤波。误差信号e(n)经过频谱整形滤波器A(z)滤波得到滤波信号e A(n)且经过白化滤波器F(z)滤波得到滤波信号e'(n)。滤波信号x 3经过频谱整形滤波器A(z)滤波得到滤波信号r A_b(n)且经过白化滤波器F(z)滤波得到滤波信号r b'(n)。处理器可以根据滤波信号e A(n)、e'(n)、r A_b(n)和r’ b(n)更新反馈滤波器LMS 2的系数。处理器可以将初级噪声信号x b(n)经过系数更新后的反馈滤波器滤波，从而输出反馈给次级声源的控制信号y 2(n)。
一个实施例中，图3所示的反馈噪声控制系统中，也可以将滤波信号x 3和误差信号e(n)分别经过白化滤波器进行滤波，而不经过频谱整形滤波器进行滤波。通过白化滤波器滤波后得到的滤波信号对反馈滤波器的系数进行更新。
一个实施例中，可以根据如下公式(2)对反馈滤波器系统进行迭代：
w b(n+1)＝w b(n)-2μ b[e A(n)r A_b(n)+αe'(n)r’ b(n)]    (2)
其中，w b(n+1)为n+1时刻反馈滤波器系数，w b(n)为n时刻反馈滤波器系数，μ b为反馈控制滤波器迭代步长，α为反馈滤波器的灵敏度幅值约束权重，r A_b(n)为初级噪声信号x b(n)经过次级路径模型及A(z)滤波后的信号，r’ b(n)为初级噪声信号x b(n)经过次级路径模型及F(z)滤波后的信号。
图3中还示出了反馈噪声控制中获取初级噪声信号x b(n)的过程。反馈给次级声源的 控制信号y 2(n)经过次级路径模型传递函数
Figure PCTCN2021122033-appb-000004
滤波后的得到滤波信号x 2。使用误差传感器拾取的误差信号e(n)减去滤波信号x 2就可以得到初级噪声信号x b(n)。本申请实施例中，误差信号e(n)可以是控制信号y 2(n)经过次级路径C(z)后得到的信号与空气中的原始噪声信号p(n)进行叠加得到的。
以上结合图2和图3分别示出了前馈噪声控制和反馈噪声控制的过程，下面结合图4和图5分别介绍本申请实施例提供的前反馈混合噪声控制方法和系统的示意图。
如图4所示，前反馈混合噪声控制方法可以包括上述前馈噪声控制和反馈噪声控制。其中，前馈噪声控制通过参考传感器拾取参考信号，参考信号经过次级路径模型得到滤波信号x 1。滤波信号x 1和误差信号在用于前馈滤波器系数更新前分别经过频谱整形滤波器和白化滤波器滤波。参考信号经过系数更新后的前馈滤波器滤波后得到第一控制信号(例如，上述y 1(n))。
反馈噪声控制可以是基于内模控制(internal model control，IMC)结构，初级噪声信号可以作为反馈部分的参考信号，初级噪声信号和误差信号在用于反馈滤波器系数更新前可以分别经过频谱整形滤波器和白化滤波器滤波。初级噪声信号经过系数更新后的反馈滤波器滤波后得到第二控制信号(例如，上述y 2(n))。
将前馈噪声控制中输出的第一控制信号和反馈噪声控制中输出的第二控制信号进行叠加后得到第三控制信号y(n)，从而将第三控制信号反馈给次级源。
应理解，关于频谱整形滤波器和白化滤波器可以参考上述实施例中的描述，此处不再赘述。
图5所示的前反馈混合噪声控制系统可以是图2所示的前馈噪声控制系统和图3所示的反馈噪声控制系统的组合。
在n时刻，通过误差传感器拾取的误差信号e(n)减去滤波信号x 2就可以得到初级噪声信号x b(n)。其中，前馈噪声控制得到的控制信号y 1(n)和反馈噪声控制得到的控制信号y 2(n)进行叠加即可获得n时刻的控制信号y(n)，控制信号y(n)经过次级路径模型传递函数
Figure PCTCN2021122033-appb-000005
滤波得到就可以得到滤波信号x 2。
应理解，本申请实施例中在系统启动前，白化滤波器的系数(或者，幅频响应)可以是根据原始噪声的频谱特性(例如，将原始噪声的功率谱密度取倒数)得到的。
还应理解，关于控制信号y 1(n)和控制信号y 2(n)的获取过程可以参考上述图2和图3中的描述，此处不再赘述。
一个实施例中，前反馈混合噪声控制系统还可以通过不断迭代前馈滤波器和反馈滤波器参数，从而使得如下公式(3)中的代价函数最小：
Figure PCTCN2021122033-appb-000006
应理解，上述公式(1)和公式(2)可以由公式(3)推导得到。
下面通过测试车辆汽车以50km/h时速在粗糙路面行驶时测得的车内噪声和车内有源头枕实测传递函数进行降噪仿真为例说明本申请实施例的降噪效果。该系统包括1个次级声源和1个误差传声器，误差传声器距离次级声源振膜中心约8cm，在车辆承重架与车身结构的主要连接处布置11个3轴加速度计拾取参考信号，使用其中8个加速度信号作为参考信号，采样率设置为12500Hz。
由于次级声源无法在70Hz以下发出足够大的声压级，过大的低频输出可能会使得扬 声器失真，故将用于选择降噪频段的频谱整形滤波器A(z)设置为截止频率为70Hz，过渡带为30Hz，阻带衰减约为20dB的高通滤波器，频谱整形滤波器A(z)的幅频响应如图6所示。使用初级噪声信号经过线性预测计算得到白化滤波器F(z)的幅频响应如图7所示。仿真中设置反馈滤波器的长度为512，前馈滤波器长度为512，频谱整形滤波器A(z)的滤波器长度为1024，白化滤波器F(z)的滤波器长度为1024，灵敏度函数幅值约束权重因子α为53.8，前馈滤波器迭代步长μ f为0.1，反馈滤波器迭代步长μ b为0.8。
初始噪声录音时长共93.6s，图8中的(a)示出了该噪声录音的83.6s至93.6s信号在[0Hz，1000Hz]频段上降噪前后噪声信号功率谱密度，并给出前馈噪声控制系统和反馈噪声控制系统降噪后的结果作为对比。图8中的(b)示出了在[70Hz，500Hz]频段上降噪前后噪声信号功率谱密度。图8中Primary代表降噪前噪声信号，Feedback代表采用本申请实施例提供的反馈噪声控制系统降噪后信号，Feedforward代表采用本申请实施例提供前馈噪声控制系统降噪后信号，Hybrid代表采用本申请实施例中的前反馈混合噪声控制系统降噪后信号。
本申请实施例中的前反馈混合噪声控制系统可在前馈噪声控制系统的基础上进一步显著降低70Hz至300Hz频段的残余噪声，其在70Hz至500Hz目标频段内的降噪量为9.1dB，高于反馈噪声控制系统的5.2dB和前馈噪声控制系统的5.3dB。本申请实施例中的前反馈混合噪声控制系统在171Hz处降噪量为最大值18.1dB，高于前馈噪声控制系统的最大值12.2dB和反馈噪声控制系统的最大值14.9dB，并有效地将全频带的噪声放大峰值限制在4.4dB以下，其灵敏度函数幅频响应如图9所示。
图10示出了本申请实施例提供的噪声控制方法1000的示意性流程图，如图10所示，该方法1000包括：
S1001，获取误差信号，该误差信号由误差传感器采集。
示例性的，该误差传感器可以为误差麦克风。
示例性的，如图3或者图5所示，该误差信号可以为e(n)。
S1002，根据该误差信号，确定第一参考信号。
示例性的，该第一参考信号可以为x b(n)。
可选地，反馈给次级声源的控制信号y 2(n)经过次级路径模型传递函数
Figure PCTCN2021122033-appb-000007
滤波后的得到滤波信号x 2。使用误差传感器拾取的误差信号e(n)减去滤波信号x 2就可以得到第一参考信号x b(n)。
S1003，将该第一参考信号经过次级路径传递函数滤波，得到第一滤波信号。
示例性的，如图3或者图5所示，该第一滤波信号可以为第一参考信号x b(n)经过次级路径模型传递函数
Figure PCTCN2021122033-appb-000008
滤波后的得到的信号。
S1004，将该第一滤波信号和该误差信号分别经过第一滤波器滤波，得到第二滤波信号和第三滤波信号，该第一滤波器的幅频响应与原始噪声信号的功率谱密度相关联。
可选地，该第一滤波器为白化滤波器。
可选地，图3或者图5中也可以不包括频谱整形滤波器A(z)，第一滤波信号和误差信号可以经过第一滤波器(如图3或者图5所示的F(z))后分别得到第二滤波信号r b'(n)和第三滤波信号e'(n)。可以根据第二滤波信号r’ b(n)和第三滤波信号e'(n)更新反馈滤波器的 系数。
可选地，该第一滤波器的幅频响应的平方与该原始噪声信号的功率谱密度的倒数之差小于或者等于预设值。
可选地，该第一滤波器的幅频响应的平方与该原始噪声信号的功率谱密度的倒数相等。
S1005，根据该第二滤波信号和该第三滤波信号，更新反馈滤波器的系数。
本申请实施例中，可以根据第二滤波信号r’ b(n)和第三滤波信号e'(n)来更新反馈滤波器的系数。
可选地，该方法还包括：将该第一滤波信号和该误差信号分别经过第二滤波器滤波，得到第四滤波信号和第五滤波信号，该第二滤波器中第一降噪频段的幅值与第二降噪频段的幅值之差的绝对值大于或者等于预设差值；其中，该根据该第二滤波信号和该第三滤波信号，更新反馈滤波器的系数，包括：根据该第二滤波信号、该第三滤波信号、该第四滤波信号和该第五滤波信号，更新该反馈滤波器的系数。
示例性的，如图3或者图5所示，该第四滤波信号可以为r A_b(n)，该第五滤波信号可以为e A(n)。
可选地，该第一降噪频段可以为目标降噪频段。示例性的，该目标降噪频段可以为[100Hz，1000Hz]。
可选地，该第二降噪频段可以为非目标降噪频段。示例性的，该目标降噪频段可以为[0Hz，100Hz]。
可选地，该第二滤波器可以为频谱整形滤波器。
可选地，该根据第二滤波信号、第三滤波信号、第四滤波信号和第五滤波信号，更新反馈滤波器的系数，包括：根据如下公式更新反馈滤波器的系数：
w b(n+1)＝w b(n)-2μ b[e A(n)r A_b(n)+αe'(n)r’ b(n)]
其中，w b(n+1)为反馈滤波器更新后的系数，w b(n)为反馈滤波器更新前的系数，μ b为反馈控制滤波器迭代步长，α为灵敏度幅值约束权重。
本申请实施例中，通过将第一滤波信号和误差信号分别经过第一滤波器和第二滤波器滤波并根据滤波后的信号来更新反馈滤波器的系数，进而将第一参考信号经过更新后的反馈滤波器滤波得到噪声信号。这样有助于控制水床效应引起的噪声放大。
S1006，将该第一参考信号经过更新后的该反馈滤波器滤波，得到第一噪声信号。
本申请实施例中，通过将第一滤波信号和误差信号分别经过第一滤波器滤波，并根据滤波后得到的信号更新反馈滤波器的系数，进而将第一参考信号经过更新后的反馈滤波器滤波得到噪声信号。通过原始噪声信号的功率谱密度获得第一滤波器，有助于控制水床效应引起的噪声放大。
可选地，该方法还包括：获取参考传感器拾取的第二参考信号；将该第二参考信号经过该次级路径传递函数滤波，得到第六滤波信号；将该第六滤波信号经过该第二滤波器滤波，得到第七滤波信号；根据该第五滤波信号和该第七滤波信号，更新前馈滤波器的系数；将该第二参考信号经过更新后的该前馈滤波器滤波，得到第二噪声信号。
可选地，该方法还包括：根据该第一噪声信号和该第二噪声信号，得到第三噪声信号；将该第三噪声信号发送给次级声源。
可选地，该参考传感器可以为加速度计，或者，该参考传感器可以为加速度计和麦克风。
可选地，该第二滤波器可以为频谱整形滤波器。
示例性的，如图2所示，该第二参考信号可以为x f(n)，该第七滤波信号可以为r A_f(n)。
可选地，该方法还包括：将该第六滤波信号经过该第一滤波器滤波，得到第八滤波信号；其中，该根据该第五滤波信号和该第七滤波信号，更新前馈滤波器的系数，包括：根据该第三滤波信号、该第五滤波信号、该第七滤波信号和该第八滤波信号，更新该前馈滤波器的系数。
示例性的，如图2或者图5所示，该第八滤波信号可以为r’ f(n)。
可选地，根据该第三滤波信号、该第五滤波信号、该第七滤波信号和该第八滤波信号，更新该前馈滤波器的系数，包括：根据如下公式更新前馈滤波器的系数：
w f(n+1)＝w f(n)-2μ f[e A(n)r A_f(n)+αe'(n)r’ f(n)]
其中，w f(n+1)为前馈滤波器更新后的系数，w f(n)为前馈滤波器更新前的系数，μ f为前馈控制滤波器迭代步长，α为灵敏度幅值约束权重。
本申请实施例中，通过将前馈噪声控制中的参考信号和误差信号经过第一滤波器和第二滤波器滤波，且反馈噪声控制中的参考信号和误差信号经过第一滤波器和第二滤波器滤波，可以使得前馈噪声控制和反馈噪声控制中的代价函数统一，有助于简化计算的复杂度，提升计算效率，从而有助于达到更好的降噪效果。
可选地，该根据该误差信号，确定第一参考信号之前，该方法还包括：获取第四噪声信号，其中，该误差信号由该第四噪声信号经过次级路径后得到的信号与该原始噪声信号进行叠加得到；其中，该根据该误差信号，确定第一参考信号，包括：将该第四噪声信号经过该次级路径传递函数滤波，得到第九滤波信号；根据该第九滤波信号和该误差信号，得到该第一参考信号。
示例性的，如图5所示，该第四噪声信号可以为y(n)。
本申请实施例中提供了前反馈混合噪声控制系统，该前反馈混合噪声控制系统为自适应前反馈混合噪声控制系统，可以用于实时自适应系统。通过第一滤波器来约束水床效应产生的噪声放大，通过第二滤波器来选择降噪频段，从而达到更好的降噪效果。
图11示出了本申请实施例提供的噪声控制装置1100的示意性框图。如图11所示，该装置1100包括：
第一获取单元1101，用于获取误差信号。
确定单元1102，用于根据该误差信号，确定第一参考信号。
第一滤波单元1103，用于将该第一参考信号经过次级路径传递函数滤波，得到第一滤波信号。
第二滤波单元1104，用于将该第一滤波信号和该误差信号分别经过第一滤波器滤波，得到第二滤波信号和第三滤波信号，该第一滤波器的幅频响应与原始噪声信号的功率谱密度相关联。
第一处理单元1105，用于根据该第二滤波信号和该第三滤波信号，更新反馈滤波器的系数。
第三滤波单元1106，将该第一参考信号经过更新后的该反馈滤波器滤波，得到第一噪声信号。
可选地，该第二滤波单元，还用于将该第一滤波信号和该误差信号分别经过第二滤波器滤波，得到第四滤波信号和第五滤波信号，该第二滤波器中第一降噪频段的幅值与第二降噪频段的幅值之差的绝对值大于或者等于预设差值；其中，该第一处理单元具体用于：根据该第二滤波信号、该第三滤波信号、该第四滤波信号和该第五滤波信号，更新该反馈滤波器的系数。
可选地，该装置还包括：第二获取单元，用于获取参考传感器拾取的第二参考信号；第四滤波单元，用于将该第二参考信号经过该次级路径传递函数滤波，得到第六滤波信号；第五滤波单元，用于将该第六滤波信号经过该第二滤波器滤波，得到第七滤波信号；第二处理单元，根据该第五滤波信号和该第七滤波信号，更新前馈滤波器的系数；第六滤波单元，用于将该第二参考信号经过更新后的该前馈滤波器滤波，得到第二噪声信号；第三处理单元，用于根据该第一噪声信号和该第二噪声信号，得到第三噪声信号；发送单元，用于将该第三噪声信号发送给次级声源。
可选地，该第五滤波单元还用于将该第六滤波信号经过该第一滤波器滤波，得到第八滤波信号；其中，该第二处理单元具体用于：根据该第三滤波信号、该第五滤波信号、该第七滤波信号和该第八滤波信号，更新该前馈滤波器的系数。
可选地，该装置还包括：第三获取单元，用于获取第四噪声信号，该误差信号由该第四噪声信号经过次级路径后得到的信号与该原始噪声信号进行叠加得到；其中，该确定单元具体用于：将该第四噪声信号经过该次级路径传递函数滤波，得到第九滤波信号；根据该第九滤波信号和该误差信号，得到该第一参考信号。
可选地，该第一滤波器的幅频响应的平方与该原始噪声信号的功率谱密度的倒数相等。
本申请实施例还提供了一种装置，该装置包括处理单元和存储单元，其中存储单元用于存储指令，处理单元执行存储单元所存储的指令，以使该装置执行上述实施例中噪声控制的方法。
图12示出了本申请实施例提供的噪声控制装置1200的示意性框图，该装置1200包括存储器1201，用于存储计算机程序；处理器1202，用于执行该存储器中存储的计算机程序，以使得该装置1200执行上述噪声控制的方法。
本申请实施例还提供了一种终端设备，该终端设备可以包括上述装置1100或者装置1200。
可选地，该终端设备可以为车辆。
本申请实施例还提供了一种计算机程序产品，所述计算机程序产品包括：计算机程序代码，当所述计算机程序代码在计算机上运行时，使得计算机执行上述服务器或者第一设备所执行的方法。
本申请实施例还提供了一种计算机可读介质，所述计算机可读介质存储有程序代码，当所述计算机程序代码在计算机上运行时，使得计算机执行上述方法。
在实现过程中，上述方法的各步骤可以通过处理器中的硬件的集成逻辑电路或者软件形式的指令完成。结合本申请实施例所公开的方法可以直接体现为硬件处理器执行完成， 或者用处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器，处理器读取存储器中的信息，结合其硬件完成上述方法的步骤。为避免重复，这里不再详细描述。
应理解，本申请实施例中，该处理器可以为中央处理单元(central processing unit，CPU)，该处理器还可以是其他通用处理器、数字信号处理器(digital signal processor，DSP)、专用集成电路(application specific integrated circuit，ASIC)、现成可编程门阵列(field programmable gate array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
还应理解，本申请实施例中，该存储器可以包括只读存储器和随机存取存储器，并向处理器提供指令和数据。
在本申请实施例中，“第一”、“第二”以及各种数字编号仅为描述方便进行的区分，并不用来限制本申请实施例的范围。例如，区分不同的管路、通孔等。
应理解，在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例 所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖。在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (18)

  1. 一种噪声控制的方法，其特征在于，包括：
    获取误差信号，所述误差信号由误差传感器采集；
    根据所述误差信号，确定第一参考信号；
    将所述第一参考信号经过次级路径传递函数滤波，得到第一滤波信号；
    将所述第一滤波信号和所述误差信号分别经过第一滤波器滤波，得到第二滤波信号和第三滤波信号，所述第一滤波器的幅频响应与原始噪声信号的功率谱密度相关联；
    根据所述第二滤波信号和所述第三滤波信号，更新反馈滤波器的系数；
    将所述第一参考信号经过更新后的所述反馈滤波器滤波，得到第一噪声信号。
  2. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    将所述第一滤波信号和所述误差信号分别经过第二滤波器滤波，得到第四滤波信号和第五滤波信号，所述第二滤波器中第一降噪频段的幅值与第二降噪频段的幅值之差的绝对值大于或者等于预设差值；
    其中，所述根据所述第二滤波信号和所述第三滤波信号，更新反馈滤波器的系数，包括：
    根据所述第二滤波信号、所述第三滤波信号、所述第四滤波信号和所述第五滤波信号，更新所述反馈滤波器的系数。
  3. 根据权利要求2所述的方法，其特征在于，所述方法还包括：
    获取参考传感器拾取的第二参考信号；
    将所述第二参考信号经过所述次级路径传递函数滤波，得到第六滤波信号；
    将所述第六滤波信号经过所述第二滤波器滤波，得到第七滤波信号；
    根据所述第五滤波信号和所述第七滤波信号，更新前馈滤波器的系数；
    将所述第二参考信号经过更新后的所述前馈滤波器滤波，得到第二噪声信号；
    根据所述第一噪声信号和所述第二噪声信号，得到第三噪声信号；
    向次级声源发送所述第三噪声信号。
  4. 根据权利要求3所述的方法，其特征在于，所述方法还包括：
    将所述第六滤波信号经过所述第一滤波器滤波，得到第八滤波信号；
    其中，所述根据所述第五滤波信号和所述第七滤波信号，更新前馈滤波器的系数，包括：
    根据所述第三滤波信号、所述第五滤波信号、所述第七滤波信号和所述第八滤波信号，更新所述前馈滤波器的系数。
  5. 根据权利要求1至4中任一项所述的方法，其特征在于，所述根据所述误差信号，确定第一参考信号之前，所述方法还包括：
    获取第四噪声信号，所述误差信号由所述第四噪声信号经过次级路径后得到的信号与所述原始噪声信号进行叠加得到；
    其中，所述根据所述误差信号，确定第一参考信号，包括：
    将所述第四噪声信号经过所述次级路径传递函数滤波，得到第九滤波信号；
    根据所述第九滤波信号和所述误差信号，得到所述第一参考信号。
  6. 根据权利要求1至5中任一项所述的方法，其特征在于，所述第一滤波器的幅频响应的平方与所述原始噪声信号的功率谱密度的倒数相等。
  7. 根据权利要求1至6中任一项所述的方法，其特征在于，所述第一滤波器为白化滤波器。
  8. 一种噪声控制的装置，其特征在于，包括：
    第一获取单元，用于获取误差信号；
    确定单元，用于根据所述误差信号，确定第一参考信号；
    第一滤波单元，用于将所述第一参考信号经过次级路径传递函数滤波，得到第一滤波信号；
    第二滤波单元，用于将所述第一滤波信号和所述误差信号分别经过第一滤波器滤波，得到第二滤波信号和第三滤波信号，所述第一滤波器的幅频响应与原始噪声信号的功率谱密度相关联；
    第一处理单元，用于根据所述第二滤波信号和所述第三滤波信号，更新反馈滤波器的系数；
    第三滤波单元，将所述第一参考信号经过更新后的所述反馈滤波器滤波，得到第一噪声信号。
  9. 根据权利要求8所述的装置，其特征在于，
    所述第二滤波单元，还用于将所述第一滤波信号和所述误差信号分别经过第二滤波器滤波，得到第四滤波信号和第五滤波信号，所述第二滤波器中第一降噪频段的幅值与第二降噪频段的幅值之差的绝对值大于或者等于预设差值；
    其中，所述第一处理单元具体用于：根据所述第二滤波信号、所述第三滤波信号、所述第四滤波信号和所述第五滤波信号，更新所述反馈滤波器的系数。
  10. 根据权利要求9所述的装置，其特征在于，所述装置还包括：
    第二获取单元，用于获取参考传感器拾取的第二参考信号；
    第四滤波单元，用于将所述第二参考信号经过所述次级路径传递函数滤波，得到第六滤波信号；
    第五滤波单元，用于将所述第六滤波信号经过所述第二滤波器滤波，得到第七滤波信号；
    第二处理单元，根据所述第五滤波信号和所述第七滤波信号，更新前馈滤波器的系数；
    第六滤波单元，用于将所述第二参考信号经过更新后的所述前馈滤波器滤波，得到第二噪声信号；
    第三处理单元，用于根据所述第一噪声信号和所述第二噪声信号，得到第三噪声信号；
    发送单元，用于向次级声源发送所述第三噪声信号。
  11. 根据权利要求10所述的装置，其特征在于，所述第五滤波单元还用于将所述第六滤波信号经过所述第一滤波器滤波，得到第八滤波信号；
    其中，所述第二处理单元具体用于：根据所述第三滤波信号、所述第五滤波信号、所述第七滤波信号和所述第八滤波信号，更新所述前馈滤波器的系数。
  12. 根据权利要求8至11中任一项所述的装置，其特征在于，所述装置还包括：
    第三获取单元，用于获取第四噪声信号，所述误差信号由所述第四噪声信号经过次级路径后得到的信号与所述原始噪声信号进行叠加得到；
    其中，所述确定单元具体用于：
    将所述第四噪声信号经过所述次级路径传递函数滤波，得到第九滤波信号；
    根据所述第九滤波信号和所述误差信号，得到所述第一参考信号。
  13. 根据权利要求8至12中任一项所述的装置，其特征在于，所述第一滤波器的幅频响应的平方与所述原始噪声信号的功率谱密度的倒数相等。
  14. 根据权利要求8至13中任一项所述的装置，其特征在于，所述第一滤波器为白化滤波器。
  15. 一种噪声控制的装置，其特征在于，包括：
    存储器，用于存储计算机程序；
    处理器，用于执行所述存储器中存储的计算机程序，以使得所述装置执行如权利要求1至7中任一项所述的方法。
  16. 一种车辆，其特征在于，所述车辆包括如权利要求8至15中任一项所述的装置。
  17. 一种计算机可读存储介质，其特征在于，其上存储有计算机程序，所述计算机程序被计算机执行时，以使得实现如权利要求1至7中任一项所述的方法。
  18. 一种计算机程序产品，其特征在于，所述计算机程序产品包括：计算机程序代码，当所述计算机程序代码在计算机上运行时，使得所述计算机执行如权利要求1至7中任一项所述的方法。
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