WO2023065368A1 - 一种信号处理方法、装置、存储介质和车辆 - Google Patents

一种信号处理方法、装置、存储介质和车辆 Download PDF

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WO2023065368A1
WO2023065368A1 PCT/CN2021/125919 CN2021125919W WO2023065368A1 WO 2023065368 A1 WO2023065368 A1 WO 2023065368A1 CN 2021125919 W CN2021125919 W CN 2021125919W WO 2023065368 A1 WO2023065368 A1 WO 2023065368A1
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audio signal
processing
signal
parameters
processing method
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PCT/CN2021/125919
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English (en)
French (fr)
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王浩
邹海山
邱小军
吴晟
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华为技术有限公司
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Priority to CN202180008019.9A priority Critical patent/CN116348357A/zh
Priority to PCT/CN2021/125919 priority patent/WO2023065368A1/zh
Publication of WO2023065368A1 publication Critical patent/WO2023065368A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61C—LOCOMOTIVES; MOTOR RAILCARS
    • B61C17/00—Arrangement or disposition of parts; Details or accessories not otherwise provided for; Use of control gear and control systems
    • B61C17/04—Arrangement or disposition of driving cabins, footplates or engine rooms; Ventilation thereof
    • 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

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  • the present application relates to the field of signal processing, and in particular to a signal processing method, device, storage medium and vehicle.
  • Vehicles usually have strong noise during high-speed driving. These noises include road noise, wind noise, environmental noise, etc. generated by the interaction between tires and the ground, suspension and body, which seriously affect the comfort of drivers and passengers. .
  • the energy of the noise perceived by people can be reduced by the noise reduction method, and the noise interference to people can be reduced.
  • the noise reduction method of vehicle noise usually has two methods: passive noise reduction and active noise reduction. Among them, passive noise reduction is to reduce the noise of the vehicle through physical noise reduction, and active noise reduction generally uses active noise control (active noise control).
  • Cancellation (ANC) technology the audio signal that suppresses the noise signal is generated through the speaker, and when the noise signal and the suppressed noise signal are combined and superimposed, they are neutralized to cancel each other out, and finally achieve the purpose of noise reduction.
  • the filter In the active noise reduction method, the filter is usually only suitable for noise reduction in a single working condition. Due to the complex structure of the actual vehicle body and unstable working conditions, the real-time adjustment ability in practical applications is poor, and rapid noise reduction cannot be achieved. And it cannot be stabilized in a state with a large amount of noise reduction, so there is an urgent need for a noise reduction solution with stronger real-time adjustment capabilities and better noise reduction effects.
  • embodiments of the present application provide a signal processing method.
  • the method includes: receiving a first audio signal at a noise source collected by one or more first sensors; receiving a second audio signal at a human ear collected by one or more second sensors, the first audio signal and the The second audio signal is used to determine parameters for processing the first audio signal according to the first processing method; sending a third audio signal determined after processing the first audio signal according to the first processing method, The third audio signal is used to instruct the speaker to emit a sound wave, and the sound wave is used to cancel out the noise at the human ear.
  • the second audio signal collected at the human ear is used for real-time parameter adjustment, so that the current noise reduction state can be considered, and according to the current Adjust the parameters of the noise reduction state.
  • the adjusted parameters are used to process the first audio signal to obtain the third audio signal to instruct the speaker to emit sound waves to cancel the noise, which can achieve faster noise reduction with greater noise reduction and noise reduction effect Better, improve the comfort of the driver and passengers.
  • the method further includes: processing the first audio signal according to a second processing manner to determine a fourth audio signal, the second processing manner indicating that the sound wave is from the The transmission method for transmitting the speaker to the second sensor; according to the second audio signal and the audio signal after processing the third audio signal according to the second processing method, determine a fifth audio signal; The fourth audio signal and the fifth audio signal determine parameters for processing the first audio signal according to the first processing manner.
  • the parameters can be adjusted in time, so that the noise reduction state can be restored faster when interference occurs, and the robustness is stronger. So as to get a better noise reduction effect.
  • determining parameters for processing the first audio signal according to the first processing method includes: according to the The autocorrelation matrix of the fourth audio signal, and the cross-correlation matrix of the fourth audio signal and the fifth audio signal determine parameters for processing the first audio signal according to the first processing manner.
  • the degree of autocorrelation of the fourth audio signal and the degree of cross-correlation between the fourth audio signal and the fifth audio signal can be taken into consideration in the process of adjusting the parameters, so as to achieve a better noise reduction effect.
  • Processing the parameters of the first audio signal includes: determining the change direction of the parameters according to the autocorrelation matrix, the cross-correlation matrix, and the parameters at the previous moment; according to one or more of the following Type: the parameter at the last moment, the signal length when processed according to the first processing mode, the change direction of the parameter, the change range of the parameter, and determine the parameter at the current moment.
  • the noise caused by the sudden change of the filter caused by not updating the parameters in time can be avoided, and the driving speed can be improved. Passenger experience comfort.
  • processing the first audio signal to determine the fourth audio signal includes: every predetermined window moving distance, the predetermined window length of the The first audio signal is processed according to the second processing method to determine a fourth audio signal; according to the second audio signal and the audio signal after processing the third audio signal according to the second processing method, determine The fifth audio signal includes: every predetermined window moving distance, according to the second audio signal with a predetermined window length and the audio signal after processing the third audio signal according to the second processing method, determine the fifth audio signal Signal.
  • the method further includes: determining a noise reduction amount according to the second audio signal and the fifth audio signal; according to the noise reduction amount, one of the following One or more types of adjustments are performed: the variation range of the parameter, the signal length when processing according to the first processing mode, the moving distance of the predetermined window, and the length of the predetermined window.
  • the amount of noise reduction by calculating the amount of noise reduction, and adjusting one or more of the following according to the amount of noise reduction: parameter variation range, signal length, predetermined window moving distance, and predetermined window length, it is possible to make the In the process of noise reduction, it adapts to different noise reduction environments and states to achieve better noise reduction effects and improve user experience.
  • the first processing manner is Wiener filtering.
  • inventions of the present application provide a signal processing device.
  • the device includes: a first receiving module, used to receive the first audio signal at the noise source collected by one or more first sensors; a second receiving module, used to receive the audio signal at the human ear collected by one or more second sensors.
  • the second audio signal, the first audio signal and the second audio signal are used to determine the parameters for processing the first audio signal according to the first processing method; the sending module is used to send the first audio signal according to the first processing method
  • a third audio signal is determined after processing the first audio signal, the third audio signal is used to instruct the speaker to emit sound waves, and the sound waves are used to cancel out the noise at the human ear.
  • the device further includes: a first determining module, configured to process the first audio signal according to a second processing manner, and determine a fourth audio signal, the first The second processing method indicates the transmission method of the sound wave from the speaker to the second sensor; the second determination module is configured to process the third audio signal according to the second audio signal and according to the second processing method After the audio signal, determine a fifth audio signal; a third determining module, configured to determine to process the first audio signal according to the first processing method according to the fourth audio signal and the fifth audio signal parameters.
  • the third determination module includes: according to the autocorrelation matrix of the fourth audio signal and the cross-correlation matrix of the fourth audio signal and the fifth audio signal, Determine parameters for processing the first audio signal according to a first processing manner.
  • Processing the parameters of the first audio signal includes: determining the change direction of the parameters according to the autocorrelation matrix, the cross-correlation matrix, and the parameters at the previous moment; according to one or more of the following Type: the parameter at the last moment, the signal length when processed according to the first processing mode, the change direction of the parameter, the change range of the parameter, and determine the parameter at the current moment.
  • the first determination module includes: processing the first audio signal with a predetermined window length according to the second processing method every predetermined window moving distance, and determining the first audio signal Four audio signals; the second determination module, including: every predetermined window moving distance, the second audio signal according to the predetermined window length, and the audio signal after processing the third audio signal according to the second processing method, A fifth audio signal is determined.
  • the device further includes: a fourth determination module, configured to determine a noise reduction amount according to the second audio signal and the fifth audio signal; an adjustment module, configured to According to the noise reduction amount, one or more of the following are adjusted: the variation range of the parameter, the signal length when processing according to the first processing mode, the predetermined window moving distance, and the predetermined window length .
  • the first processing manner is Wiener filtering.
  • an embodiment of the present application provides a signal processing device, which includes: a processor and a memory; the memory is used to store programs; the processor is used to execute the programs stored in the memory, so that The device implements the first aspect or the signal processing method in any possible implementation manner of the first aspect.
  • the embodiments of the present application provide a terminal device, where the terminal device can execute the signal processing method in the foregoing first aspect or any possible implementation manner of the first aspect.
  • the embodiments of the present application provide a computer-readable storage medium, on which program instructions are stored.
  • the program instructions When executed by a computer, the program instructions enable the computer to implement the above-mentioned first aspect or any possible implementation of the first aspect. way of way.
  • the sixth aspect of the present application provides a computer program product, which includes program instructions.
  • the program instructions When executed by a computer, the program instructions enable the computer to implement the above first aspect or any possible implementation of the first aspect. Signal processing methods in .
  • embodiments of the present application provide a vehicle, where the vehicle includes a processor, and the processor is configured to execute the signal processing method in the foregoing first aspect or any possible implementation manner of the first aspect.
  • Fig. 1 shows a schematic diagram of an application scenario according to an embodiment of the present application.
  • Fig. 2 shows a flowchart of a signal processing method according to an embodiment of the present application.
  • Fig. 3 shows a schematic diagram of a sliding window according to an embodiment of the present application.
  • Fig. 4 shows a flowchart of a signal processing method according to an embodiment of the present application.
  • Fig. 5 shows a flowchart of a signal processing method according to an embodiment of the present application.
  • Fig. 6 shows a flowchart of a signal processing method according to an embodiment of the present application.
  • Fig. 7 shows a flowchart of a signal processing method according to an embodiment of the present application.
  • Fig. 8 shows a structural diagram of a signal processing device according to an embodiment of the present application.
  • Fig. 9 shows a structural diagram of a signal processing device according to an embodiment of the present application.
  • Fig. 1 shows a schematic diagram of an application scenario according to an embodiment of the present application.
  • the signal processing method of the embodiment of the present application can be used to reduce noise heard by drivers and passengers in a vehicle.
  • the signal processing system of the embodiment of the present application can be arranged on a vehicle, and includes a speaker, a sensor and a processor.
  • the loudspeaker can be used to emit sound waves corresponding to the audio signal to offset the noise near the ears of the driver and passengers, thereby reducing the noise heard by the drivers and passengers in the car.
  • the senor may include a first sensor and a second sensor.
  • the first sensor can be one or more, which can include accelerometer, vehicle radar (such as millimeter wave radar, laser radar, ultrasonic radar, etc.), rain sensor, camera, vehicle attitude sensor (such as gyroscope), inertial measurement unit (inertial measurement unit, IMU), etc.
  • vehicle radar such as millimeter wave radar, laser radar, ultrasonic radar, etc.
  • vehicle attitude sensor such as gyroscope
  • inertial measurement unit inertial measurement unit
  • IMU inertial measurement unit
  • the first sensor can be arranged near the noise source on the vehicle for collecting the reference signal.
  • a reference signal can be used to indicate noise near a noise source.
  • the reference signal may include an acceleration signal collected by an accelerometer. Since the acceleration signal is proportional to the vibration amplitude of the vehicle, the magnitude of the noise near the noise source can be determined through the acceleration signal.
  • the second sensor may include a microphone, and may be arranged near the ears of the occupants in the vehicle for collecting residual signals.
  • the residual signal can be used to indicate the residual noise heard by the occupants of the vehicle after the sound waves from the speakers have been canceled out by the noise near the human ear.
  • the processor can be built into the vehicle (or audio system) on the vehicle as a vehicle computing unit, such as a digital signal processor (DSP) chip.
  • DSP digital signal processor
  • the processor can perform calculations based on the signals collected by the sensors to determine the audio signal.
  • the processor may also be placed externally in the cloud server.
  • the server and the vehicle can communicate through wireless connections, such as mobile communication technologies such as 2G/3G/4G/5G, as well as wireless communication technologies such as Wi-Fi, Bluetooth, frequency modulation (FM), digital radio, and satellite communications. Communication method to communicate. Through the communication between the vehicle and the server, the server can collect the signals collected by the sensor for calculation, and send the calculation result back to the corresponding vehicle.
  • the signal processing system in the embodiment of the present application may further include a preamplifier and a power amplifier.
  • the preamplifier can be used to amplify the residual signal collected by the second sensor to a certain level range
  • the power amplifier can be used to amplify the audio signal to drive the speaker to emit corresponding sound waves.
  • the current method of noise reduction in the vehicle cannot be adjusted in real time according to the current noise reduction effect, and the noise reduction effect is not good.
  • the residual signal is also used to adjust the parameters during processing, so that the current The noise reduction effect can be adjusted in real time, dynamically changing the audio signal.
  • the dynamically adjusted audio signal can be offset against the noise signal at the human ear to obtain a greater amount of noise reduction, achieve rapid noise reduction, and obtain a better noise reduction effect.
  • Fig. 2 shows a flowchart of a signal processing method according to an embodiment of the present application. This method can be used in the above-mentioned signal processing system. As shown in Figure 2, the method may include:
  • Step S201 the first sensor collects a reference signal.
  • the reference signal collected by the first sensor can be referred to as x(n) in the figure.
  • n may correspond to the current moment and represent a sequence number in the signal sequence, that is, the signal collected at the current moment is the nth signal in the signal sequence.
  • the reference signal may be a multi-channel signal, that is, one x(n) may correspond to a group of signals, wherein one signal in each group of signals corresponds to one channel.
  • Step S202 the second sensor collects the residual signal.
  • ⁇ may refer to the summation of the reference signal and the audio signal at the error point, that is, the reference signal and the audio signal are canceled at the error point, and the signal remaining after the cancellation is the residual signal.
  • the error point is the position where the second sensor is placed, which can be any position near the human ear, for example, any position near the left ear and/or near the right ear of the human.
  • one or more second sensors can be provided. If there are multiple drivers and passengers, multiple corresponding second sensors may also be provided.
  • d(n) can represent the actual primary noise signal, corresponding to the noise that actually reaches the error point.
  • G in the figure may represent the actual secondary path, and the secondary path may refer to the path of sound wave transmission from the loudspeaker to the error point.
  • the audio signal from the speaker y(n) in the figure
  • the signal that can be collected by the second sensor is The remaining residual signal
  • e(n) can indicate the noise actually heard by the driver and passengers after noise reduction.
  • the current noise reduction effect can be better known by using the e(n) collected by the second sensor at the error point, which helps to adjust relevant parameters more specifically and improve the noise reduction effect.
  • the known audio signal can be combined to determine the reference signal filtered by the filter corresponding to the transfer function of the secondary path, and calculate the primary noise signal, using these two A signal updates the relevant parameters of the Wiener filter (which can be represented by W) used to obtain the audio signal.
  • the output audio signal can be dynamically adjusted.
  • the relevant parameters may be calculated using a sliding window algorithm. That is, for some parameters, point-by-point calculation may not be required to save the amount of calculation.
  • Fig. 3 shows a schematic diagram of a sliding window according to an embodiment of the present application.
  • the rectangular boxes in the figure may correspond to sliding windows, and each point on the coordinate axis may correspond to a signal.
  • n may correspond to the current signal, for example, x(n).
  • N may represent the length of the sliding window, that is, one sliding window corresponds to N signals.
  • M can represent the moving distance of the sliding window, that is, the corresponding parameters are calculated every M signals.
  • the sliding window moves twice, from the position corresponding to signal n-M to the position corresponding to signal n, and then from the position corresponding to signal n to the position corresponding to signal n+M.
  • three calculations can be performed corresponding to the above three positions.
  • the sliding window algorithm can be used in the related processes of the following steps S203-S208.
  • the correlation process in step S203-step S208 can be performed every M signals, according to a total of N signals including the current signal and the N-1 signals before the current signal signal to recalculate the associated parameters.
  • Step S203 the processor filters the reference signal according to the transfer function of the secondary path, and determines the filtered reference signal.
  • the application Since the reference signal needs to go through the secondary path to reach the error point after the audio signal is obtained through filtering, the application first calculates the reference signal after the secondary path (ie, the filtered reference signal, see x in Fig. 2 g (n)). Then, according to the signal, the parameters for determining the filtering of the audio signal are adjusted, and in this process, the influence of the secondary path on the noise reduction effect is taken into account, thereby achieving a better noise reduction effect.
  • the reference signal after the secondary path ie, the filtered reference signal, see x in Fig. 2 g (n)
  • a speaker may be used to play a white noise signal and record a signal collected by the second sensor, thereby estimating the transfer function of the secondary path.
  • a least mean square (LMS) algorithm or a Wiener filter may be used to estimate the secondary path to obtain a transfer function of the secondary path, or other methods may also be used.
  • a sliding window algorithm may be used to filter the reference signals once every M reference signals according to the transfer function of the secondary path to determine the filtered reference signals.
  • Step S204 the processor determines the primary noise signal according to the residual signal and the audio signal obtained by filtering the audio signal according to the transfer function of the secondary path.
  • the application After determining the filtered reference signal x g (n), the application also needs to calculate the primary noise signal d(n) at the error point, thus, when updating the parameters for determining the filtering of the audio signal, the filtering
  • the parameters are adjusted based on the correlation between the final reference signal and the primary noise signal, so that the final audio signal can better cancel out the noise signal at the human ear.
  • the present application uses the transfer function of the determined secondary path to calculate and reconstruct the primary noise signal ( See Figure 2 in ).
  • Equation (1) One way to determine the primary noise signal can be seen in Equation (1):
  • the length of the filter can represent the number of signals filtered when the filter performs one filtering (that is, the number of sampling points of the input signal processed by the filter at one time).
  • I may represent the maximum value of the length of the Wiener filter W used to determine the audio signal, and may represent the number of signals filtered by the Wiener filter once. It can represent the audio signal y(n) obtained after filtering the reference signal x(n) by W, It can be expressed that for y(n) after The audio signal reaching the error point obtained after filtering.
  • the primary noise signal can be deduced from the collected residual signal.
  • a sliding window algorithm may be used to determine the primary noise signal every M residual signals and the audio signal after filtering the audio signal according to the transfer function of the secondary path.
  • Step S205 the processor determines an autocorrelation matrix according to the filtered reference signal.
  • R xx (n) may represent an autocorrelation matrix corresponding to x g (n), and may indicate an autocorrelation degree of x g (n).
  • the transpose matrix of x g (n) can be represented.
  • a method of determining the autocorrelation matrix using the sliding window algorithm can be referred to formula (3):
  • N may represent the length of the sliding window.
  • Step S206 the processor determines a cross-correlation matrix according to the filtered reference signal and the primary noise signal.
  • R xd (n) can represent x g (n) and
  • the corresponding autocorrelation matrix can indicate x g (n) and the degree of correlation between them.
  • a method for determining the cross-correlation matrix using the sliding window algorithm can be referred to formula (5):
  • N may represent the length of the sliding window.
  • step S207 the processor updates the coefficients of the Wiener filter used to determine the audio signal according to the autocorrelation matrix and the cross-correlation matrix.
  • the Wiener filter coefficient target direction Wwn (n) can be determined according to the autocorrelation matrix and the cross-correlation matrix.
  • W wn (n) One way to determine W wn (n) can be found in Equation (6):
  • the change direction of the filter ⁇ W(n) can be determined according to the difference between the target direction Wwn (n) of the Wiener filter and the previous Wiener filter coefficient W(n-1), see formula (7):
  • ⁇ can represent the variation range of the Wiener filter.
  • L may represent the length of the Wiener filter, and the value of L may be consistent with the value of the length N of the sliding window, thereby obtaining a better noise reduction effect.
  • the processor needs to update the coefficient W(n) corresponding to W point by point.
  • a sliding window algorithm may be used to update ⁇ W(n) every M points.
  • Step S208 the processor determines the amount of noise reduction according to the primary noise signal and the residual signal, and adjusts the parameters of the Wiener filter and the parameters of the sliding window according to the determined amount of noise reduction.
  • the noise reduction amount in order to adjust the noise reduction state according to the current noise reduction effect, and obtain a larger noise reduction amount and a faster and more responsive noise reduction speed, the noise reduction amount can be determined first, and related parameters can be adjusted accordingly.
  • P d (n) and P e (n) can be expressed respectively The power corresponding to e(n).
  • P d (n) and P e (n) can be expressed respectively The power corresponding to e(n).
  • P d (n) and Pe (n) can be found in Equation (10) and Equation (11), respectively:
  • ⁇ may represent a parameter for controlling the sliding speed, which may be preset, and the value of ⁇ is, for example, 0.01.
  • the parameters of the Wiener filter and the parameters of the sliding window may be adjusted according to the calculated noise reduction amount
  • the adjustable parameters may include, for example, the variation range ⁇ , The length L of the Wiener filter, the moving distance M of the sliding window, the length N of the sliding window, and the like.
  • the amount of noise reduction can be inversely proportional to ⁇ , and proportional to L, M, and N.
  • the value of the above parameters can also be determined according to the size of the noise reduction amount NR, and a method of determining L according to NR can be referred to in formula (12):
  • I may represent a maximum value corresponding to the length of the Wiener filter, which may be preset.
  • M may be determined according to a value of L, and the values of M and L may be equal.
  • r(NR) may represent a scaling factor determined from NR.
  • N r(NR)*N 0 (13)
  • the value of N 0 may represent a maximum value corresponding to the length of the sliding window, and may be preset.
  • ⁇ 0 may represent the maximum value corresponding to the fluctuation range of the Wiener filter coefficient, which may be preset.
  • r ⁇ (NR) may represent a proportionality factor determined from NR.
  • ⁇ 1 , ⁇ 2 , and ⁇ 3 are preset parameters.
  • ⁇ 1 may be used to constrain the lower limit of r(NR), and the value range of ⁇ 1 is, for example, 0.05-0.1.
  • ⁇ 2 can be used to adjust the slope of the function. The larger the value of ⁇ 2 , the faster the corresponding parameters can be adjusted with the amount of noise reduction.
  • ⁇ 3 can be used to determine the value of r(NR) when the noise reduction amount is 0, and is used to indicate the initial noise reduction amount when r(NR) starts to increase.
  • ⁇ 4 , ⁇ 5 , and ⁇ 6 are preset parameters.
  • ⁇ 1 can be used to constrain the lower limit of r ⁇ (NR), and the value range of ⁇ 4 is, for example, 0.05-0.1.
  • ⁇ 5 can be used to adjust the slope of the function. The larger the value of ⁇ 5 , the faster the corresponding parameters can be adjusted with the amount of noise reduction.
  • ⁇ 6 can be used to determine the value of r ⁇ (NR) when the noise reduction amount is 0, and is used to indicate the initial noise reduction amount when r ⁇ (NR) starts to increase.
  • ⁇ 1 and ⁇ 4 may be the same or different. The same is true for ⁇ 2 and ⁇ 5 , ⁇ 3 and ⁇ 6 .
  • Step S209 the processor performs Wiener filtering on the reference signal according to the determined coefficients of the Wiener filter, determines the audio signal, and emits a sound wave corresponding to the audio signal through the speaker.
  • I may represent a maximum value corresponding to the length L of the Wiener filter, which may be preset.
  • the determined corresponding audio signal can be canceled out with the noise signal at the human ear to achieve the effect of noise reduction.
  • Fig. 4 shows a flowchart of a signal processing method according to an embodiment of the present application. This method can be used in the above-mentioned signal processing system. As shown in Figure 4, the method includes:
  • Step S401 receiving a first audio signal at a noise source collected by one or more first sensors
  • Step S402 receiving a second audio signal at the human ear collected by one or more second sensors, the first audio signal and the second audio signal are used to determine the first audio signal according to the first processing method parameters for processing;
  • Step S403 sending a third audio signal determined after processing the first audio signal according to the first processing method, the third audio signal is used to instruct the speaker to emit a sound wave, and the sound wave is used to communicate with the human ear noise cancels out.
  • real-time parameter adjustment is performed by using the second audio signal collected at the human ear.
  • the second audio signal is the actual noise at the human ear, that is, it is The third audio signal
  • the sound wave generated by the third audio speaker cancels the remaining noise (ie, the residual signal above), so that the adjusted parameters are used to process the first audio signal to obtain the third audio signal to indicate the speaker
  • Sending out sound waves to offset the noise can achieve faster noise reduction, and has a greater noise reduction amount, and the noise reduction effect is better, improving the comfort of drivers and passengers.
  • the first audio signal may be the aforementioned reference signal x(n)
  • the second audio signal may be the aforementioned residual signal e(n)
  • the third audio signal may be the aforementioned audio signal y(n).
  • the second audio signal at the human ear may be a residual signal collected at any position within a preset range near the human ear of the driver and occupant in the vehicle.
  • Multiple first sensors can be set at different positions, and multiple second sensors can also be set at different positions.
  • the first processing manner is Wiener filtering. As a result, a greater amount of noise reduction can be obtained, and faster noise reduction can be achieved.
  • the first processing manner may also be other processing manners capable of processing the first audio signal to determine the third audio signal.
  • the parameters for processing the first audio signal according to the first processing manner may be, for example, coefficients of the Wiener filter W described above.
  • step S401 refers to step S201 in FIG. 2, for an example of step S402, refer to step S202 in FIG. 2, and for an example of step S403, refer to the relevant description in step S209 in FIG.
  • Fig. 5 shows a flowchart of a signal processing method according to an embodiment of the present application. As shown in Figure 5, the method also includes:
  • Step S501 process the first audio signal according to a second processing method to determine a fourth audio signal, the second processing method indicates the transmission method of the sound wave from the speaker to the second sensor;
  • Step S502 determining a fifth audio signal according to the second audio signal and the audio signal after processing the third audio signal according to the second processing method
  • Step S503 according to the fourth audio signal and the fifth audio signal, determine parameters for processing the first audio signal according to the first processing manner.
  • the parameters can be adjusted in time, so that the noise reduction state can be restored faster when interference occurs, and the robustness is stronger. So as to get a better noise reduction effect.
  • the second processing method can be, for example, the transfer function of the above-mentioned secondary path
  • the fourth audio signal may be a reference signal x g (n) obtained by filtering the reference signal according to the transfer function of the secondary path.
  • the fifth audio signal may be the primary noise signal calculated above
  • step S501 refer to step S203 in FIG. 2, for an example of step S502, refer to step S204 in FIG.
  • determining parameters for processing the first audio signal according to the first processing manner includes: according to the fourth audio signal The autocorrelation matrix of the signals, and the cross-correlation matrix of the fourth audio signal and the fifth audio signal determine the parameters for processing the first audio signal according to the first processing manner.
  • the degree of autocorrelation of the fourth audio signal and the degree of cross-correlation between the fourth audio signal and the fifth audio signal can be taken into consideration in the process of adjusting the parameters, so as to achieve a better noise reduction effect.
  • step S205 For an example of the determination process of the autocorrelation matrix, refer to step S205 in FIG. 2 , and for an example of the determination process of the cross-correlation matrix, refer to step S206 in FIG. 2 .
  • An example of determining parameters for processing the first audio signal according to the first processing method according to the autocorrelation matrix of the fourth audio signal and the cross-correlation matrix of the fourth audio signal and the fifth audio signal Refer to the relevant description in step S207 in FIG. 2 .
  • Fig. 6 shows a flowchart of a signal processing method according to an embodiment of the present application. As shown in FIG. 6, according to the autocorrelation matrix of the fourth audio signal and the cross-correlation matrix of the fourth audio signal and the fifth audio signal, it is determined that the first audio signal is processed according to the first processing method. Parameters for processing, including:
  • Step S601 according to the autocorrelation matrix, the cross-correlation matrix, and the parameters at the last moment, determine the change direction of the parameters
  • Step S602 according to one or more of the following: the parameter at the previous moment, the signal length when processing according to the first processing method, the direction of change of the parameter, and the range of change of the parameter, determine the parameter at the current moment .
  • the noise caused by the sudden change of the filter caused by not updating the parameters in time can be avoided, and the driving speed can be improved. Passenger experience comfort.
  • the change direction of the parameter may be the above-mentioned ⁇ W(n)
  • the signal length during processing according to the first processing mode may refer to the signal length during each processing, and may be the length L of the above-mentioned Wiener filter.
  • the variation range of the parameter may be the aforementioned ⁇
  • the parameter at the current moment may be the aforementioned current coefficient W(n) of the Wiener filter.
  • the last moment may refer to a moment before the current moment, and the parameter of the last moment may be the above-mentioned W(n-1).
  • step S601-step S602 refer to step S207 in FIG. 2 above.
  • the first audio signal is processed to determine the fourth audio signal, including: every predetermined window moving distance, and the predetermined window length
  • the first audio signal is processed according to the second processing method to determine the fourth audio signal;
  • Determining the fifth audio signal according to the second audio signal and the audio signal after processing the third audio signal according to the second processing method includes: moving a distance at intervals of the predetermined window, according to the predetermined window The second audio signal of the length and the audio signal after processing the third audio signal according to the second processing manner determine the fifth audio signal.
  • the window can refer to the sliding window shown in Figure 3 above
  • the predetermined moving distance of the window can be the moving distance M of the sliding window above
  • the predetermined window length can be the length N of the sliding window above.
  • step S203-step S204 in FIG. 2 refer to the related examples in step S203-step S204 in FIG. 2 .
  • Fig. 7 shows a flowchart of a signal processing method according to an embodiment of the present application. As shown in Figure 7, the method also includes:
  • Step S701 determining a noise reduction amount according to the second audio signal and the fifth audio signal
  • Step S702 according to the noise reduction amount, adjust one or more of the following: the variation range of the parameter, the signal length when processing according to the first processing mode, the moving distance of the predetermined window, the Predetermined window length.
  • the amount of noise reduction by calculating the amount of noise reduction, and adjusting one or more of the following according to the amount of noise reduction: parameter variation range, signal length, predetermined window moving distance, and predetermined window length, it is possible to make the In the process of noise reduction, it adapts to different noise reduction environments and states to achieve better noise reduction effects and improve user experience.
  • the amount of noise reduction can be, for example, NR above.
  • the smaller the value of the noise reduction amount the greater the noise reduction power and the faster the noise reduction speed.
  • the smaller the value of the noise reduction amount is, the larger the variation range of the corresponding parameter is, the smaller the signal length is, the smaller the moving distance of the predetermined window is, and the smaller the length of the predetermined window is.
  • the larger the value of the noise reduction amount the smaller the variation range of the corresponding parameter, the larger the signal length, the larger the moving distance of the predetermined window, and the larger the length of the predetermined window.
  • step S701-step S702 refer to the related description in step S208 above.
  • Fig. 8 shows a structural diagram of a signal processing device according to an embodiment of the present application. As shown in Figure 8, the device includes:
  • a first receiving module 801 configured to receive a first audio signal at a noise source collected by one or more first sensors;
  • the second receiving module 802 is configured to receive the second audio signal at the human ear collected by one or more second sensors, the first audio signal and the second audio signal are used to determine the Parameters for processing the first audio signal;
  • a sending module 803 configured to send a third audio signal determined after processing the first audio signal according to the first processing manner, where the third audio signal is used to instruct the speaker to emit a sound wave, and the sound wave is used to communicate with the Noise at the human ear cancels out.
  • the second audio signal collected at the human ear is used for real-time parameter adjustment, so that the current noise reduction state can be considered, and according to the current Adjust the parameters of the noise reduction state.
  • the adjusted parameters are used to process the first audio signal to obtain the third audio signal to instruct the speaker to emit sound waves to cancel the noise, which can achieve faster noise reduction with greater noise reduction and noise reduction effect Better, improve the comfort of the driver and passengers.
  • the first processing manner is Wiener filtering.
  • the device further includes: a first determination module, configured to process the first audio signal according to a second processing manner to determine a fourth audio signal, and the second processing manner indicates The transmission method of the sound wave from the speaker to the second sensor; the second determination module is configured to process the third audio signal according to the second audio signal and according to the second processing method audio signal, determining a fifth audio signal; a third determining module, configured to determine parameters for processing the first audio signal according to the first processing method according to the fourth audio signal and the fifth audio signal .
  • the parameters can be adjusted in time, so that the noise reduction state can be restored faster when interference occurs, and the robustness is stronger. So as to get a better noise reduction effect.
  • the third determination module includes: according to the autocorrelation matrix of the fourth audio signal and the cross-correlation matrix of the fourth audio signal and the fifth audio signal, determine the The processing mode is the parameter for processing the first audio signal.
  • the degree of autocorrelation of the fourth audio signal and the degree of cross-correlation between the fourth audio signal and the fifth audio signal can be taken into consideration in the process of adjusting the parameters, so as to achieve a better noise reduction effect.
  • the parameters for processing an audio signal include: determining the change direction of the parameters according to the autocorrelation matrix, the cross-correlation matrix, and the parameters at the last moment; according to one or more of the following: The parameter at the last moment, the signal length when processed according to the first processing mode, the direction of change of the parameter, and the magnitude of change of the parameter determine the parameter at the current moment.
  • the noise caused by the sudden change of the filter caused by not updating the parameters in time can be avoided, and the driving speed can be improved. Passenger experience comfort.
  • the first determination module includes: processing the first audio signal with a predetermined window length according to the second processing method at every predetermined window moving distance, and determining a fourth audio signal;
  • the second determination module includes: every predetermined window moving distance, according to the second audio signal with a predetermined window length and the audio signal after processing the third audio signal according to the second processing method, determine the fifth audio frequency Signal.
  • the device further includes: a fourth determination module, configured to determine a noise reduction amount according to the second audio signal and the fifth audio signal; an adjustment module, configured to determine a noise reduction amount according to the noise reduction
  • the amount of noise is to adjust one or more of the following: the variation range of the parameter, the signal length when processing according to the first processing mode, the moving distance of the predetermined window, and the length of the predetermined window.
  • the amount of noise reduction by calculating the amount of noise reduction, and adjusting one or more of the following according to the amount of noise reduction: parameter variation range, signal length, predetermined window moving distance, and predetermined window length, it is possible to make the In the process of noise reduction, it adapts to different noise reduction environments and states to achieve better noise reduction effects and improve user experience.
  • FIG. 9 shows a structural diagram of a signal processing device according to an embodiment of the present application.
  • the signal processing device may be applicable to the signal processing system shown in FIG. 1, and execute the signal processing method shown in any one of FIGS. 2-7.
  • a signal processing apparatus 900 may include a processor 901 and a transceiver 902 .
  • the signal processing device 900 may include a memory 903 .
  • the processor 901 is coupled with the transceiver 902 and the memory 903, such as may be connected through a communication bus.
  • the components of the signal processing device 900 will be specifically introduced below in conjunction with FIG. 9 .
  • the above-mentioned processor 901 is the control center of the signal processing device 900, and may be one processor, or may be a general term for multiple processing elements.
  • the processor 901 is one or more central processing units (central processing unit, CPU), may also be a specific integrated circuit (application specific integrated circuit, ASIC), or is configured to implement one or more An integrated circuit, for example: one or more microprocessors, or, one or more field programmable gate arrays (field programmable gate array, FPGA).
  • the processor 901 can execute various functions of the signal processing device 900 by running or executing software programs stored in the memory 903 and calling data stored in the memory 903 .
  • the processor 901 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 9 .
  • the signal processing apparatus 900 may also include multiple processors, for example, the processor 901 and the processor 904 shown in FIG. 9 .
  • processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU).
  • a processor herein may refer to one or more communication devices, circuits, and/or processing cores for processing data (eg, computer program instructions).
  • the transceiver 902 may include a receiver and a transmitter (not separately shown in FIG. 9 ). Wherein, the receiver is used to realize the receiving function, and the transmitter is used to realize the sending function.
  • the transceiver 902 may be integrated with the processor 901, or may exist independently, and be coupled to the processor 901 through an input/output port (not shown in FIG. 9 ) of the signal processing device 900. In this embodiment of the present application, There is no limit to this.
  • the above-mentioned memory 903 can be used to store the software program for implementing the solution of the present application, and the execution is controlled by the processor 901.
  • the specific implementation can refer to the above-mentioned method embodiment, and will not be repeated here.
  • the memory 903 may be a read-only memory (read-only memory, ROM) or other types of static storage communication devices that can store static information and instructions, or a random access memory (random access memory, RAM) that can store information and instructions
  • Other types of dynamic storage communication devices can also be electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical discs Storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage communication devices, or can be used to carry or store desired information in the form of instructions or data structures program code and any other medium that can be accessed by a computer, but not limited to.
  • the memory 903 can be integrated with the processor 901, or can exist independently, and is coupled with the processor 901 through the input/output port of the signal processing device 900 (not shown in FIG. 9 ). There is no limit to this.
  • the structure of the signal processing device 900 shown in FIG. 9 does not constitute a limitation on the implementation of the signal processing device.
  • the actual signal processing device may include more or fewer components than shown in the figure, or Combining certain parts, or different arrangements of parts.
  • An embodiment of the present application provides a signal processing device, including: a processor and a memory; the memory is used to store a program; the processor is used to execute the program stored in the memory, so that the device implements the above method .
  • An embodiment of the present application provides a computer-readable storage medium, on which program instructions are stored, and when the program instructions are executed by a computer, the computer is made to implement the above method.
  • Embodiments of the present application provide a terminal device, and the terminal device can execute the foregoing method.
  • An embodiment of the present application provides a computer program product, which includes program instructions, and when the program instructions are executed by a computer, the computer can implement the above method.
  • An embodiment of the present application provides a vehicle, the vehicle includes a processor, and the processor is configured to execute the above method.
  • a computer readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device.
  • a computer readable storage medium may be, for example, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing.
  • Computer readable program instructions or codes described herein may be downloaded from a computer readable storage medium to a respective computing/processing device, or downloaded to an external computer or external storage device over a network, such as the Internet, local area network, wide area network, and/or wireless network.
  • the network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers.
  • a network adapter card or a network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing/processing device .
  • These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine such that when executed by the processor of the computer or other programmable data processing apparatus , producing an apparatus for realizing the functions/actions specified in one or more blocks in the flowchart and/or block diagram.
  • These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause computers, programmable data processing devices and/or other devices to work in a specific way, so that the computer-readable medium storing instructions includes An article of manufacture comprising instructions for implementing various aspects of the functions/acts specified in one or more blocks in flowcharts and/or block diagrams.
  • each block in a flowchart or block diagram may represent a module, a portion of a program segment, or an instruction that includes one or more Executable instructions.
  • the functions noted in the block may occur out of the order noted in the figures. For example, two blocks in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved.
  • each block in the block diagrams and/or flowcharts, and combinations of blocks in the block diagrams and/or flowcharts can be implemented with hardware (such as circuits or ASIC (Application Specific Integrated Circuit, application-specific integrated circuit)), or can be implemented with a combination of hardware and software, such as firmware.
  • hardware such as circuits or ASIC (Application Specific Integrated Circuit, application-specific integrated circuit)
  • firmware such as firmware

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Abstract

本申请涉及一种信号处理方法、装置、存储介质和车辆。该方法包括：接收一个或多个第一传感器采集的噪声源处的第一音频信号；接收一个或多个第二传感器采集的人耳处的第二音频信号，所述第一音频信号和所述第二音频信号用于确定根据第一处理方式对所述第一音频信号进行处理的参数；发送根据所述第一处理方式对所述第一音频信号进行处理后确定的第三音频信号，所述第三音频信号用于指示扬声器发出声波，所述声波用于与人耳处的噪声相抵消。由此，可以实现在降噪过程中进行参数的实时调整能力，从而可以实现快速降噪，且降噪量大，降噪效果更好。

Description

一种信号处理方法、装置、存储介质和车辆 技术领域
本申请涉及信号处理领域，尤其涉及一种信号处理方法、装置、存储介质和车辆。
背景技术
车辆在高速行驶的过程中通常存在较强的噪声，这些噪声包括由车胎与地面、悬架与车身相互作用产生的路噪，风噪，环境噪声等等，严重影响了驾乘人员的舒适度。通过降噪方法可以降低人们感知的噪声的能量，减少人们受到的噪声干扰。车辆噪音的降噪方法通常有被动降噪和主动降噪两种方法，其中，被动降噪就是通过物理降噪的方式使得车辆的噪音减小，而主动降噪一般利用主动噪声控制(active noise cancellation，ANC)技术，通过扬声器产生抑制噪音信号的音频信号，当噪音信号与抑制噪音信号交汇叠加后便中和以相互抵消，最终达到降噪目的。
在主动降噪的方法中，滤波器通常仅适用于单一工况的降噪，由于实际车辆的车身结构复杂、工况不稳定，在实际应用中的实时调整能力较差，无法实现快速降噪且无法稳定于降噪量较大的状态，因此亟需实时调整能力更强、降噪效果更好的降噪方案。
发明内容
有鉴于此，提出了一种信号处理方法、装置、存储介质和车辆。
第一方面，本申请的实施例提供了一种信号处理方法。该方法包括：接收一个或多个第一传感器采集的噪声源处的第一音频信号；接收一个或多个第二传感器采集的人耳处的第二音频信号，所述第一音频信号和所述第二音频信号用于确定根据第一处理方式对所述第一音频信号进行处理的参数；发送根据所述第一处理方式对所述第一音频信号进行处理后确定的第三音频信号，所述第三音频信号用于指示扬声器发出声波，所述声波用于与人耳处的噪声相抵消。
根据本申请实施例，通过在对第一音频信号进行处理的过程中，利用了人耳处采集的第二音频信号进行实时的参数调整，由此可以考虑到当前的降噪状态，并根据当前的降噪状态对参数进行调整。由此，利用调整后的参数对第一音频信号进行处理得到第三音频信号，以指示扬声器发出声波来抵消噪声，可以实现更快速的降噪，且具有更大的降噪量，降噪效果更好，提升了驾乘人员的舒适度。
根据第一方面及任一种可能的实现方式，该方法还包括：根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，所述第二处理方式指示声波从所述扬声器传输至所述第二传感器的传输方式；根据所述第二音频信号、以及根据所述第二处理方式对所述第三音频信号进行处理后的音频信号，确定第五音频信号；根据所述第四音频信号和所述第五音频信号，确定根据所述第一处理方式对所述第一音频信号进行处理的参数。
根据本申请实施例，通过估计从所述扬声器传输至所述第二传感器的传输方式，确定第四音频信号，考虑了第一音频信号的传输过程，同时，重构出第五音频信号，可以计算出驾 乘人员听到的降噪前的初始噪声，结合二者对参数进行调整，可以使得调整后的参数指示的扬声器发出的对应声波能够更好地与噪声相抵消，从而获得更大的降噪量。同时，通过根据上述二者对参数的实时计算，可以及时调整参数，使得在出现干扰时可以更快的恢复降噪状态，鲁棒性更强。从而得到更好的降噪效果。
根据第一方面及任一种可能的实现方式，根据所述第四音频信号和所述第五音频信号，确定根据第一处理方式对所述第一音频信号进行处理的参数，包括：根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的参数。
由此，可以在调整参数的过程中同时考虑到第四音频信号的自相关程度，以及第四音频信号和第五音频信号的互相关程度，实现更好的降噪效果。
根据第一方面及任一种可能的实现方式，根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的参数，包括：根据所述自相关矩阵、所述互相关矩阵、和上一时刻的参数，确定所述参数的变化方向；根据以下中的一种或多种：上一时刻的参数、根据第一处理方式进行处理时的信号长度、所述参数的变化方向、所述参数的变化幅度，确定当前时刻的参数。
根据本申请实施例，通过在每一时刻确定当前时刻的参数，可以在稳定大降噪量且实现快速降噪的基础上，避免不及时更新参数导致的滤波器突变带来的噪声，提高驾乘人员的体验舒适度。
根据第一方面及任一种可能的实现方式，根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，包括：每隔预定窗口移动距离，对预定窗口长度的所述第一音频信号根据所述第二处理方式进行处理，确定第四音频信号；根据所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号，包括：每隔预定窗口移动距离，根据预定窗口长度的所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号。
根据本申请实施例，可以实现利用预定窗口进行计算，不必逐点确定第四音频信号和第五音频信号，减少计算量。
根据第一方面及任一种可能的实现方式，该方法还包括：根据所述第二音频信号和所述第五音频信号，确定降噪量；根据所述降噪量，对以下中的一种或多种进行调整：所述参数的变化幅度、根据第一处理方式进行处理时的信号长度、所述预定窗口移动距离、所述预定窗口长度。
根据本申请实施例，通过计算降噪量，并根据降噪量对以下中的一种或多种进行调整：参数的变化幅度、信号长度、预定窗口移动距离、预定窗口长度，可以使得在降噪的过程中适应于不同的降噪环境和状态，达到更好的降噪效果，提高用户的体验。
根据第一方面及任一种可能的实现方式，在所述信号处理方法的第六种可能的实现方式中，该第一处理方式为维纳滤波。
由此，可以得到更大的降噪量，且可以实现更快速地降噪。
第二方面，本申请的实施例提供了一种信号处理装置。该装置包括：第一接收模块，用于接收一个或多个第一传感器采集的噪声源处的第一音频信号；第二接收模块，用于接收一个或多个第二传感器采集的人耳处的第二音频信号，所述第一音频信号和第二音频信号用于 确定根据第一处理方式对所述第一音频信号进行处理的参数；发送模块，用于发送根据所述第一处理方式对所述第一音频信号进行处理后确定的第三音频信号，所述第三音频信号用于指示扬声器发出声波，所述声波用于与人耳处的噪声相抵消。
根据第二方面及任一种可能的实现方式，该装置还包括：第一确定模块，用于根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，所述第二处理方式指示声波从所述扬声器传输至所述第二传感器的传输方式；第二确定模块，用于根据所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号；第三确定模块，用于根据所述第四音频信号和所述第五音频信号，确定根据所述第一处理方式对所述第一音频信号进行处理的参数。
根据第二方面及任一种可能的实现方式，第三确定模块包括：根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的参数。
根据第二方面及任一种可能的实现方式，根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的参数，包括：根据所述自相关矩阵、所述互相关矩阵、和上一时刻的参数，确定所述参数的变化方向；根据以下中的一种或多种：上一时刻的参数、根据第一处理方式进行处理时的信号长度、所述参数的变化方向、所述参数的变化幅度，确定当前时刻的参数。
根据第二方面及任一种可能的实现方式，第一确定模块，包括：每隔预定窗口移动距离，对预定窗口长度的所述第一音频信号根据所述第二处理方式进行处理，确定第四音频信号；第二确定模块，包括：每隔预定窗口移动距离，根据预定窗口长度的所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号。
根据第二方面及任一种可能的实现方式，该装置还包括：第四确定模块，用于根据所述第二音频信号和所述第五音频信号，确定降噪量；调整模块，用于根据所述降噪量，对以下中的一种或多种进行调整：所述参数的变化幅度、根据第一处理方式进行处理时的信号长度、所述预定窗口移动距离、所述预定窗口长度。
根据第二方面及任一种可能的实现方式，该第一处理方式为维纳滤波。
第三方面，本申请的实施例提供了一种信号处理装置，该装置包括：处理器和存储器；所述存储器用于存储程序；所述处理器用于执行所述存储器所存储的程序，以使所述装置实现上述第一方面或者第一方面任意一种可能的实现方式中的信号处理方法。
第四方面，本申请的实施例提供了一种终端设备，该终端设备可以执行上述第一方面或者第一方面任意一种可能的实现方式中的信号处理方法。
第五方面，本申请的实施例提供了一种计算机可读存储介质，其上存储有程序指令，程序指令当被计算机执行时使得计算机实现上述第一方面或者第一方面任意一种可能的实施方式的方法。
为达到上述目的，本申请的第六方面提供了一种计算机程序产品，其包括有程序指令，程序指令当被计算机执行时使得计算机实现上述第一方面或者第一方面任意一种可能的实现方式中的信号处理方法。
第七方面，本申请的实施例提供了一种车辆，所述车辆包括处理器，所述处理器用于执行上述第一方面或者第一方面任意一种可能的实现方式中的信号处理方法。
本申请的这些和其他方面在以下(多个)实施例的描述中会更加简明易懂。
附图说明
包含在说明书中并且构成说明书的一部分的附图与说明书一起示出了本申请的示例性实施例、特征和方面，并且用于解释本申请的原理。
图1示出根据本申请一实施例的应用场景的示意图。
图2示出了根据本申请一实施例的信号处理方法的流程图。
图3示出根据本申请一实施例的滑动窗口的示意图。
图4示出根据本申请一实施例的信号处理方法的流程图。
图5示出根据本申请一实施例的信号处理方法的流程图。
图6示出根据本申请一实施例的信号处理方法的流程图。
图7示出根据本申请一实施例的信号处理方法的流程图。
图8示出根据本申请一实施例的信号处理装置的结构图。
图9示出根据本申请一实施例的信号处理装置的结构图。
具体实施方式
以下将参考附图详细说明本申请的各种示例性实施例、特征和方面。附图中相同的附图标记表示功能相同或相似的元件。尽管在附图中示出了实施例的各种方面，但是除非特别指出，不必按比例绘制附图。
在这里专用的词“示例性”意为“用作例子、实施例或说明性”。这里作为“示例性”所说明的任何实施例不必解释为优于或好于其它实施例。
另外，为了更好的说明本申请，在下文的具体实施方式中给出了众多的具体细节。本领域技术人员应当理解，没有某些具体细节，本申请同样可以实施。在一些实例中，对于本领域技术人员熟知的方法、手段、元件和电路未作详细描述，以便于凸显本申请的主旨。
图1示出了根据本申请一实施例的应用场景的示意图。如图1所示，本申请实施例的信号处理方法可以用于在车辆中降低驾乘人员听到的噪声。本申请实施例的信号处理系统可设置于车辆上，包括扬声器、传感器和处理器。
其中，扬声器可以用于发出与音频信号对应的声波，以与驾乘人员人耳附近的噪声相抵消，从而可以降低车内驾乘人员听到的噪声。扬声器可以是一个或多个。
其中，传感器可以包括第一传感器和第二传感器。
第一传感器可以是一个或者多个，可以包括加速度计、车载雷达(如毫米波雷达、激光雷达、超声波雷达等)、雨量传感器、摄像头、车姿传感器(如陀螺仪)、惯性测量单元(inertial measurement unit，IMU)等。第一传感器可以设置于车辆上的噪声源附近，用于采集参考信号。参考信号可以用于指示噪声源附近的噪声。例如，参考信号中可以包括加速度计采集到的加速度信号，由于该加速度信号与车辆振动幅度存在正比关系，由此通过该加速度信号确定噪声源附近的噪声大小。
第二传感器可以包括传声器，可以设置于车内驾乘人员的人耳附近，用于采集残差信号。残差信号可以用于指示在扬声器发出的声波与人耳附近的噪声相抵消后，车内驾乘人员听到的残留的噪声。在一种可能的实现方式中，车内可能存在多个驾乘人员，则可以对应多个驾 乘人员分别设置多个第二传感器采集对应的残差信号。
其中，处理器可以作为车载计算单元内置于车辆上的车机(或是音频系统)中，例如是数字信号处理(digital signal processor，DSP)芯片。处理器可以根据传感器采集到的信号并进行计算，以确定音频信号。在一种可能的实现方式中，处理器也可以外置于云端服务器中。服务器和车辆可以通过无线连接的方式进行通信，例如可以通过2G/3G/4G/5G等移动通信技术，以及Wi-Fi、蓝牙、调频(frequency modulation，FM)、数传电台、卫星通信等无线通信方式进行通信。通过车辆和服务器之间的通信，服务器可以收集传感器采集到的信号进行计算，并将计算结果回传给对应的车辆。
在一种可能的实现方式中，本申请实施例的信号处理系统还可以包括前置放大器和功率放大器。前置放大器可以用于将第二传感器采集的残差信号放大至一定的电平范围内，功率放大器可以用于将音频信号放大以驱动扬声器发出对应的声波。
在进行车辆内主动降噪的过程中，由于车辆的车身结构复杂，工况不稳定，当前的车内降噪方法并不能很好的依据当前的降噪效果进行实时调整，降噪效果不好。通过本申请实施例的信号处理方法，在对参考信号进行处理以确定音频信号进行主动降噪的过程中，还利用了残差信号，以对进行处理时的参数进行调整，从而可以实现根据当前的降噪效果实时的进行调整，动态地改变音频信号。由此，可以通过动态调整的音频信号与人耳处的噪声信号抵消，获得更大的降噪量，实现快速降噪，得到更好的降噪效果。
以下以图2-图3为例，在上述信号处理系统的基础上，对本申请实施例的信号处理方法进行详细的介绍：
图2示出了根据本申请一实施例的信号处理方法的流程图。该方法可用于上述信号处理系统。如图2所述，该方法可包括：
步骤S201，第一传感器采集参考信号。
其中，第一传感器可以是一个或多个。第一传感器采集的参考信号可以参见图中x(n)。n可以对应于当前的时刻，表示信号序列中的序号，即当前时刻采集的信号为信号序列中的第n个信号。参考信号可以是多通道信号，即一个x(n)可以对应一组信号，其中，每组信号中的一个信号对应一个通道。
步骤S202，第二传感器采集残差信号。
参见图2，∑可以指参考信号与音频信号在误差点求和，即参考信号与音频信号在误差点相抵消，抵消后残留的信号即残差信号。误差点即放置第二传感器的位置，可以是人耳附近的任意位置，例如人左耳附近和/或人右耳附近的任意位置，相应的，第二传感器可以设置有一个或多个。如果存在多个驾乘人员，还可以设置有对应的多个第二传感器。图中d(n)可以表示实际的初级噪声信号，对应着实际上到达误差点的噪声。图中G可以表示实际的次级路径，次级路径可以指从扬声器到误差点声波传递的路径。
在实际车辆中，扬声器发出的音频信号(如图中y(n))经过次级路径G到达误差点后，会与d(n)相互抵消，抵消后，第二传感器可以采集到的信号即残留的残差信号，可以参见图中e(n)，e(n)可以指示驾乘人员在降噪后实际听到的噪声。本申请中通过利用误差点处的第二传感器采集的e(n)可以更好的了解到当前的降噪效果，有助于更有针对性地调整相关参数，提高降噪效果。
本申请中，在得到参考信号和残差信号后，可以结合已知的音频信号，确定利用次级路 径的传输函数对应的滤波器滤波后的参考信号，并计算出初级噪声信号，利用这两个信号更新用于得到音频信号的维纳滤波器(可以以W表示)的相关参数。从而可以动态地调整输出的音频信号。
在一种可能的实现方式中，在对W的相关参数更新的过程中，可以利用滑动窗口算法计算相关参数。即，对于部分参数，可以不用逐点计算，以节省计算量。
图3示出根据本申请一实施例的滑动窗口的示意图。如图3所示，图中的长方形框可以对应于滑动窗口，坐标轴上的每个点可以对应一个信号。其中，n可以对应于当前的信号，例如对应x(n)。N可以表示滑动窗口的长度，即一个滑动窗口对应N个信号。M可以表示滑动窗口的移动距离，即每隔M个信号，计算一次相应的参数。
在图3所示的过程中，滑动窗口移动了2次，分别从对应信号n-M的位置移动到了对应信号n的位置，再从对应信号n的位置移动到了对应信号n+M的位置。在此过程中，对应上述三个位置可以分别进行三次计算。
滑动窗口算法可以用于下述步骤S203-步骤S208的相关过程中。参见图3，在对W的参数进行更新过程中，可以每隔M个信号，执行一次步骤S203-步骤S208中的相关过程，根据包括当前信号及当前信号之前N-1个信号的共N个信号，重新计算相关的参数。
步骤S203，处理器根据次级路径的传输函数对参考信号进行滤波，确定滤波后的参考信号。
由于参考信号在经过滤波得到音频信号后还需要经过次级路径才能到达误差点，因此，本申请中首先计算出经过次级路径后的参考信号(即滤波后的参考信号，参见图2中x g(n))。再根据该信号来调整确定音频信号的滤波的参数，在此过程中考虑到了次级路径对降噪效果的影响，由此可以实现更好的降噪效果。
其中，次级路径的传输函数可以参见图2中
Figure PCTCN2021125919-appb-000001
在一种可能的实现方式中，可以利用扬声器播放白噪信号，并记录第二传感器采集的信号，由此估计次级路径的传输函数。其中，可以利用最小均方(least mean square，LMS)算法或维纳滤波估计次级路径，得到次级路径的传输函数，也可以利用其它的方式。
在一种可能的实现方式中，可以利用滑动窗口算法，每隔M个参考信号，根据次级路径的传输函数对参考信号进行一次滤波，确定滤波后的参考信号。
步骤S204，处理器根据残差信号、以及根据次级路径的传输函数对音频信号进行滤波后的音频信号，确定初级噪声信号。
在确定滤波后的参考信号x g(n)之后，本申请中还需要计算出误差点处的初级噪声信号d(n)，由此，在更新确定音频信号的滤波的参数时，可以利用滤波后的参考信号和初级噪声信号的相关性来调整参数，使得最终确定的音频信号可以更好地与人耳处的噪声信号抵消。
其中，由于在实际主动降噪的过程中，初级噪声信号已与音频信号相抵消，无法直接采集得到。为了实现动态地调整用于确定音频信号的维纳滤波器的相关参数，本申请中根据采集到的残差信号、音频信号，利用确定的次级路径的传输函数计算重构出初级噪声信号(参见图2中
Figure PCTCN2021125919-appb-000002
)。
确定初级噪声信号的一种方式可参见公式(1)：
Figure PCTCN2021125919-appb-000003
其中，J可以表示次级路径的传输函数
Figure PCTCN2021125919-appb-000004
对应的滤波器的长度的最大值，滤波器的长度可以表示滤波器进行一次滤波时滤波的信号个数(即滤波器一次处理的输入信号的采样点数)。I可以表示用于确定音频信号的维纳滤波器W的长度的最大值，可以表示维纳滤波器进行一次 滤波时滤波的信号个数。
Figure PCTCN2021125919-appb-000005
可以表示对参考信号x(n)经过W滤波后得到的音频信号y(n),
Figure PCTCN2021125919-appb-000006
可以表示对y(n)经过
Figure PCTCN2021125919-appb-000007
滤波后得到的到达误差点的音频信号。由此，可以根据采集到的残差信号反推出初级噪声信号。
在一种可能的实现方式中，可以利用滑动窗口算法，每隔M个残差信号、以及根据次级路径的传输函数对音频信号进行滤波后的音频信号，确定一次初级噪声信号。
步骤S205，处理器根据滤波后的参考信号，确定自相关矩阵。
确定自相关矩阵的一种方法可以参见公式(2)：
Figure PCTCN2021125919-appb-000008
其中，R xx(n)可以表示x g(n)对应的自相关矩阵，可以指示x g(n)的自相关程度。
Figure PCTCN2021125919-appb-000009
可以表示x g(n)的转置矩阵。
在一种可能的实现方式中，利用图3所示的滑动窗口算法，可以每隔M个经过
Figure PCTCN2021125919-appb-000010
滤波后的参考信号，获取前N个该信号以计算x g(n)对应的自相关矩阵。
利用滑动窗口算法确定自相关矩阵的一种方法可以参见公式(3)：
Figure PCTCN2021125919-appb-000011
其中，N可以表示滑动窗口的长度。
步骤S206，处理器根据滤波后的参考信号和初级噪声信号，确定互相关矩阵。
确定互相关矩阵的一种方法可以参见公式(4)：
Figure PCTCN2021125919-appb-000012
其中，R xd(n)可以表示x g(n)和
Figure PCTCN2021125919-appb-000013
对应的自相关矩阵，可以指示x g(n)与
Figure PCTCN2021125919-appb-000014
之间的相关程度。
Figure PCTCN2021125919-appb-000015
可以表示
Figure PCTCN2021125919-appb-000016
的转置矩阵。
在一种可能的实现方式中，利用图3所示的滑动窗口算法，可以每隔M个经过
Figure PCTCN2021125919-appb-000017
滤波后的参考信号，同时每隔M个点计算一次
Figure PCTCN2021125919-appb-000018
并获取前N个上述信号以计算x g(n)和
Figure PCTCN2021125919-appb-000019
对应的互相关矩阵。
利用滑动窗口算法确定互相关矩阵的一种方法可以参见公式(5)：
Figure PCTCN2021125919-appb-000020
其中，N可以表示滑动窗口的长度。
步骤S207，处理器根据自相关矩阵和互相关矩阵，更新用于确定音频信号的维纳滤波的系数。
其中，可以根据自相关矩阵和互相关矩阵，确定维纳滤波器系数目标方向W wn(n)。确定W wn(n)的一种方法可以参见公式(6)：
Figure PCTCN2021125919-appb-000021
其中，
Figure PCTCN2021125919-appb-000022
可以表示R xx(n)的逆矩阵。
接着,可以根据维纳滤波器的目标方向W wn(n)和上一个维纳滤波系数W(n-1)的差值，确定滤波器的变动方向ΔW(n)，参见公式(7)：
ΔW(n)＝W wn(n)-W(n-1)     (7)
由此，可以确定当前W对应的系数W(n)，确定W(n)的一种方法可参见公式(8)：
Figure PCTCN2021125919-appb-000023
其中，μ可以表示维纳滤波器的变化幅度。L可以表示维纳滤波器的长度，L的值可以与滑动窗口的长度N的值一致，由此可以获得更好的降噪效果。
需要说明的是，为了防止跳变噪声，处理器需要逐点更新W对应的系数W(n)。例如，本申请中可以利用滑动窗口算法，每隔M个点更新一次ΔW(n)。但为了防止跳变噪声，对于每 个参考信号，都需要利用当前的ΔW(n)(不管是否更新)、μ和L，更新对应的维纳滤波器W(n)。
步骤S208，处理器根据初级噪声信号和残差信号，确定降噪量，根据确定的降噪量对维纳滤波器的参数和滑动窗的参数进行调整。
本申请中，为了根据当前的降噪效果对降噪状态进行调整，获得更大的降噪量和更快速、响应及时的降噪速度，可以首先确定降噪量，据此调整相关参数。
确定降噪量(Noise Reduction，NR)的一种方法可参见公式(9)：
Figure PCTCN2021125919-appb-000024
其中，P d(n)和P e(n)可以分别表示
Figure PCTCN2021125919-appb-000025
和e(n)对应的功率。确定P d(n)和P e(n)的一种方法可分别参见公式(10)和公式(11)：
Figure PCTCN2021125919-appb-000026
P e(n)＝(1-α)P e(n-1)-αe 2(n)        (11)
其中，α可以表示用于控制滑动速度的参数，可以预先设定，α的值例如是0.01。
在一种可能的实现方式中，可以根据计算出的降噪量，对维纳滤波器的参数和滑动窗的参数进行调整，可调整的参数例如可以包括维纳滤波器系数的变动幅度μ、维纳滤波器的长度L、滑动窗口的移动距离M、滑动窗口的长度N等。其中，降噪量的大小可以与μ成反比，与L、M、N成正比。
还可以根据降噪量NR的大小确定上述参数的值，根据NR确定L的一种方法可参见公式(12)：
L＝r(NR)*I        (12)
其中，I可以表示维纳滤波器长度对应的最大值，可以预先设定。在一种可能的实现方式中，M可以根据L的值确定，M和L的值可以是相等的。r(NR)可以表示根据NR确定的比例系数。
根据NR确定N的一种方法可参见公式(13)：
N＝r(NR)*N 0          (13)
其中，N 0的值可以表示滑动窗口的长度对应的最大值，可以预先设定。
根据NR确定μ的一种方法可参见公式(14)：
Figure PCTCN2021125919-appb-000027
其中，μ 0可以表示维纳滤波器系数的变动幅度对应的最大值，可以与预先设定。r μ(NR)可以表示根据NR确定的比例系数。
根据NR确定r(NR)的一种方法可参见公式(15)：
Figure PCTCN2021125919-appb-000028
其中，β 1、β 2、β 3为预设的参数。β 1可以用于约束r(NR)的下限，β 1的取值范围例如是0.05-0.1。β 2可以用于调整函数的斜率，β 2的值越大，可以表示对应的参数随降噪量调整越快。β 3可以用于确定降噪量为0时r(NR)的值，用于指示r(NR)开始增加时的起始降噪量。
根据NR确定r μ(NR)的一种方法可参见公式(16)：
Figure PCTCN2021125919-appb-000029
其中，β 4、β 5、β 6为预设的参数。β 1可以用于约束r μ(NR)的下限，β 4的取值范围例如是0.05-0.1。β 5可以用于调整函数的斜率，β 5的值越大，可以表示对应的参数随降噪量调整越快。β 6可以用于确定降噪量为0时r μ(NR)的值，用于指示r μ(NR)开始增加时的起始降噪量。
需要说明的是，β 1和β 4的值可以相同，也可以不同。对于β 2和β 5、β 3和β 6同理。
步骤S209，处理器根据确定的维纳滤波器的系数对参考信号进行维纳滤波，确定音频信号，并通过扬声器发出与音频信号对应的声波。
维纳滤波器的系数对参考信号进行维纳滤波，确定音频信号y(n)的一种方法可参见公式(17)：
Figure PCTCN2021125919-appb-000030
其中，I可以表示维纳滤波器长度L对应的最大值，可以预先设定。
由此，确定的对应的音频信号可以与人耳处的噪声信号相抵消，达到降噪的效果。
图4示出根据本申请一实施例的信号处理方法的流程图。该方法可用于上述信号处理系统。如图4所示，该方法包括：
步骤S401，接收一个或多个第一传感器采集的噪声源处的第一音频信号；
步骤S402，接收一个或多个第二传感器采集的人耳处的第二音频信号，所述第一音频信号和所述第二音频信号用于确定根据第一处理方式对所述第一音频信号进行处理的参数；
步骤S403，发送根据所述第一处理方式对所述第一音频信号进行处理后确定的第三音频信号，所述第三音频信号用于指示扬声器发出声波，所述声波用于与人耳处的噪声相抵消。
根据本申请实施例，通过在对第一音频信号进行处理的过程中，利用了人耳处采集的第二音频信号进行实时的参数调整，第二音频信号是人耳处的实际噪声，即被第三音频信号第三音频扬声器产生的声波抵消后剩余的噪声(即上文中的残差信号)，由此，利用调整后的参数对第一音频信号进行处理得到第三音频信号，以指示扬声器发出声波来抵消噪音，可以实现更快速的降噪，且具有更大的降噪量，降噪效果更好，提升了驾乘人员的舒适度。
其中，第一音频信号可以是上述参考信号x(n)，第二音频信号可以是上述残差信号e(n)，第三音频信号可以是上述音频信号y(n)。人耳处的第二音频信号可以是车内驾乘人员的人耳附近预设范围内任意位置采集到的残差信号。多个第一传感器可以设置在不同的位置，多个第二传感器也可以设置在不同的位置。
在一种可能的实现方式中，该第一处理方式为维纳滤波。由此，可以得到更大的降噪量，且可以实现更快速地降噪。第一处理方式也可为能够对第一音频信号进行处理来确定的第三音频信号的其他处理方式。
根据第一处理方式对所述第一音频信号进行处理的参数可以例如是上述维纳滤波器W的系数。
扬声器发出的声波与人耳处的噪声相抵消后，车内驾乘人员听到噪声量会下降。
步骤S401的示例可参见图2中步骤S201，步骤S402的示例可参见图2中步骤S202，步骤S403的示例可参见图2中步骤S209中的相关叙述。
图5示出根据本申请一实施例的信号处理方法的流程图。如图5所示，该方法还包括：
步骤S501，根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，所述第二处理方式指示声波从所述扬声器传输至所述第二传感器的传输方式；
步骤S502，根据所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号；
步骤S503，根据所述第四音频信号和所述第五音频信号，确定根据所述第一处理方式对所述第一音频信号进行处理的参数。
根据本申请实施例，通过估计从所述扬声器传输至所述第二传感器的传输方式，确定第 四音频信号，考虑了第一音频信号的传输过程，同时，重构出第五音频信号，可以计算出驾乘人员听到的降噪前的初始噪声，结合二者对参数进行调整，可以使得调整后的参数指示的扬声器发出的对应声波能够更好地与噪声相抵消，从而获得更大的降噪量。同时，通过根据上述二者对参数的实时计算，可以及时调整参数，使得在出现干扰时可以更快的恢复降噪状态，鲁棒性更强。从而得到更好的降噪效果。
其中，第二处理方式可以例如上述次级路径的传输函数
Figure PCTCN2021125919-appb-000031
第四音频信号可以是根据次级路径的传输函数对参考信号进行滤波后的参考信号x g(n)。第五音频信号可以是上述计算出的初级噪声信号
Figure PCTCN2021125919-appb-000032
步骤S501的示例可参见图2中步骤S203，步骤S502的示例可参见图2中步骤S204，步骤S503的示例可参见图2中步骤S205-S207中的相关叙述。
在一种可能的实现方式中，根据所述第四音频信号和所述第五音频信号，确定根据第一处理方式对所述第一音频信号进行处理的参数，包括：根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的所述参数。
由此，可以在调整参数的过程中同时考虑到第四音频信号的自相关程度，以及第四音频信号和第五音频信号的互相关程度，实现更好的降噪效果。
自相关矩阵的确定过程的示例可以参见图2中步骤S205，互相关矩阵的确定过程的示例可以参见图2中步骤S206。根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定对所述第一音频信号根据第一处理方式进行处理的参数的示例可参见图2中步骤S207中的相关叙述。
图6示出根据本申请一实施例的信号处理方法的流程图。如图6所示，根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的参数，包括：
步骤S601，根据所述自相关矩阵、所述互相关矩阵、和上一时刻的参数，确定所述参数的变化方向；
步骤S602，根据以下中的一种或多种：上一时刻的参数、根据第一处理方式进行处理时的信号长度、所述参数的变化方向、所述参数的变化幅度，确定当前时刻的参数。
根据本申请实施例，通过在每一时刻确定当前时刻的参数，可以在稳定大降噪量且实现快速降噪的基础上，避免不及时更新参数导致的滤波器突变带来的噪声，提高驾乘人员的体验舒适度。
其中，参数的变化方向可以是上述ΔW(n)，根据第一处理方式进行处理时的信号长度可以是指每次处理时的信号长度，可以是上述维纳滤波器的长度L。参数的变化幅度可以是上述μ，当前时刻的参数可以是上述当前的维纳滤波器的系数W(n)。上一时刻可以是指当前时刻的前一时刻，上一时刻的参数可以是上述W(n-1)。
步骤S601-步骤S602的示例可参见上述图2中步骤S207。
在一种可能的实现方式中根据所述传输方式，根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，包括：每隔预定窗口移动距离，对预定窗口长度的所述第一音频信号根据所述第二处理方式进行处理，确定所述第四音频信号；
根据所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号，包括：每隔所述预定窗口移动距离，根据所述预定窗口长度的所 述第二音频信号、以及根据所述第二处理方式对所述第三音频信号进行处理后的音频信号，确定所述第五音频信号。
根据本申请实施例，可以实现利用预定窗口进行计算，不必逐点确定第四音频信号和第五音频信号，减少计算量。
其中，窗口可以参见上文图3所示滑动窗口，预定窗口移动距离可以是上文中滑动窗口的移动距离M、预定窗口长度可以是上文中滑动窗口的长度N。
上述过程可参见图2中步骤S203-步骤S204中的相关示例。
图7示出根据本申请一实施例的信号处理方法的流程图。如图7所示，该方法还包括：
步骤S701，根据所述第二音频信号和所述第五音频信号，确定降噪量；
步骤S702，根据所述降噪量，对以下中的一种或多种进行调整：所述参数的变化幅度、根据第一处理方式进行处理时的信号长度、所述预定窗口移动距离、所述预定窗口长度。
根据本申请实施例，通过计算降噪量，并根据降噪量对以下中的一种或多种进行调整：参数的变化幅度、信号长度、预定窗口移动距离、预定窗口长度，可以使得在降噪的过程中适应于不同的降噪环境和状态，达到更好的降噪效果，提高用户的体验。
其中，降噪量可例如上文中NR。所述降噪量的值越小，表示需要降低噪声的功率越大、需要降低噪声的速度越快。进行调整后，所述降噪量的值越小，对应所述参数的变化幅度越大、所述信号长度越小、所述预定窗口移动距离越小、所述预定窗口长度越小，所述降噪量的值越大，对应所述参数的变化幅度越小、所述信号长度越大、所述预定窗口移动距离越大、所述预定窗口长度越大。
步骤S701-步骤S702的示例可参见上文中步骤S208中的相关叙述。
图8示出根据本申请实施例的信号处理装置的结构图。如图8所示，该装置包括：
第一接收模块801，用于接收一个或多个第一传感器采集的噪声源处的第一音频信号；
第二接收模块802，用于接收一个或多个第二传感器采集的人耳处的第二音频信号，所述第一音频信号和所述第二音频信号用于确定根据第一处理方式对所述第一音频信号进行处理的参数；
发送模块803，用于发送根据所述第一处理方式对所述第一音频信号进行处理后确定的第三音频信号，所述第三音频信号用于指示扬声器发出声波，所述声波用于与人耳处的噪声相抵消。
根据本申请实施例，通过在对第一音频信号进行处理的过程中，利用了人耳处采集的第二音频信号进行实时的参数调整，由此可以考虑到当前的降噪状态，并根据当前的降噪状态对参数进行调整。由此，利用调整后的参数对第一音频信号进行处理得到第三音频信号，以指示扬声器发出声波来抵消噪声，可以实现更快速的降噪，且具有更大的降噪量，降噪效果更好，提升了驾乘人员的舒适度。
在一种可能的实现方式中，该第一处理方式为维纳滤波。
由此，可以得到更大的降噪量，且可以实现更快速地降噪。
在一种可能的实现方式中，该装置还包括：第一确定模块，用于根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，所述第二处理方式指示声波从所述扬声器传输至所述第二传感器的传输方式；第二确定模块，用于根据所述第二音频信号、以及根据所述第二处理方式对所述第三音频信号进行处理后的音频信号，确定第五音频信号；第三确 定模块，用于根据所述第四音频信号和所述第五音频信号，确定根据所述第一处理方式对所述第一音频信号进行处理的参数。
根据本申请实施例，通过估计从所述扬声器传输至所述第二传感器的传输方式，确定第四音频信号，考虑了第一音频信号的传输过程，同时，重构出第五音频信号，可以计算出驾乘人员听到的降噪前的初始噪声，结合二者对参数进行调整，可以使得调整后的参数指示的扬声器发出的对应声波能够更好地与噪声相抵消，从而获得更大的降噪量。同时，通过根据上述二者对参数的实时计算，可以及时调整参数，使得在出现干扰时可以更快的恢复降噪状态，鲁棒性更强。从而得到更好的降噪效果。
在一种可能的实现方式中，第三确定模块包括：根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的所述参数。
由此，可以在调整参数的过程中同时考虑到第四音频信号的自相关程度，以及第四音频信号和第五音频信号的互相关程度，实现更好的降噪效果。
在一种可能的实现方式中，根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据第一处理方式对所述第一音频信号进行处理的所述参数，包括：根据所述自相关矩阵、所述互相关矩阵、和上一时刻的参数，确定所述参数的变化方向；根据以下中的一种或多种：所述上一时刻的参数、根据第一处理方式进行处理时的信号长度、所述参数的变化方向、所述参数的变化幅度，确定当前时刻的所述参数。
根据本申请实施例，通过在每一时刻确定当前时刻的参数，可以在稳定大降噪量且实现快速降噪的基础上，避免不及时更新参数导致的滤波器突变带来的噪声，提高驾乘人员的体验舒适度。
在一种可能的实现方式中，第一确定模块，包括：每隔预定窗口移动距离，对预定窗口长度的所述第一音频信号根据所述第二处理方式进行处理，确定第四音频信号；第二确定模块，包括：每隔预定窗口移动距离，根据预定窗口长度的所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号。
根据本申请实施例，可以实现利用预定窗口进行计算，不必逐点确定第四音频信号和第五音频信号，减少计算量。
在一种可能的实现方式中，该装置还包括：第四确定模块，用于根据所述第二音频信号和所述第五音频信号，确定降噪量；调整模块，用于根据所述降噪量，对以下中的一种或多种进行调整：所述参数的变化幅度、根据第一处理方式进行处理时的信号长度、所述预定窗口移动距离、所述预定窗口长度。
根据本申请实施例，通过计算降噪量，并根据降噪量对以下中的一种或多种进行调整：参数的变化幅度、信号长度、预定窗口移动距离、预定窗口长度，可以使得在降噪的过程中适应于不同的降噪环境和状态，达到更好的降噪效果，提高用户的体验。
图9示出根据本申请实施例的信号处理装置的结构图。该信号处理装置可适用于图1示出的信号处理系统中，执行上述图2-图7中任一项所示出的信号处理方法。
如图9所示，信号处理装置900可以包括处理器901和收发器902。可选地，信号处理装置900可以包括存储器903。其中，处理器901与收发器902和存储器903耦合，如可以通过通信总线连接。
下面结合图9对信号处理装置900的各个构成部件进行具体的介绍。
上述处理器901是信号处理装置900的控制中心，可以是一个处理器，也可以是多个处理元件的统称。例如，处理器901是一个或多个中央处理器(central processing unit，CPU)，也可以是特定集成电路(application specific integrated circuit，ASIC)，或者是被配置成实施本申请实施例的一个或多个集成电路，例如：一个或多个微处理器，或，一个或者多个现场可编程门阵列(field programmable gate array，FPGA)。
可选地，处理器901可以通过运行或执行存储在存储器903内的软件程序，以及调用存储在存储器903内的数据，执行信号处理装置900的各种功能。
在具体的实现中，作为一种实施例，处理器901可以包括一个或多个CPU，例如图9中所示出的CPU0和CPU1。
在一种可能的实现方式中，信号处理装置900也可以包括多个处理器，例如图9中所示的处理器901和处理器904。这些处理器中的每一个可以是一个单核处理器(single-CPU)，也可以是一个多核处理器(multi-CPU)。这里的处理器可以指一个或多个通信设备、电路、和/或用于处理数据(例如计算机程序指令)的处理核。
可选地，收发器902可以包括接收器和发送器(图9中未单独示出)。其中，接收器用于实现接收功能，发送器用于实现发送功能。
可选地，收发器902可以和处理器901集成在一起，也可以独立存在，并通过信号处理装置900的输入/输出端口(图9中未示出)与处理器901耦合，本申请实施例对此不作限定。
上述存储器903可用于存储执行本申请方案的软件程序，并由处理器901来控制执行，具体实现方式可以参考上述方法实施例，此处不再赘述。
其中，存储器903可以是只读存储器(read-only memory，ROM)或可存储静态信息和指令的其他类型的静态存储通信设备，随机存取存储器(random access memory，RAM)或者可存储信息和指令的其他类型的动态存储通信设备，也可以是电可擦可编程只读存储器(electrically erasable programmable read-only memory，EEPROM)、只读光盘(compact disc read-only memory，CD-ROM)或其他光盘存储、光碟存储(包括压缩光碟、激光碟、光碟、数字通用光碟、蓝关光盘碟等)、磁盘存储介质或者其他磁存储通信设备、或者能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质，但不限于此。需要说明的是，存储器903可以和处理器901集成在一起，也可以独立存在，并通过信号处理装置900的输入/输出端口(图9中未示出)与处理器901耦合，本申请实施例对此不作限定。
需要说明的是，图9中所示出的信号处理装置900的结构并不构成对信号处理装置的实现方式的限定，实际的信号处理装置可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
本申请的实施例提供了一种信号处理装置，包括：处理器和存储器；所述存储器用于存储程序；所述处理器用于执行所述存储器所存储的程序，以使所述装置实现上述方法。
本申请的实施例提供了一种计算机可读存储介质，其上存储有程序指令，当所述程序指令被计算机执行时使得计算机实现上述方法。
本申请的实施例提供了一种终端设备，该终端设备可以执行上述方法。
本申请的实施例提供了一种计算机程序产品，其包括有程序指令，当所述程序指令被计 算机执行时使得计算机实现上述方法。
本申请的实施例提供了一种车辆，该车辆包括处理器，该处理器用于执行上述方法。
计算机可读存储介质可以是可以保持和存储由指令执行设备使用的指令的有形设备。计算机可读存储介质例如可以是电存储设备、磁存储设备、光存储设备、电磁存储设备、半导体存储设备或者上述的任意合适的组合。
这里所描述的计算机可读程序指令或代码可以从计算机可读存储介质下载到各个计算/处理设备，或者通过网络、例如因特网、局域网、广域网和/或无线网下载到外部计算机或外部存储设备。网络可以包括铜传输电缆、光纤传输、无线传输、路由器、防火墙、交换机、网关计算机和/或边缘服务器。每个计算/处理设备中的网络适配卡或者网络接口从网络接收计算机可读程序指令，并转发该计算机可读程序指令，以供存储在各个计算/处理设备中的计算机可读存储介质中。
这里参照根据本申请实施例的方法、装置(系统)和计算机程序产品的流程图和/或框图描述了本申请的各个方面。应当理解，流程图和/或框图的每个方框以及流程图和/或框图中各方框的组合，都可以由计算机可读程序指令实现。
这些计算机可读程序指令可以提供给通用计算机、专用计算机或其它可编程数据处理装置的处理器，从而生产出一种机器，使得这些指令在通过计算机或其它可编程数据处理装置的处理器执行时，产生了实现流程图和/或框图中的一个或多个方框中规定的功能/动作的装置。也可以把这些计算机可读程序指令存储在计算机可读存储介质中，这些指令使得计算机、可编程数据处理装置和/或其他设备以特定方式工作，从而，存储有指令的计算机可读介质则包括一个制造品，其包括实现流程图和/或框图中的一个或多个方框中规定的功能/动作的各个方面的指令。
也可以把计算机可读程序指令加载到计算机、其它可编程数据处理装置、或其它设备上，使得在计算机、其它可编程数据处理装置或其它设备上执行一系列操作步骤，以产生计算机实现的过程，从而使得在计算机、其它可编程数据处理装置、或其它设备上执行的指令实现流程图和/或框图中的一个或多个方框中规定的功能/动作。
附图中的流程图和框图显示了根据本申请的多个实施例的装置、系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或指令的一部分，所述模块、程序段或指令的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。
也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行相应的功能或动作的硬件(例如电路或ASIC(Application Specific Integrated Circuit，专用集成电路))来实现，或者可以用硬件和软件的组合，如固件等来实现。
尽管在此结合各实施例对本申请进行了描述，然而，在实施所要求保护的本申请过程中，本领域技术人员通过查看所述附图、公开内容、以及所附权利要求书，可理解并实现所述公开实施例的其它变化。在权利要求中，“包括”(comprising)一词不排除其他组成部分或步骤，“一”或“一个”不排除多个的情况。单个处理器或其它单元可以实现权利要求中列举的若干项功能。相互不同的从属权利要求中记载了某些措施，但这并不表示这些措施不能组合 起来产生良好的效果。
以上已经描述了本申请的各实施例，上述说明是示例性的，并非穷尽性的，并且也不限于所披露的各实施例。在不偏离所说明的各实施例的范围的情况下，对于本技术领域的普通技术人员来说许多修改和变更都是显而易见的。本文中所用术语的选择，旨在最好地解释各实施例的原理、实际应用或对市场中的技术的改进，或者使本技术领域的其它普通技术人员能理解本文披露的各实施例。

Claims (18)

  1. 一种信号处理方法，其特征在于，所述方法包括：
    接收一个或多个第一传感器采集的噪声源处的第一音频信号；
    接收一个或多个第二传感器采集的人耳处的第二音频信号，所述第一音频信号和所述第二音频信号用于确定根据第一处理方式对所述第一音频信号进行处理的参数；
    发送根据所述第一处理方式对所述第一音频信号进行处理后确定的第三音频信号，所述第三音频信号用于指示扬声器发出声波，所述声波用于与人耳处的噪声相抵消。
  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：
    根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，所述第二处理方式指示声波从所述扬声器传输至所述第二传感器的传输方式；
    根据所述第二音频信号、以及根据所述第二处理方式对所述第三音频信号进行处理后的音频信号，确定第五音频信号；
    根据所述第四音频信号和所述第五音频信号，确定根据所述第一处理方式对所述第一音频信号进行处理的参数。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述第四音频信号和所述第五音频信号，确定根据所述第一处理方式对所述第一音频信号进行处理的参数，包括：
    根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据所述第一处理方式对所述第一音频信号进行处理的所述参数。
  4. 根据权利要求3所述的方法，其特征在于，所述根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据所述第一处理方式对所述第一音频信号进行处理的所述参数，包括：
    根据所述自相关矩阵、所述互相关矩阵、和上一时刻的参数，确定所述参数的变化方向；
    根据以下中的一种或多种：所述上一时刻的参数、根据所述第一处理方式进行处理时的信号长度、所述参数的变化方向、所述参数的变化幅度，确定当前时刻的所述参数。
  5. 根据权利要求2-4任意一项所述的方法，其特征在于，所述根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，包括：
    每隔预定窗口移动距离，对预定窗口长度的所述第一音频信号根据所述第二处理方式进行处理，确定所述第四音频信号；
    所述根据所述第二音频信号、以及根据所述第二处理方式对第三音频信号进行处理后的音频信号，确定第五音频信号，包括：
    每隔预定所述窗口移动距离，根据所述预定窗口长度的所述第二音频信号、以及根据所述第二处理方式对所述第三音频信号进行处理后的所述音频信号，确定所述第五音频信号。
  6. 根据权利要求5所述的方法，其特征在于，所述方法还包括：
    根据所述第二音频信号和所述第五音频信号，确定降噪量；
    根据所述降噪量，对以下中的一种或多种进行调整：所述参数的变化幅度、所述根据第一处理方式进行处理时的信号长度、所述预定窗口移动距离、所述预定窗口长度。
  7. 根据权利要求1-6任意一项所述的方法，其特征在于，所述第一处理方式为维纳滤波。
  8. 一种信号处理装置，其特征在于，所述装置包括：
    第一接收模块，用于接收一个或多个第一传感器采集的噪声源处的第一音频信号；
    第二接收模块，用于接收一个或多个第二传感器采集的人耳处的第二音频信号，所述第一音频信号和第二音频信号用于确定根据第一处理方式对所述第一音频信号进行处理的参数；
    发送模块，用于发送根据第一处理方式对所述第一音频信号进行处理后确定的第三音频信号，所述第三音频信号用于指示扬声器发出声波，所述声波用于与人耳处的噪声相抵消。
  9. 根据权利要求8所述的装置，其特征在于，所述装置还包括：
    第一确定模块，用于根据第二处理方式，对所述第一音频信号进行处理，确定第四音频信号，所述第二处理方式指示声波从所述扬声器传输至所述第二传感器的传输方式；
    第二确定模块，用于根据所述第二音频信号、以及根据所述第二处理方式对所述第三音频信号进行处理后的音频信号，确定第五音频信号；
    第三确定模块，用于根据所述第四音频信号和所述第五音频信号，确定根据所述第一处理方式对所述第一音频信号进行处理的参数。
  10. 根据权利要求9所述的装置，其特征在于，所述第三确定模块，包括：
    根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据所述第一处理方式对所述第一音频信号进行处理的所述参数。
  11. 根据权利要求10所述的装置，其特征在于，所述根据所述第四音频信号的自相关矩阵，以及所述第四音频信号和所述第五音频信号的互相关矩阵，确定根据所述第一处理方式对所述第一音频信号进行处理的所述参数，包括：
    根据所述自相关矩阵、所述互相关矩阵、和上一时刻的参数，确定所述参数的变化方向；
    根据以下中的一种或多种：所述上一时刻的参数、根据所述第一处理方式进行处理时的信号长度、所述参数的变化方向、所述参数的变化幅度，确定当前时刻的所述参数。
  12. 根据权利要求9-11任意一项所述的装置，其特征在于，所述第一确定模块，包括：
    每隔预定窗口移动距离，对预定窗口长度的所述第一音频信号根据所述第二处理方式进行处理，确定所述第四音频信号；
    所述第二确定模块，包括：
    每隔预定所述窗口移动距离，根据所述预定窗口长度的所述第二音频信号、以及根据所述第二处理方式对所述第三音频信号进行处理后的所述音频信号，确定所述第五音频信号。
  13. 根据权利要求12所述的装置，其特征在于，所述装置还包括：
    第四确定模块，用于根据所述第二音频信号和所述第五音频信号，确定降噪量；
    调整模块，用于根据所述降噪量，对以下中的一种或多种进行调整：所述参数的变化幅度、所述根据第一处理方式进行处理时的信号长度、所述预定窗口移动距离、所述预定窗口长度。
  14. 根据权利要求8-13任意一项所述的装置，其特征在于，所述第一处理方式为维纳滤波。
  15. 一种信号处理装置，其特征在于，包括：处理器和存储器；
    所述存储器用于存储程序；
    所述处理器用于执行所述存储器所存储的程序，以使所述装置实现权利要求1-7中任意一项所述的方法。
  16. 一种计算机可读存储介质，其上存储有程序指令，其特征在于，所述程序指令当被计算机执行时使得计算机实现权利要求1-7中任意一项所述的方法。
  17. 一种计算机程序产品，其包括有程序指令，其特征在于，所述程序指令当被计算机执行时使得计算机实现权利要求1-7中任意一项所述的方法。
  18. 一种车辆，其特征在于，所述车辆包括处理器，所述处理器用于执行如权利要求1-7中任意一项所述的方法。
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