In-vehicle noise reduction method, device and vehicle based on pedestrian warning sound

Abstract

The present invention discloses a method for reducing in-vehicle noise based on pedestrian alert sounds, comprising: obtaining an external in-vehicle alert sound signal and its corresponding original in-vehicle alert sound signal, wherein the external in-vehicle alert sound signal is a signal collected by an external microphone after the original in-vehicle alert sound signal is emitted by an in-vehicle alert sound speaker; extracting a target noise signal from the external in-vehicle alert sound signal based on the original in-vehicle alert sound signal; obtaining a control signal for the in-vehicle speaker using an adaptive control algorithm based on the target noise signal; and transmitting the control signal to the in-vehicle speaker, causing the in-vehicle speaker to emit sound to offset the target noise signal. The present invention effectively filters out noise components from the external in-vehicle alert sound signal transmitted into the vehicle, thereby improving the in-vehicle noise reduction effect and enhancing the in-vehicle sound quality.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a method, device and vehicle for reducing in-vehicle noise based on pedestrian prompt sound. Background Art

[0002] Regulations regarding pedestrian warning sounds require existing electric vehicles or vehicles equipped with external warning systems to provide pedestrian warning sounds that meet minimum sound level requirements. However, the low-frequency component of pedestrian warning sounds can easily be transmitted into the vehicle cabin, thereby affecting the interior sound quality.

[0003] To reduce in-vehicle noise, fuel vehicles typically use CAN signals as reference signals for in-vehicle noise reduction. If a similar solution as for fuel vehicles is used in electric vehicles, the signal-to-noise ratio of the reference signal for in-vehicle noise reduction will be low, and it can only reduce the frequency components of the prompt sound related to the vehicle speed, but cannot reduce the frequency components unrelated to the vehicle speed, and thus cannot effectively reduce the prompt sound.

[0004] Pedestrian warning sounds on electric vehicles are typically transmitted through external speakers. The amplitude and phase information of each frequency component in the warning sound will change depending on the transmission path. Existing electric vehicle warning sound noise reduction methods do not consider the changes in the amplitude and phase information of each frequency component after the warning sound is transmitted into the vehicle, resulting in poor in-vehicle noise reduction. They also fail to retain external environmental noise signals that may affect driving safety, such as horns and alarms from nearby vehicles, resulting in poor in-vehicle noise reduction quality. Summary of the Invention

[0005] The embodiments of the present invention provide a method, device and vehicle for reducing in-vehicle noise based on pedestrian prompt sounds, so as to solve the problem that the existing prompt sound noise reduction method has poor noise reduction effect.

[0006] A method for reducing in-vehicle noise based on pedestrian warning sounds, comprising:

[0007] Obtaining an external vehicle prompt sound signal and its corresponding original prompt sound signal, wherein the external vehicle prompt sound signal is a signal collected by an external vehicle microphone after the original prompt sound signal is emitted by a prompt sound speaker;

[0008] extracting a target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal;

[0009] According to the target noise signal, a control signal of a speaker in the vehicle is obtained by an adaptive control algorithm;

[0010] The control signal is sent to the in-vehicle speaker, causing the in-vehicle speaker to emit sound to cancel the target noise signal.

[0011] Optionally, extracting a target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal includes:

[0012] Performing fast Fourier transform on the original prompt sound signal and the external vehicle prompt sound signal respectively to obtain an original prompt audio domain signal and an external vehicle prompt audio domain signal;

[0013] Comparing the amplitude of the original prompt audio domain signal with a preset amplitude threshold;

[0014] Acquire a frequency band range in which the amplitude of the original prompt audio domain signal is greater than or equal to the preset amplitude threshold;

[0015] Acquire an external vehicle prompt audio domain signal falling within the frequency band as a frequency domain signal of the target noise;

[0016] Performing inverse fast Fourier transform and smoothing processing on the frequency domain signal of the target noise to obtain a target noise signal.

[0017] Optionally, acquiring a control signal for an in-vehicle speaker by using an adaptive control algorithm according to the target noise signal includes:

[0018] Obtain the transfer function matrix corresponding to the secondary sound channel in the vehicle;

[0019] Acquire a filtered signal according to the target noise signal and the transfer function matrix;

[0020] Obtaining an in-vehicle prompt sound signal and a sound signal from an in-vehicle speaker, and calculating an error signal between the in-vehicle prompt sound signal and the sound signal, wherein the in-vehicle prompt sound signal is a signal collected by an in-vehicle microphone after the original prompt sound signal is emitted by the prompt sound speaker;

[0021] updating weight coefficients of an adaptive filter according to the error signal and the filtered signal;

[0022] A control signal of the in-vehicle speaker is obtained according to the updated weight coefficient and the filtered signal.

[0023] Optionally, when the adaptive control algorithm is a filtering-type time-domain FxLMS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0024] W(n)=W(n-1)-2μe(n)x f (n)

[0025] Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, μ represents the iteration step size, e(n) represents the error signal, and x f (n) represents the filtered signal.

[0026] Optionally, when the adaptive control algorithm is a filtering-type time-domain FxRLS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0027] W(n)=W(n-1)-g(n)e(n|n-1)

[0028] Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, e(n|n-1) represents the error signal, g(n) represents the intermediate variable and x f (n) represents the filtered signal, λ represents the forgetting factor, and C(n) represents x f (n) and the inverse correlation matrix

[0029] A vehicle interior noise reduction device based on pedestrian warning sound, comprising:

[0030] An acquisition module is used to acquire an external vehicle prompt sound signal and its corresponding original prompt sound signal, wherein the external vehicle prompt sound signal is a signal collected by an external vehicle microphone after the original prompt sound signal is emitted by the prompt sound speaker;

[0031] An extraction module, configured to extract a target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal;

[0032] an algorithm module, configured to obtain a control signal for an in-vehicle speaker through an adaptive control algorithm according to the target noise signal;

[0033] The sending module is used to send the control signal to the in-vehicle speaker, so that the in-vehicle speaker produces sound to offset the target noise signal.

[0034] Optionally, the extraction module includes:

[0035] a transform unit, configured to perform fast Fourier transform on the original prompt sound signal and the external vehicle prompt sound signal respectively to obtain an original prompt audio domain signal and an external vehicle prompt audio domain signal;

[0036] a comparing unit, configured to compare the amplitude of the original prompt audio domain signal with a preset amplitude threshold;

[0037] a frequency band acquiring unit, configured to acquire a frequency band range in which the amplitude of the original prompt audio domain signal is greater than or equal to the preset amplitude threshold;

[0038] a target acquisition unit, configured to acquire an external vehicle prompt audio domain signal falling within the frequency band as a frequency domain signal of the target noise;

[0039] The post-processing unit is used to perform inverse fast Fourier transform and smoothing processing on the frequency domain signal of the target noise to obtain the target noise signal.

[0040] Optionally, the algorithm module includes:

[0041] A matrix acquisition unit, used to obtain a transfer function matrix corresponding to the secondary sound channel in the vehicle;

[0042] a filtered signal acquisition unit, configured to acquire a filtered signal according to the target noise signal and the transfer function matrix;

[0043] a calculation unit, configured to obtain an in-vehicle prompt sound signal and a sound signal emitted by an in-vehicle speaker, and calculate an error signal between the in-vehicle prompt sound signal and the sound signal, wherein the in-vehicle prompt sound signal is a signal collected by an in-vehicle microphone after the original prompt sound signal is emitted by the prompt sound speaker;

[0044] an updating unit, configured to update a weight coefficient of an adaptive filter according to the error signal and the filtered signal;

[0045] A control signal acquisition unit is used to acquire a control signal of the in-vehicle speaker according to the updated weight coefficient and the filtered signal.

[0046] Optionally, when the adaptive control algorithm is a filtering-type time-domain FxLMS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0047] W(n)=W(n-1)-2μe(n)x f (n)

[0048] Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, μ represents the iteration step size, e(n) represents the error signal, and x f (n) represents a filtered signal; or

[0049] When the adaptive control algorithm is a filtering-type time-domain FxRLS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0050] W(n)=W(n-1)-g(n)e(n|n-1)

[0051] Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, e(n|n-1) represents the error signal, g(n) represents the intermediate variable and x f (n) represents the filtered signal, λ represents the forgetting factor, and C(n) represents x f (n) and the inverse correlation matrix

[0052] A vehicle comprises the above-mentioned in-vehicle noise reduction device based on pedestrian prompt sound.

[0053] The embodiment of the present invention obtains an external vehicle prompt sound signal and its corresponding original prompt sound signal, wherein the external vehicle prompt sound signal is a signal collected by an external vehicle microphone after the original prompt sound signal is emitted by a prompt sound speaker, and is a near-field noise signal that can more accurately reflect the assignment and phase information of various components in the prompt sound emitted by the speaker; then, a target noise signal is extracted from the external vehicle prompt sound signal according to the original prompt sound signal, thereby improving the signal-to-noise ratio of the reference signal for in-vehicle noise reduction; finally, based on the target noise signal, a control signal of the in-vehicle speaker is obtained through an adaptive control algorithm; the control signal is sent to the in-vehicle speaker, causing the in-vehicle speaker to emit sound to offset the target noise signal, thereby effectively improving the in-vehicle noise reduction effect and improving the in-vehicle sound quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0055] Figure 1 This is a schematic diagram of the actual vehicle layout of the pedestrian warning sound active noise reduction system provided by an embodiment of the present invention;

[0056] Figure 2 is a flow chart of a method for reducing in-vehicle noise based on pedestrian prompt sound provided by an embodiment of the present invention;

[0057] Figure 3 (a) is a schematic diagram of an original prompt audio domain signal provided by an embodiment of the present invention, Figure 3 (b) is a schematic diagram of an external vehicle prompt audio domain signal provided by an embodiment of the present invention, Figure 3 (c) is a schematic diagram of the frequency domain signal of the target noise and the original prompt audio domain signal provided by an embodiment of the present invention, Figure 3 (d) is a schematic diagram of a frequency domain signal of target noise extracted by a preset amplitude threshold provided in this embodiment;

[0058] Figure 4 is a flowchart of step S102 in the in-vehicle noise reduction method based on pedestrian prompt sound provided by an embodiment of the present invention;

[0059] Figure 5 is a flowchart of step S103 in the in-vehicle noise reduction method based on pedestrian prompt sound provided by an embodiment of the present invention;

[0060] Figure 6 This is a principle block diagram of an in-vehicle noise reduction device based on pedestrian prompt sound provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0062] The following is a detailed description of the in-vehicle noise reduction method based on pedestrian warning sound provided by this embodiment. Figure 1 The figure shows a schematic diagram of the actual vehicle layout of the pedestrian prompt sound active noise reduction system. The pedestrian prompt sound active noise reduction system is a multi-channel active noise reduction control system, including multiple speakers and multiple microphones. The prompt sound speaker 10 is used to emit a prompt sound to pedestrians. During the driving process of the car, the active noise controller 20 reads the current vehicle speed from the OBD interface 30, determines whether the car currently needs to emit a pedestrian prompt sound based on the current vehicle speed, and controls the prompt sound controller 70 to emit the original prompt sound signal. The external microphone 40, as a near-field microphone, is used to collect the sound signal of the prompt sound speaker, obtain the external prompt sound signal, and provide the external prompt sound signal to the active noise controller 20. The internal microphone 50 is used to collect the sound signal of the prompt sound speaker, obtain the internal prompt sound signal, and serve as the primary sound signal for the internal noise reduction. The internal speaker 60 is used to receive the control signal generated by the active noise controller 20 and make sound according to the control signal. Ideally, the sound signal of the in-car speaker 60 is superimposed on the original prompt sound signal, thereby forming a local "silent zone" in the in-car microphone 50 to achieve active noise reduction in the car.

[0063] The existing electric vehicle warning sound noise reduction method does not consider the changes in the amplitude and phase information of each frequency component after the warning sound is transmitted into the vehicle, and does not retain the external environmental noise signal related to driving safety, resulting in poor noise reduction effect in the vehicle. In order to solve the problem of poor noise reduction effect, the embodiment of the present invention proposes a vehicle noise reduction method based on pedestrian warning sound. Figure 2 The in-vehicle noise reduction method based on pedestrian prompt sound includes:

[0064] In step S101, an external vehicle prompt sound signal and its corresponding original prompt sound signal are obtained.

[0065] The original prompt sound signal refers to a digital prompt sound signal that needs to be emitted by the prompt sound speaker 10. In contrast, the external prompt sound signal refers to a signal collected by the external microphone 40 and emitted by the prompt sound speaker 10. That is, the original prompt sound signal refers to the input signal of the prompt sound speaker 10, and the external prompt sound signal refers to the output signal of the prompt sound speaker 10.

[0066] The external prompt sound signal corresponds to the original prompt sound signal one-to-one, and the external prompt sound signal generally includes the original prompt sound signal and the ambient noise of the vehicle.

[0067] In step S102 , a target noise signal is extracted from the external vehicle prompt sound signal according to the original prompt sound signal.

[0068] After obtaining the external prompt sound signal, this embodiment uses the external prompt sound signal as the reference signal of the pedestrian prompt sound active noise reduction system, filters the ambient noise component in the external prompt sound signal according to the original prompt sound signal, and extracts the signal after the original prompt sound signal is transmitted through the prompt sound speaker 10 to obtain the target noise signal. The target noise signal serves as the target object for noise reduction by the adaptive control algorithm. This embodiment uses the external prompt sound signal as the reference signal of the pedestrian prompt sound active noise reduction system, which can more accurately reflect the amplitude and phase information of each frequency component of the original prompt sound signal after it is emitted by the prompt sound speaker 10, which is conducive to improving the noise reduction effect.

[0069] Optionally, as a preferred example of the present invention, a frequency domain signal processing method can be used to extract the target noise signal from the external vehicle warning sound signal. Figure 4 As shown, the step S102 of extracting the target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal includes:

[0070] In step S401, fast Fourier transform is performed on the original prompt sound signal and the external vehicle prompt sound signal respectively to obtain an original prompt audio domain signal and an external vehicle prompt audio domain signal.

[0071] Here, the original prompt sound signal and the external prompt sound signal are both time domain signals. Through fast Fourier transform, the frequency domain signal corresponding to the original prompt sound signal and the frequency domain signal corresponding to the external prompt sound signal can be obtained.

[0072] In step S402, the amplitude of the original prompt audio domain signal is compared with a preset amplitude threshold.

[0073] This embodiment predefines an amplitude threshold in the frequency domain for the original prompt sound signal based on experience, serving as a filtering criterion for the external vehicle prompt sound signal. Each amplitude value in the original prompt sound signal is compared with the preset amplitude threshold. If the amplitude value in the original prompt sound signal is greater than or equal to the preset amplitude threshold, the frequency value corresponding to the amplitude value is retained. Otherwise, if the amplitude value in the original prompt sound signal is less than the preset amplitude threshold, the frequency value corresponding to the amplitude value is discarded.

[0074] In step S403, a frequency band range in which the amplitude of the original prompt audio domain signal is greater than or equal to the preset amplitude threshold is obtained.

[0075] By comparing and filtering in step S402, one or more frequency bands in which the amplitude of the original prompt audio domain signal is greater than or equal to the preset amplitude threshold can be obtained. The frequency bands are used as references for filtering the external vehicle prompt audio domain signal.

[0076] In step S404, an external vehicle prompt audio domain signal falling within the frequency band is acquired as a frequency domain signal of the target noise.

[0077] Here, this embodiment compares the frequency of the external vehicle prompt audio domain signal with the frequency band range, extracts the external vehicle prompt audio domain signal falling within the frequency band range as a valid signal, obtains the frequency domain signal of the target noise, and effectively removes the environmental noise component in the original external vehicle prompt sound signal.

[0078] For example, assuming that S(f) represents the original prompt audio domain signal, M(f) represents the external prompt audio domain signal collected by the external microphone 40, T(f) represents the frequency domain signal of the target noise, and a represents the preset amplitude threshold, the mathematical model for extracting the frequency domain signal of the target noise is as follows:

[0079]

[0080] In step S405, inverse fast Fourier transform and smoothing processing are performed on the frequency domain signal of the target noise to obtain a target noise signal.

[0081] After obtaining the frequency domain signal of the target noise, it is converted into a time domain signal through inverse fast Fourier transform. At the same time, the converted time domain signal is smoothed to eliminate the ripples in the flat domain signal and obtain the final target noise signal, thereby effectively improving the signal-to-noise ratio of the reference signal for in-vehicle noise reduction.

[0082] For ease of understanding, for example, Figure 3 As shown, Figure 3(a) is a schematic diagram of an original prompt audio domain signal provided by this embodiment, Figure 3 (b) is a schematic diagram of an external vehicle prompt audio domain signal provided in this embodiment, Figure 3 (c) is a schematic diagram of the frequency domain signal of the target noise and the original prompt audio domain signal provided in this embodiment, Figure 3 (d) is a schematic diagram of the frequency domain signal of the target noise extracted by the preset amplitude a provided in this embodiment.

[0083] In step S103 , a control signal for the in-vehicle speaker is obtained through an adaptive control algorithm according to the target noise signal.

[0084] Here, the embodiment of the present invention uses an adaptive control algorithm to iteratively update the weight coefficient according to the error signal between the in-car prompt sound signal collected by the in-car microphone 50 and the sound signal of the in-car speaker 60, and the target noise signal, to generate a control signal for the in-car speaker 60 and control the sound of the in-car speaker 60, so as to achieve the purpose of reducing the error signal, so that the in-car prompt sound signal collected by the in-car microphone 50 and the in-car speaker 60 are superimposed to form a silent zone, thereby realizing noise reduction in the car.

[0085] The adaptive control algorithm is a filter-X type time domain or frequency domain algorithm based on a transversal filter, including but not limited to a time domain FxLMS algorithm, a frequency domain FxLMS algorithm, a time domain FxRLS algorithm and a frequency domain FxRLS algorithm.

[0086] Alternatively, taking the time domain FxLMS algorithm and the time domain FxRLS algorithm as examples, Figure 5 As shown, the step S103 of obtaining the control signal of the in-vehicle speaker by using the adaptive control algorithm according to the target noise signal includes:

[0087] In step S501 , a transfer function matrix corresponding to the secondary sound channel in the vehicle is obtained.

[0088] Here, this embodiment pre-identifies the various secondary sound channels in the vehicle and obtains the corresponding transfer function matrix.

[0089] In step S502, a filtered signal is obtained according to the target noise signal and the transfer function matrix.

[0090] This embodiment obtains the convolution between the target noise signal and the transfer function matrix as the filter function corresponding to the target noise signal. The calculation formula is as follows:

[0091]

[0092] Among them, x f(n) represents the filter function, x(n) represents the target noise signal, represents the transfer function matrix.

[0093] In step S503, an in-vehicle prompt sound signal and a sound signal of an in-vehicle speaker are obtained, and an error signal between the in-vehicle prompt sound signal and the sound signal is calculated.

[0094] Here, in contrast to the external prompt sound signal, the internal prompt sound signal is the signal collected by the internal microphone 50 after the original prompt sound signal is emitted by the prompt sound speaker 10. It is the actual internal sound signal and serves as the primary sound wave of the adaptive control algorithm; the sound signal of the internal speaker 60 serves as the secondary sound wave. Ideally, the superposition of the internal prompt sound signal and the sound signal of the internal speaker 60 will cancel out the original prompt sound signal. Adaptive control is to achieve a stable state of the control system through cyclic iteration. Therefore, this embodiment needs to calculate the error signal between the internal prompt sound signal and the sound signal of the internal speaker 60. The calculation formula is as follows:

[0095] e(n)=d(n)-y(n)

[0096] Wherein, e(n) represents the error signal, d(n) represents the in-car prompt sound signal, and y(n) represents the sound signal of the in-car speaker.

[0097] In step S504, the weight coefficients of the adaptive filter are updated according to the error signal and the filtered signal.

[0098] Here, the weight coefficient represents the importance of the target noise signal to the control signal. In each iterative control, the weight coefficient needs to be adjusted to adjust the control signal.

[0099] Optionally, as a preferred example of the present invention, when the adaptive control algorithm is a filtering-type time-domain FxLMS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0100] W(n)=W(n-1)-2μe(n)x f (n)

[0101] Among them, W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, μ represents the iteration step size, which is set according to experience, e(n) represents the error signal, and x f (n) represents the filtered signal.

[0102] Optionally, as another preferred example of the present invention, when the adaptive control algorithm is a filtering-type time-domain FxRLS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0103] W(n)=W(n-1)-g(n)e(n|n-1)

[0104] Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, e(n|n-1) represents the error signal, g(n) represents the intermediate variable and x f (n) represents the filtered signal, λ represents the forgetting factor, and C(n) represents x f (n) and the inverse correlation matrix

[0105] In step S505 , a control signal of the in-vehicle speaker is obtained according to the updated weight coefficient and the filtered signal.

[0106] Finally, based on the updated weight coefficients and filtered signal, the response of the adaptive filter to the input signal, that is, the target noise signal, is calculated to obtain the control signal. The calculation formula is:

[0107] u(n)=x f T (n)W(n)

[0108] Wherein, u(n) represents the control signal, and x f T (n) represents the filtered signal x f The transpose of (n).

[0109] In step S104 , the control signal is sent to the in-vehicle speaker, causing the in-vehicle speaker to emit sound to cancel the target noise signal.

[0110] After receiving the control signal, the control signal is sent to the in-vehicle speaker 60 to drive the in-vehicle speaker 60 to emit secondary sound waves. Steps S501 to S505 and S104 are iterated until the system reaches stability. At this point, the sound signal from the in-vehicle speaker 60 is superimposed on the target noise signal, forming a local "anechoic quiet zone" at the in-vehicle microphone 50. This reduces the impact of the original prompt sound signal on the vehicle interior, achieving active noise reduction in the vehicle interior, eliminating the original prompt sound signal transmitted into the vehicle interior, and still retaining the ambient noise that is related to driver safety.

[0111] In summary, the embodiments of the present invention obtain an external vehicle warning sound signal and its corresponding original warning sound signal, wherein the external vehicle warning sound signal is a signal collected by an external vehicle microphone after the original warning sound signal is emitted by the warning sound speaker. It is a near-field noise signal that can more accurately reflect the changes in the amplitude and phase information of each frequency component in the warning sound emitted by the speaker. Then, based on the original warning sound signal, a target noise signal is extracted from the external vehicle warning sound signal, thereby improving the signal-to-noise ratio of the reference signal for in-vehicle noise reduction. Finally, based on the target noise signal, a control signal for the in-vehicle speaker is obtained through an adaptive control algorithm. The control signal is sent to the in-vehicle speaker, causing the in-vehicle speaker to emit sound to offset the target noise signal, thereby reducing the impact of the original warning sound signal on the vehicle interior and effectively improving the in-vehicle noise reduction effect. This not only meets the minimum sound level requirements of relevant regulations on pedestrian warning sounds for electric vehicles, but also eliminates the low-frequency components of the pedestrian warning sound transmitted to the vehicle interior, while also retaining the ambient noise related to driver safety, greatly improving the in-vehicle sound quality.

[0112] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0113] In one embodiment, a vehicle interior noise reduction device based on pedestrian prompt sound is provided, and the vehicle interior noise reduction device based on pedestrian prompt sound corresponds one-to-one with the vehicle interior noise reduction method based on pedestrian prompt sound in the above embodiment. Figure 6 As shown, the in-vehicle noise reduction device based on pedestrian prompt sound includes an acquisition module 61, an extraction module 62, an algorithm module 63, and a sending module 64. The detailed description of each functional module is as follows:

[0114] An acquisition module 61 is configured to acquire an external vehicle prompt sound signal and its corresponding original prompt sound signal, wherein the external vehicle prompt sound signal is a signal collected by an external vehicle microphone after the original prompt sound signal is emitted by a prompt sound speaker;

[0115] An extraction module 62 is configured to extract a target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal;

[0116] an algorithm module 63 for obtaining a control signal for a speaker in the vehicle through an adaptive control algorithm according to the target noise signal;

[0117] The sending module 64 is configured to send the control signal to the in-vehicle speaker, causing the in-vehicle speaker to emit sound to cancel the target noise signal.

[0118] Optionally, the extraction module 62 includes:

[0119] a transform unit, configured to perform fast Fourier transform on the original prompt sound signal and the external vehicle prompt sound signal respectively to obtain an original prompt audio domain signal and an external vehicle prompt audio domain signal;

[0120] a comparing unit, configured to compare the amplitude of the original prompt audio domain signal with a preset amplitude threshold;

[0121] a frequency band acquiring unit, configured to acquire a frequency band range in which the amplitude of the original prompt audio domain signal is greater than or equal to the preset amplitude threshold;

[0122] a target acquisition unit, configured to acquire an external vehicle prompt audio domain signal falling within the frequency band as a frequency domain signal of the target noise;

[0123] The post-processing unit is used to perform inverse fast Fourier transform and smoothing processing on the frequency domain signal of the target noise to obtain the target noise signal.

[0124] Optionally, the algorithm module 63 includes:

[0125] A matrix acquisition unit, used to obtain a transfer function matrix corresponding to the secondary sound channel in the vehicle;

[0126] a filtered signal acquisition unit, configured to acquire a filtered signal according to the target noise signal and the transfer function matrix;

[0127] a calculation unit, configured to obtain an in-vehicle prompt sound signal and a sound signal emitted by an in-vehicle speaker, and calculate an error signal between the in-vehicle prompt sound signal and the sound signal, wherein the in-vehicle prompt sound signal is a signal collected by an in-vehicle microphone after the original prompt sound signal is emitted by the prompt sound speaker;

[0128] an updating unit, configured to update a weight coefficient of an adaptive filter according to the error signal and the filtered signal;

[0129] A control signal acquisition unit is used to acquire a control signal of the in-vehicle speaker according to the updated weight coefficient and the filtered signal.

[0130] Optionally, when the adaptive control algorithm is a filtering-type time-domain FxLMS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0131] W(n)=W(n-1)-2μe(n)x f (n)

[0132] Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, μ represents the iteration step size, e(n) represents the error signal, and x f (n) represents the filtered signal.

[0133] Optionally, when the adaptive control algorithm is a filtering-type time-domain FxRLS algorithm based on a transversal filter, the updating formula of the weight coefficient is:

[0134] W(n)=W(n-1)-g(n)e(n|n-1)

[0135] Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, e(n|n-1) represents the error signal, g(n) represents the intermediate variable and x f (n) represents the filtered signal, λ represents the forgetting factor, and C(n) represents x f (n) and the inverse correlation matrix

[0136] The specific limitations of the in-vehicle noise reduction device based on pedestrian alert sounds can be found in the limitations of the in-vehicle noise reduction method based on pedestrian alert sounds above and will not be further elaborated here. Each module in the aforementioned in-vehicle noise reduction device based on pedestrian alert sounds can be implemented in whole or in part through software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each of these modules.

[0137] This embodiment also provides a vehicle, which includes the above-mentioned in-vehicle noise reduction device based on pedestrian prompt sound.

[0138] Those skilled in the art will appreciate that all or part of the processes in the above-described embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described embodiments. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAM bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM).

[0139] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0140] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for reducing noise in a vehicle based on pedestrian warning sounds, characterized in that: include: Obtaining an external vehicle prompt sound signal and its corresponding original prompt sound signal, wherein the external vehicle prompt sound signal is a signal collected by an external vehicle microphone after the original prompt sound signal is emitted by a prompt sound speaker; extracting a target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal; According to the target noise signal, a control signal of a speaker in the vehicle is obtained by an adaptive control algorithm; The control signal is sent to the in-vehicle speaker, causing the in-vehicle speaker to emit sound to cancel the target noise signal.

2. The in-vehicle noise reduction method based on pedestrian warning sound according to claim 1, characterized in that: The extracting the target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal comprises: Performing fast Fourier transform on the original prompt sound signal and the external vehicle prompt sound signal respectively to obtain an original prompt audio domain signal and an external vehicle prompt audio domain signal; Comparing the amplitude of the original prompt audio domain signal with a preset amplitude threshold; Acquire a frequency band range in which the amplitude of the original prompt audio domain signal is greater than or equal to the preset amplitude threshold; Acquire an external vehicle prompt audio domain signal falling within the frequency band as a frequency domain signal of the target noise; Performing inverse fast Fourier transform and smoothing processing on the frequency domain signal of the target noise to obtain a target noise signal.

3. The in-vehicle noise reduction method based on pedestrian warning sound according to claim 2, characterized in that: The step of obtaining a control signal for an in-vehicle speaker by using an adaptive control algorithm according to the target noise signal includes: Obtain the transfer function matrix corresponding to the secondary sound channel in the vehicle; Acquire a filtered signal according to the target noise signal and the transfer function matrix; Obtaining an in-vehicle prompt sound signal and a sound signal from an in-vehicle speaker, and calculating an error signal between the in-vehicle prompt sound signal and the sound signal, wherein the in-vehicle prompt sound signal is a signal collected by an in-vehicle microphone after the original prompt sound signal is emitted by the prompt sound speaker; updating weight coefficients of an adaptive filter according to the error signal and the filtered signal; A control signal of the in-vehicle speaker is obtained according to the updated weight coefficient and the filtered signal.

4. The method for reducing in-vehicle noise based on pedestrian warning sound according to claim 3, characterized in that: When the adaptive control algorithm is a filtering-type time-domain FxLMS algorithm based on a transversal filter, the updating formula of the weight coefficient is: W(n)=W(n-1)-2μe(n)x f (n) Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, μ represents the iteration step size, e(n) represents the error signal, and x f (n) represents the filtered signal.

5. The method for reducing noise in a vehicle based on pedestrian warning sound according to claim 3, wherein: When the adaptive control algorithm is a filtering-type time-domain FxRLS algorithm based on a transversal filter, the updating formula of the weight coefficient is: W(n)=W(n-1)-g(n)e(n|n-1) Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, e(n|n-1) represents the error signal, g(n) represents the intermediate variable and x f (n) represents the filtered signal, λ represents the forgetting factor, and C(n) represents x f (n) and the inverse correlation matrix 6. A vehicle interior noise reduction device based on pedestrian warning sound, characterized in that: The device comprises: An acquisition module is used to acquire an external vehicle prompt sound signal and its corresponding original prompt sound signal, wherein the external vehicle prompt sound signal is a signal collected by an external vehicle microphone after the original prompt sound signal is emitted by the prompt sound speaker; An extraction module, configured to extract a target noise signal from the external vehicle prompt sound signal according to the original prompt sound signal; an algorithm module, configured to obtain a control signal for an in-vehicle speaker through an adaptive control algorithm according to the target noise signal; The sending module is used to send the control signal to the in-vehicle speaker, so that the in-vehicle speaker produces sound to offset the target noise signal.

7. The in-vehicle noise reduction device based on pedestrian warning sound according to claim 6, characterized in that: The extraction module includes: a transform unit, configured to perform fast Fourier transform on the original prompt sound signal and the external vehicle prompt sound signal respectively to obtain an original prompt audio domain signal and an external vehicle prompt audio domain signal; a comparing unit, configured to compare the amplitude of the original prompt audio domain signal with a preset amplitude threshold; a frequency band acquiring unit, configured to acquire a frequency band range in which the amplitude of the original prompt audio domain signal is greater than or equal to the preset amplitude threshold; a target acquisition unit, configured to acquire an external vehicle prompt audio domain signal falling within the frequency band as a frequency domain signal of the target noise; The post-processing unit is used to perform inverse fast Fourier transform and smoothing processing on the frequency domain signal of the target noise to obtain the target noise signal.

8. The in-vehicle noise reduction device based on pedestrian warning sound according to claim 7, characterized in that: The algorithm module includes: A matrix acquisition unit, used to obtain a transfer function matrix corresponding to the secondary sound channel in the vehicle; a filtered signal acquisition unit, configured to acquire a filtered signal according to the target noise signal and the transfer function matrix; a calculation unit, configured to obtain an in-vehicle prompt sound signal and a sound signal emitted by an in-vehicle speaker, and calculate an error signal between the in-vehicle prompt sound signal and the sound signal, wherein the in-vehicle prompt sound signal is a signal collected by an in-vehicle microphone after the original prompt sound signal is emitted by the prompt sound speaker; an updating unit, configured to update a weight coefficient of an adaptive filter according to the error signal and the filtered signal; A control signal acquisition unit is used to acquire a control signal of the in-vehicle speaker according to the updated weight coefficient and the filtered signal.

9. The in-vehicle noise reduction device based on pedestrian warning sound according to claim 8, characterized in that: When the adaptive control algorithm is a filtering-type time-domain FxLMS algorithm based on a transversal filter, the updating formula of the weight coefficient is: W(n)=W(n-1)-2μe(n)x f (n) Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, μ represents the iteration step size, e(n) represents the error signal, and x f (n) represents a filtered signal; or When the adaptive control algorithm is a filtering-type time-domain FxRLS algorithm based on a transversal filter, the updating formula of the weight coefficient is: W(n)=W(n-1)-g(n)e(n|n-1) Where W(n) represents the updated weight coefficient, W(n-1) represents the weight coefficient of the previous iteration, e(n|n-1) represents the error signal, g(n) represents the intermediate variable and x f (n) represents the filtered signal, λ represents the forgetting factor, and C(n) represents x f (n) and the inverse correlation matrix 10. A vehicle, characterized in that: It includes the in-vehicle noise reduction device based on pedestrian warning sound as described in any one of claims 6 to 9.

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