A method for implementing automobile sound effects based on a real performance venue model

Abstract

This invention provides a method for implementing car audio effects based on a real performance venue model. The method includes: S1: placing a sound source to be tested in the target performance venue, and setting up at least two sets of performance venue test points with the sound source to be tested as the origin, collecting the performance venue impulse response at each performance venue test point, and forming an original acoustic signal; S2: processing the original acoustic signal to obtain a standardized acoustic signal; S3: controlling the car audio system in the car cabin to play the test sound, setting up at least two sets of cabin test points in the car cabin, and collecting and obtaining the cabin impulse response; S4: extracting the performance venue impulse response and the cabin impulse response, calculating and obtaining the target impulse response; S5: calculating the target audio signal y(t) by performing a convolution operation between the standardized acoustic signal and the target impulse response; S6: adjusting the sound effect parameters of the target audio signal and playing it through the car audio system in the car cabin.

Description

Technical Field

[0001] This invention relates to the field of automotive audio technology and acoustic simulation, specifically to a method for realizing automotive sound effects based on a model constructed from acoustic test data of real performance venues such as concert halls and grand theaters. Background Technology

[0002] With the upgrading of the automotive industry and the increasing demands of consumers for driving and riding experiences, automotive audio systems need to evolve from simple playback to immersive and personalized listening experiences. Simulating high-quality acoustic scenarios has become an important research and development direction, with professional performance venues such as concert halls and grand theaters serving as core reference objects due to their excellent acoustic characteristics.

[0003] Current automotive audio simulation technologies typically employ virtual acoustic models, constructing models with preset parameters to simulate sound effects. However, virtual model parameters are often theoretical presets or empirical values, deviating significantly from real-world scenarios and resulting in insufficient realism in sound effects. Alternatively, existing technologies may use simplified convolution algorithms, collecting a small number of scene impulse responses and directly applying them to audio convolution. However, this approach has significant drawbacks: the measured data collection dimension is limited, accuracy is low, and it fails to cover the full range and frequency band differences of performance venues, making it unsuitable for adapting to the different seating requirements within the cabin. Furthermore, both of these approaches lack a mechanism for adapting acoustic parameters to the cabin environment, making them susceptible to interference from inherent cabin characteristics, leading to distortion.

[0004] Therefore, it is necessary to design a method for accurately collecting acoustic parameters of real performance venues and implementing sound effects that are adapted to the cabin, in order to enhance the realism of the sound effects and meet the personalized experience of users. Summary of the Invention

[0006] To address the above problems, this invention provides a method for implementing car sound effects based on a real performance venue model, the method comprising:

[0007] S1: Place the sound source to be tested in the target performance venue, and set up at least two sets of test points in the performance venue with the sound source to be tested as the origin. Collect the impulse response of the performance venue at each test point. And form the original acoustic signal. Where t is the time domain time of the signal;

[0008] S2: For the original acoustic signal The signal is processed to obtain a standardized acoustic signal. ;

[0009] S3: Control the car audio system in the vehicle cabin to play test sounds, set up at least two sets of cabin test points in the vehicle cabin, and collect and obtain the cabin impulse response. ;

[0010] S4: Extract the impulse response of the performance venue and cockpit impulse response Calculate and obtain the target impulse response ;

[0011] S5: By standardizing acoustic signals With target impulse response Perform convolution operations to calculate the target audio signal y(t);

[0012] S6: Adjust the target audio signal The sound parameters are set and played through the car's audio system.

[0013] As an optional technical solution, step S1 includes:

[0014] S11: Place the sound source to be tested in the center of the stage of the target performance venue, and control the sound source to play sounds of different frequency bands;

[0015] S12: Construct a coordinate system with the center of the stage as the origin. The test points of the performance venue include a first test point, which is arranged within a range of 1m to 2m along the extreme radius.

[0016] S13: Collect impulse responses of the performance venue at different frequency bands at each test point. And form the original acoustic signal. .

[0017] As an optional technical solution, in step S12, the test point further includes a second test point, which is located at the center seam axis of the audience area of ​​the performance venue, and the number of the second test point is 2 to 6.

[0018] As an optional technical solution, step S2 includes:

[0019] S21: For the original acoustic signal After denoising ;

[0020] S22: For the denoised acoustic signal The signal is then standardized to obtain the standardized acoustic signal. .

[0021] As an optional technical solution, step S21 includes:

[0022] For the original acoustic signal Perform wavelet decomposition.

[0023] ,

[0024] Where j is the wavelet decomposition level, J is the total number of wavelet decomposition levels, and k is the time scale index. For the set of integers, These are wavelet coefficients. For wavelet basis functions, The scaling factor. It is a scaling function;

[0025] For wavelet coefficients Soft thresholding is performed to obtain the denoised wavelet coefficients. ,

[0026] ,

[0027] in, , Let N be the noise standard deviation and N be the original acoustic signal. The total number of sampling points;

[0028] For the original acoustic signal Update to the denoised acoustic signal ,

[0029] .

[0030] As an optional technical solution, step S22 includes: processing the denoised acoustic signal Normalization is performed to obtain the standardized acoustic signal. ,

[0031] ,

[0032] in, The denoised acoustic signal The maximum value, The denoised acoustic signal The minimum value of , where a is the minimum value of the target normalized interval, and b is the maximum value of the target normalized interval.

[0033] As an optional technical solution, a=0, b=1; or, a=-1, b=1.

[0034] As an optional technical solution, the cockpit test points in step S3 include microphone test points and vibration test points. The microphone test points include driver's ear position and at least one passenger's ear position. The vibration test points include at least two seat points and at least one floor point.

[0035] As an optional technical solution, in step S4, "calculate and obtain the target impulse response" "include:

[0036] S41: Impulse response via entertainment venue and cockpit impulse response Calculate the deviation coefficient k.

[0037] ,

[0038] Where T is the pulse duration response time;

[0039] S42: Calculate the target impulse response ,

[0040] .

[0041] As an optional technical solution, step S5 includes:

[0042] ;

[0043] in, τ is the convolution operator, τ is the integral dummy variable, t-τ represents the time delay, and dτ represents a small time interval in the time domain.

[0044] Compared with existing technologies, this invention, by setting up at least two sets of test points in a real performance venue, and by allowing the sound source under test to play test sound sources of different frequency bands, can generate original acoustic signals from multiple test points. This accurately reflects the acoustic characteristics of the performance venue, laying the foundation for highly realistic sound effects. Furthermore, by deploying at least two sets of cabin test points inside the car and extracting the impulse response of the performance venue... and cockpit impulse response A cockpit adaptation mechanism is introduced to correct acoustic parameter deviations and construct an adaptive convolution kernel, thus avoiding distortion problems. The entire process is clear, easy for staff to operate, and adaptable to different cockpits and performance venues, showing extremely broad application prospects. Attached Figure Description

[0045] Figure 1 This is a flowchart illustrating the method for implementing car sound effects based on a real performance venue model. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0047] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0048] like Figure 1 As shown, a method for implementing car sound effects based on a real performance venue model is described, the method comprising:

[0049] S1: Place the sound source to be tested in the target performance venue, and set up at least two sets of test points in the performance venue with the sound source to be tested as the origin. Collect the impulse response of the performance venue at each test point. And form the original acoustic signal. ;

[0050] S2: For the original acoustic signal The signal is processed to obtain a standardized acoustic signal. ;

[0051] S3: Control the car audio system in the vehicle cabin to play test sounds, set up at least two sets of cabin test points in the vehicle cabin, and collect and obtain the cabin impulse response. ;

[0052] S4: Extract the impulse response of the performance venue and cockpit impulse response Calculate and obtain the target impulse response ;

[0053] S5: By standardizing acoustic signals With target impulse response Perform convolution operations to calculate the target audio signal y(t);

[0054] S6: Adjust the target audio signal The sound parameters are set and played through the car's audio system.

[0055] Therefore, in this invention, by setting up at least two sets of test points in a real performance venue, and by allowing the sound source under test to play test sound sources of different frequency bands, original acoustic signals from multiple test points can be generated. This accurately reflects the acoustic characteristics of the performance venue, laying the foundation for highly realistic sound effects. Furthermore, by deploying at least two sets of cabin test points inside the car and extracting the impulse response of the performance venue... and cockpit impulse response A cockpit adaptation mechanism is introduced, and an adaptive convolution kernel is constructed to avoid distortion problems. The entire process is clear, easy for staff to operate, and can be adapted to different cockpits and performance venues, showing extremely broad application prospects.

[0056] Where t is the time domain time of the signal.

[0057] Specifically, step S1 includes:

[0058] S11: Place the sound source to be tested in the center of the stage of the target performance venue, and control the sound source to play sounds of different frequency bands;

[0059] S12: Construct a coordinate system with the center of the stage as the origin. The test points of the performance venue include a first test point, which is arranged within a range of 1m to 2m along the extreme radius.

[0060] S13: Collect impulse responses of the performance venue at different frequency bands at each test point. And form the original acoustic signal. .

[0061] Specifically, in this embodiment, the sound source to be tested is a 20Hz-20kHz omnidirectional sound source device, and the first test points are arranged along a radius of 1.5m. Furthermore, the polar angle between any two adjacent first test points is the same; in this embodiment, the polar angle between any two adjacent first test points is 30°. Therefore, the first test points are evenly distributed in the performance venue.

[0062] Of course, the purpose of this invention can also be achieved if the first test point is arranged at other distances, or if the polar angle between two adjacent first test points is other angles.

[0063] Additionally, it should be noted that the step numbers in this solution are for ease of reading only and do not represent a fixed order of steps. For example, the step "controlling the sound source under test to play sounds of different frequency bands" in step S11 above can also be placed after step S12. As long as this technical solution can be implemented smoothly, any different embodiments resulting from changing the order of steps or within steps are within the protection scope of this technical solution.

[0064] In step S12, the test points further include second test points, which are located at the center seam axis of the audience area in the performance venue, and there are 2 to 6 of them. Furthermore, the second test points are generally located in the front and middle rows of the audience area.

[0065] The second test point is an additional addition used to collect acoustic indicators of the actual listening area in the performance venue.

[0066] Therefore, in this specific embodiment, the actual number of test points in the performance venue is 32, which can be used to collect acoustic parameters from different sound directions and frequency bands, and form raw acoustic signals. .

[0067] Step S2 includes:

[0068] S21: For the original acoustic signal After denoising ;

[0069] S22: For the denoised acoustic signal The signal is then standardized to obtain the standardized acoustic signal. .

[0070] Of course, due to the large number of test points in performance venues and the potential for significant noise in the collected audio, it is essential to process the original acoustic signals. Noise reduction is performed.

[0071] Specifically, step S21 includes:

[0072] For the original acoustic signal Perform wavelet decomposition.

[0073] ,

[0074] Where j is the wavelet decomposition level, J is the total number of wavelet decomposition levels, and k is the time scale index. For the set of integers, These are wavelet coefficients. For wavelet basis functions, The scaling factor. It is a scaling function;

[0075] For wavelet coefficients Soft thresholding is performed to obtain the denoised wavelet coefficients. ,

[0076] ,

[0077] in, , Let N be the noise standard deviation and N be the original acoustic signal. The total number of sampling points;

[0078] For the original acoustic signal Update to the denoised acoustic signal ,

[0079] .

[0080] Step "On the original acoustic signal" In wavelet decomposition, the number of decomposition levels, j, is typically 4-6. The effective frequency band of acoustic signals is usually between 20Hz and 20kHz. A decomposition of 4-6 levels allows for precise sub-banding of the signal, effectively separating noise without causing excessive computation or signal distortion due to too many levels. Wavelet basis functions... Used to extract high-frequency details of signals, such as ambient noise, current noise, and other clutter, it employs the dB4 / dB6 wavelets commonly used in acoustic scenarios. Suitable for processing non-stationary acoustic signals such as music signals, it can accurately separate noise from the effective signal while avoiding signal distortion. Scaling function The low-frequency component of the signal is preserved, retaining the original acoustic signal. The main information in the signal. Therefore, in this step, the original acoustic signal is first processed. It is divided into a noise-generating part and a main body part.

[0081] Then, for the wavelet coefficients That is, the noise component is subjected to soft threshold shrinkage to obtain the denoised wavelet coefficients. .

[0082] This embodiment uses a soft threshold formula, when... This indicates that the wavelet coefficients Larger, corresponding As a valid signal, it needs to be preserved; therefore, the wavelet coefficients are processed using the sign function. The sign is preserved, and the wavelet coefficient is... Subtract threshold The coefficients are shrunk to avoid abrupt distortion due to hard thresholds. And when... When, it indicates that the wavelet coefficients Smaller, corresponding If it's noise, set it to 0 to filter out the noise. Threshold The noise standard deviation Typically composed of wavelet coefficients The median estimate, The larger the value, the stronger the noise; the threshold value... The larger the volume, the stronger the noise reduction required; The smaller the value, the weaker the noise; the threshold value... The smaller the size, the less need there is for strong noise reduction; instead, more detail of the original sound signal needs to be preserved.

[0083] Then, the updated wavelet coefficients Substitute it into the original wavelet decomposition function to update it with the denoised acoustic signal. This is used for subsequent calculations. Therefore, the denoised acoustic signal... for:

[0084] .

[0085] This formula is largely the same as the one above, and the same characters have the same meaning, so it will not be repeated here.

[0086] Furthermore, to standardize the data volume and facilitate subsequent algorithm calculations, step S22 includes: processing the denoised acoustic signal... Normalization is performed to obtain the standardized acoustic signal. ,

[0087] ,

[0088] in, The denoised acoustic signal The maximum value, The denoised acoustic signal The minimum value of , where a is the minimum value of the target normalized interval, and b is the maximum value of the target normalized interval.

[0089] Specifically, The process is to denoise the acoustic signal Linear mapping to the range of 0 to 1, when hour, ;when hour, Then, This allows the data to be scaled up or shifted proportionally to the target range.

[0090] Specifically, in this embodiment, a=0, b=1; or a=-1, b=1. When a=0, b=1, the normalized acoustic signal is then... The range is [0, 1]. When a = -1 and b = 1, the normalized acoustic signal is then... The range is [-1, 1].

[0091] After normalizing the data, all data fall within the same range, allowing for fair processing of each acoustic feature and ensuring the accuracy of subsequent deviation coefficients k and target impulse responses. The calculations are accurate.

[0092] Without data normalization, the raw acoustic data exhibits a wide numerical range, easily leading to distortion in subsequent calculations and causing clipping, popping, and other distortion in the output audio. Normalization, on the other hand, standardizes the acoustic signal. The data range is controllable, the convolution operation values ​​are stable, the output target audio signal y(t) will not be distorted, and the listening experience is more natural.

[0093] Raw acoustic signals obtained from the detection of the target performance venue After processing, the acoustic data inside the car cabin also needs to be tested.

[0094] Specifically, the cockpit test points in step S3 include microphone test points and vibration test points. The microphone test points include the driver's ear position and at least one passenger's ear position. The vibration test points include at least two seat points and at least one floor point.

[0095] By testing the inherent acoustic parameters of different seats in a car cabin, such as cabin impulse response... By analyzing data such as inherent reverberation time, specific acoustic environment data within the car cabin can be obtained.

[0096] Specifically, when conducting tests inside a car cabin, there are specific requirements not only for the test points but also for the testing environment. First, the test must be conducted in a semi-anechoic chamber or rotary testing facility with ambient noise ≤30 dB(A). Here, A represents A-weighting, a frequency-weighted filtering method that simulates the characteristics of human hearing to correct instrument readings, making them closer to the actual subjective perception of the human ear. The corrected sound pressure level (in dB(A)) directly reflects the actual loudness heard by the human ear. Furthermore, the car's doors and windows must be closed, and the test must be conducted at room temperature. The test items include at least one of the following: for example, testing ambient noise during idling, constant speed, or acceleration; NVH (Noise, Vibration, Harshness) vibration noise; and spatial acoustics or panoramic sound testing.

[0097] By collecting acoustic data inside the car cabin, the cabin impulse response can be obtained. The cockpit's impulse response The results were obtained through on-site testing using professional acoustic testing equipment. Specific testing methods will not be detailed here, as there are corresponding national and industry standards.

[0098] Furthermore, in step S4, "calculate and obtain the target impulse response" "include:

[0099] S41: Impulse response via entertainment venue and cockpit impulse response Calculate the deviation coefficient k.

[0100] ,

[0101] Where T is the pulse duration response time;

[0102] S42: Calculate the target impulse response ,

[0103] .

[0104] Because there are significant acoustic differences between performance venues and car cabins, it is necessary to use impulse response analysis of performance venues. and cockpit impulse response Calculate the deviation coefficient k, and then calculate the impulse response of the performance venue. Corrected target impulse response to suit the cabin acoustic environment .

[0105] Specifically, performance venues are typically large spaces with long reverberation times, for example... The reverberation time is typically 0.8–2.0 s, with strong early reflections. Car cabins are usually small spaces with shorter reverberation times, for example... It is typically less than 0.5s and exhibits multimodal structural vibration and closed acoustic cavity effects.

[0106] In this solution, the aforementioned acoustic adaptation algorithm is adopted. This acoustic adaptation algorithm is a cross-scene acoustic transmission characteristic correction method. It quantifies the acoustic parameter deviation between the performance venue and the car cabin, and adjusts the impulse response of the performance venue. Corrected target impulse response to suit the cabin acoustic environment The kernel is then used as a convolution kernel for sound field reconstruction and sound quality transfer. Thus, in this embodiment, the aforementioned acoustic adaptation algorithm models the parameter deviation, corrects the impulse response, and then generates a convolution kernel to align the acoustic characteristics of the two types of scenes, ensuring the fidelity and naturalness of sound quality during cross-scene transfer.

[0107] Specifically, in step S41, the performance venue impulse response and cockpit impulse response Since the pulse duration response time T is the same for both environments, it can be used to calculate the deviation coefficient k in the formula. k represents the relative degree of difference between the two environments, with k=0 indicating complete consistency and k=1 indicating complete difference. The larger the value, the greater the difference.

[0108] Therefore, in step S42, if the value of k is small, it indicates that the environmental difference between the performance venue and the cabin is small, and the performance venue impulse response will be small. Corresponding weights A larger value for k indicates a greater weight, which preserves more of the sense of space in the performance venue. A smaller value for k indicates a greater difference between the performance venue and the cabin environment, resulting in a weaker cabin impulse response. A larger weight k value indicates a better fit for the in-vehicle acoustic environment.

[0109] Furthermore, in step S5, the target impulse response is... As a convolution kernel, and with the normalized acoustic signal Perform convolution operations to obtain the target audio signal Step S5 includes:

[0110] .

[0111] in, Representing the convolution operator, it is equivalent to converting the normalized acoustic signal... Input to In this acoustic system, the sound is processed by delaying, attenuating, and reflecting, and finally outputs y(t) for playback in the car cabin.

[0112] .

[0113] This formula is the expanded form of the convolution formula, where the parameters... t-τ is the integral dummy variable, representing each past moment when the sound is emitted, and t-τ represents the time delay, i.e. the time it takes for the sound to propagate. It represents a tiny time interval in the time domain.

[0114] Therefore, after processing by the above convolution algorithm, the music / voices played in the cabin possess the spatial feel of a performance venue, i.e., reverberation and early reflections, while also adapting to the acoustic characteristics of the car cabin. This improves the user's listening experience and enhances the driving and riding experience.

[0115] Finally, step S6, "adjusting the target audio signal", In the "Sound Effects Parameters" section, users can adjust the reverberation intensity and the proportion of early reflections within the range of 0-100%, thereby modifying the target convolution kernel. Impulse response of performance venues in calculation formula weight and cockpit impulse response The weight k can be adjusted in real time to modify the target convolution kernel. The energy distribution is adjusted to dynamically change the spatial immersion and adaptation characteristics of the output audio, meeting personalized listening needs. Of course, this adjustment can be performed by the user via the central control screen or voice control.

[0116] Therefore, in summary, the technical solution of the present invention firstly involves setting up at least two sets of test points in a real performance venue, and the sound source under test can play test sound sources of different frequency bands, thereby forming original acoustic signals from multiple test points. It accurately reflects the acoustic characteristics of performance venues, laying the foundation for highly realistic sound effects.

[0117] Furthermore, through the analysis of the original acoustic signal Denoising was performed using wavelet decomposition, followed by normalization to obtain a standardized acoustic signal. This eliminates computational bias caused by differences in signal magnitude under different test conditions, improves the numerical stability of subsequent difference calculations and convolution operations, and ensures the robustness of the acoustic adaptation algorithm.

[0118] Then, by setting up at least two sets of cabin test points inside the car cabin and extracting the impulse response of the performance venue. and cockpit impulse response A cockpit adaptation mechanism is introduced to correct acoustic parameter deviations and construct an adaptation convolution kernel. Using the deviation coefficient k as a dynamic weight, the impulse response of the performance venue is analyzed. Impulse response in the car cabin By performing weighted fusion, the system can automatically balance the spatial perception of the scene with the suitability of the in-vehicle acoustics, thus avoiding distortion problems.

[0119] Finally, the entire process is clear, easy for staff to operate, and adaptable to different cockpits and performance venues. During use, users can dynamically modify the convolution kernel in real time by changing the reverberation intensity and the proportion of early reflections. The energy distribution of the system can meet the personalized experience of users and improve the interactivity of the vehicle acoustic system, which has extremely broad application prospects.

[0120] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

[0121] The detailed descriptions listed above are merely specific descriptions of feasible implementations of the present invention and are not intended to limit the scope of protection of the present invention. All equivalent implementations or modifications made without departing from the spirit of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for implementing car sound effects based on a real performance venue model, characterized in that, The implementation method includes: S1: placing a to-be-tested sound source at a target performance venue, and arranging at least two groups of performance venue test points with the to-be-tested sound source as the origin, and collecting performance venue impulse responses at each performance venue test point , and forming an original acoustic signal , wherein t is a time domain moment of the signal. S2: processing the original acoustic signal and obtaining a standardized acoustic signal S3: processing the standardized acoustic signal and obtaining a standardized acoustic signal S2: processing the original acoustic signal and obtaining a standardized acoustic signal S3: processing the standardized S3: controlling a vehicle audio in a car cabin to play a test sound, arranging at least two groups of test points in the car cabin, collecting and obtaining a car cabin impulse response ; S4: Extracting the venue impulse response and the cockpit impulse response , calculating and obtaining the target impulse response ; S5: calculating the target audio signal y(t) by performing a convolution operation on the normalized acoustic signal with the target impulse response ​ S6: adjusting the sound effect parameter of the target audio signal and playing through the car audio in the car cabin.

2. The automobile sound effect realizing method according to claim 1, characterized by, Step S1 includes: S11: Place the sound source to be tested in the center of the stage of the target performance venue, and control the sound source to play sounds of different frequency bands; S12: Construct a coordinate system with the center of the stage as the origin. The test points of the performance venue include a first test point, which is arranged within a range of 1m to 2m along the extreme radius. S13: Collect the impulse response of the performance venue under different frequency bands at each test point of the performance venue , and form the original acoustic signal .

3. The automobile sound effect realizing method according to claim 1, characterized by, In step S12, the test point further includes a second test point, which is located at the center seam axis of the audience area of ​​the performance venue, and the number of the second test point is 2 to 6.

4. The method for implementing car sound effects according to claim 1, characterized in that, Step S2 includes: S21: For the original acoustic signal After denoising ; S22: For the denoised acoustic signal The signal is then standardized to obtain the standardized acoustic signal. .

5. The method for implementing car sound effects according to claim 4, characterized in that, Step S21 includes: For the original acoustic signal Perform wavelet decomposition. ， Where j is the wavelet decomposition level, J is the total number of wavelet decomposition levels, and k is the time scale index. For the set of integers, These are wavelet coefficients. For wavelet basis functions, The scaling factor. It is a scaling function; For wavelet coefficients Soft thresholding is performed to obtain the denoised wavelet coefficients. , ， in, , Let N be the noise standard deviation and N be the original acoustic signal. The total number of sampling points; For the original acoustic signal Update to the denoised acoustic signal , 。 6. The method for implementing car sound effects according to claim 4, characterized in that, Step S22 includes: processing the denoised acoustic signal Normalization is performed to obtain the standardized acoustic signal. , ， in, The denoised acoustic signal The maximum value, The denoised acoustic signal The minimum value of , where a is the minimum value of the target normalized interval, and b is the maximum value of the target normalized interval.

7. The method for achieving car sound effects according to claim 6, characterized in that, a=0, b=1; or a=-1, b=1.

8. The method for implementing car sound effects according to claim 1, characterized in that, The cockpit test points in step S3 include microphone test points and vibration test points. The microphone test points include the driver's ear position and at least one passenger's ear position. The vibration test points include at least two seat points and at least one floor point.

9. The method for achieving car sound effects according to claim 1, characterized in that, In step S4, "calculate and obtain the target impulse response" "include: S41: Impulse response via entertainment venue and cockpit impulse response Calculate the deviation coefficient k. ， Where T is the pulse duration response time; S42: Calculate the target impulse response , 。 10. The method for achieving car sound effects according to claim 1, characterized in that, Step S5 includes: ； in, τ is the convolution operator, τ is the integral dummy variable, t-τ represents the time delay, and dτ represents a small time interval in the time domain.

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