Automobile dsp power amplifier sound effect intelligent processing system

Abstract

The application discloses a car DSP power amplifier sound effect intelligent processing system and particularly relates to the field of vehicle audio system optimization, which is used for solving the problems of sound effect consistency and intelligent adaptation under a dynamic sound field, and is characterized in that acoustic data are collected in real time through a microphone array, a three-dimensional acoustic geometric model is constructed by combining ray tracing and image source method, and sound wave propagation paths and dynamic changes are accurately captured; through frequency band division of low-frequency, medium-frequency and high-frequency signals, the spectral distribution difference and gain fluctuation center of each seat are evaluated, a sound field consistency adjustment coefficient is generated, and the design and optimization of a directional beam forming filter are guided, the amplitudes and phases of each sound channel are adjusted, a directional sound beam is formed, and noise interference is suppressed; and the car DSP power amplifier sound effect intelligent processing system can further dynamically adapt to changes in the acoustic environment in the car, improve sound effect balance and high fidelity, and enhance the auditory experience and satisfaction of passengers.

Description

Technical Field

[0001] This invention relates to the field of vehicle audio system optimization, and more specifically, to an intelligent audio processing system for automotive DSP amplifiers. Background Technology

[0002] In-vehicle sound field design directly impacts a car's audio performance and is a crucial factor in enhancing the driving and riding experience. However, the in-vehicle space, as a constrained acoustic environment with a complex geometry, is dynamically influenced by various factors, including seat layout, the sound absorption and reflection properties of interior materials, and the number and location of passengers. Dynamic conditions within the vehicle, such as adjustments to seat positions, changes in passenger distribution, or alterations in luggage loading, can change sound propagation paths and reflection patterns, leading to an uneven sound field distribution. In this dynamic environment, traditional sound design techniques typically rely on static acoustic models. These models assume that sound field characteristics remain stable under fixed conditions, making it difficult to handle real-time changes in sound field characteristics in actual scenarios.

[0003] Existing DSP audio adjustment technologies have significant limitations in adapting to the complex dynamic sound fields within vehicles. First, traditional methods struggle to perceive real-time changes in sound field characteristics caused by seat adjustments or passenger movement, resulting in insufficient sound compensation for different locations. For example, the driver's area may experience low-frequency enhancement, while the rear passenger area may lack high frequencies, leading to inconsistencies in sound quality across different locations. Second, current technologies lack intelligent adjustment capabilities for dynamic changes in the in-vehicle sound field, failing to provide precise compensation strategies based on real-time sound field distribution. This results in significant differences in the driver's and passengers' perception of the same sound, a problem that significantly diminishes the user's audio experience, especially in high-end audio systems. Therefore, developing an intelligent audio adjustment technology capable of real-time analysis of dynamic sound field distribution, precise generation of adjustment parameters, and rapid response to changes in in-vehicle sound field characteristics is a crucial issue that urgently needs to be addressed. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an intelligent audio processing system for automotive DSP amplifiers. This system utilizes a microphone array to collect acoustic data in real time and combines it with a three-dimensional acoustic geometric model constructed using ray tracing and image source methods. This allows for precise capture of the sound wave propagation path and its dynamic changes in space. Based on this, by dividing the low-frequency, mid-frequency, and high-frequency audio signals into frequency bands and evaluating the spectral distribution differences and gain fluctuation center positions of each seat in different frequency bands, a sound field consistency adjustment coefficient is generated by measuring the distribution dispersion and gain offset of each frequency band. This coefficient guides the design and optimization of directional beamforming filters. Based on the sound field consistency adjustment coefficient, the system identifies the positions of the main audio target sources within the vehicle, designs and adjusts the amplitude and phase of each channel to form directional sound beams pointing towards the target sources, while effectively suppressing noise interference from non-target directions. Furthermore, by dynamically adapting to changes in the in-vehicle acoustic environment, the system significantly improves the balance and high fidelity of the in-vehicle sound effects, enhancing the passenger's auditory experience and satisfaction, thereby solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] The automotive DSP power amplifier audio effect intelligent processing system includes: a data acquisition module, a 3D modeling module, a frequency band analysis module, and a beam optimization module;

[0007] Data acquisition module: Uses a microphone array and acoustic sensors to transmit the acquired data to the central processing unit;

[0008] 3D Modeling Module: The central processing unit uses ray tracing and image source methods to construct a 3D acoustic geometry model of the vehicle interior based on data collected from multiple points, and calculates the reflection path and propagation delay of sound waves on various surfaces inside the vehicle.

[0009] Frequency band analysis module: Divides the audio signal into low frequency, mid frequency and high frequency according to the predetermined frequency band. Based on the difference in spectral distribution and the position of the gain fluctuation center of each seat in the three-dimensional acoustic geometry model, it measures the distribution dispersion and gain offset of each frequency band, generates sound field consistency adjustment coefficients to evaluate the frequency band gain adjustment effect, and passes the sound field consistency adjustment coefficients to beam optimization.

[0010] Beam Optimization Module: Based on the sound field consistency adjustment coefficient results, the module identifies the location of the main audio target sound source in the vehicle, designs a directional beamforming filter, and forms a directional sound beam pointing towards the target sound source by adjusting the amplitude and phase of each channel, while suppressing noise interference from non-target directions.

[0011] In a preferred embodiment, the 3D modeling module includes the following:

[0012] First, categorize all collected data points according to their spatial location P.i =(x i ,y i ,z i A unified spatial coordinate calibration was performed, and the in-vehicle space framework was constructed using a three-dimensional Cartesian coordinate system. Subsequently, the following specific methods were applied to complete the construction of the three-dimensional acoustic geometry model and the calculation of the reflection path:

[0013] Based on the vehicle interior structural design parameters, a three-dimensional geometric mesh model G containing all acoustic surfaces was created. j , where j represents the spatial index of each surface; each surface is labeled with specific attribute parameters A. j =(r j ,c j ,θ j ), where r j c is the reflection coefficient. j Let θ be the absorption coefficient. j The direction angle of the surface normal vector;

[0014] From each sound source point S k A sound wave path ray is emitted onto the mesh surface, and the interaction between the ray and each surface mesh G is calculated. j The intersection point Q k,j and the angle of incidence φ k,j The formula for calculating the intersection point is: Q k,j =S k +t·d; where d is the ray direction vector and t is the path parameter, solved through geometric constraint equations; record the path length L of each ray. k,j =||S k -Q k,j ||;and propagation time T k,j =L k,j / υ, where υ is the speed of sound;

[0015] Based on the intersection point Q of the first reflection k,j Generate a virtual mirror point M corresponding to the sound source point. k,j Calculate the multiple reflection paths from the mirror point to other surfaces; complete the multiple reflection paths R using a recursive algorithm. m,n The length and propagation delay are calculated; the path recursive formula is: And cumulative transmission time

[0016] Phase difference calculation is performed on the superimposed signals of all rays and reflection paths, based on the propagation time T. k,j And frequency f, through the phase formula: Δφ k,j =2πf·T k,j ; Calculate the phase shift of each path, and accumulate them to obtain the phase superposition effect of the entire sound field;

[0017] Based on the combined results, a three-dimensional acoustic geometric model M is constructed, which includes information on path length, propagation time, number of reflections, and phase change. acoustic And all its parameters are recorded in matrix form.

[0018] In a preferred embodiment, the frequency band analysis module includes the following:

[0019] Based on the original in-vehicle audio signal, and according to the preset boundary frequencies, the audio signal is divided into three major ranges: low frequency (LF), mid frequency (MF), and high frequency (HF).

[0020] For each large interval, divide it into several sub-bands to characterize the energy distribution within each frequency band; let the BAND b,u Let u represent the u-th subband in frequency band b, where b∈{LF,MF,HF} and u is the subband index;

[0021] By combining a three-dimensional acoustic geometry model, the propagation attenuation coefficient and material absorption characteristics of each seat h in each subband are corrected to obtain the corrected subband energy E. h,b,u ;

[0022] To measure the dispersion of energy distribution at each seat across different frequency bands, a multi-layered threshold-based coverage calculation method is first defined:

[0023] First, a threshold sequence {ν1,ν2,…,ν} is set for each seat and sub-band. m}, where ν K Increasing and following a geometric or logarithmic distribution to capture changes in energy distribution from low to high;

[0024] For the threshold ν K With the corrected subband energy E h,b,u Define a subband coverage determination function: ;

[0025] Then, the coverage determination results of all sub-bands under the same frequency band are summed to obtain the position h at the threshold ν. K Subband coverage and:

[0026] The distribution dispersion FDI was obtained using a multi-level fractal measure method. h,b : in, It is a non-linear exponent used to amplify or reduce the difference in subband coverage as the threshold increases.

[0027] In a preferred embodiment, the frequency band analysis module further includes the following:

[0028] To evaluate the gain offset, first define a relative gain scalar: Among them, G h,b Set the current gain for seat h in frequency band b. For a predefined ideal reference value, tanh(·) is used to map the gain offset to the interval [0,1);

[0029] Subsequently, to quantify the connectivity of the corresponding offsets between each subband, the gain offset connectivity is calculated: GDC h,b =exp(∑log(1+Z) h,b )).

[0030] In a preferred embodiment, the frequency band analysis module further includes the following:

[0031] By fusing the distribution dispersion and gain offset connectivity in frequency band b, the corresponding seat-level sound field deviation index is obtained: Π h,b =(FDI) h,b ) κ1 +ln(1+GDC h,b ); where κ1 is a nonlinear adjustment coefficient used to control the contribution of distribution dispersion to this deviation index; finally, to comprehensively evaluate the sound field consistency of the seat in the low, mid, and high frequency bands, a sound field consistency adjustment coefficient SCA is defined. h SCA h =∑ b∈{LF,MF,HF} Π h,b Arrange the calculation results of all seat sound field consistency adjustment coefficients according to seat index h to form a one-dimensional sequence {SCA1,SCA2,…}.

[0032] In a preferred embodiment, the propagation attenuation coefficient and material absorption characteristics of each seat in each sub-band are corrected by the following method: First, based on the total length of the sound wave along the propagation path and the reflection angle of each path segment, the attenuation factor along the path is calculated, and the total propagation attenuation coefficient is obtained by combining all paths; Second, the absorption coefficient of each reflecting surface recorded in the three-dimensional model is queried, and the energy loss at each reflection point in the path is cumulatively calculated; Finally, the initial energy value of each seat in the sub-band is multiplied sequentially by the propagation attenuation coefficient and the absorption loss correction coefficient to obtain the corrected sub-band energy, which is used to describe the frequency band energy distribution under real propagation conditions.

[0033] In a preferred embodiment, the beam optimization module includes the following:

[0034] First, based on the sequence {SCA1,SCA2,…}, select the target seat index h that exceeds the consistency threshold and has the largest value. crit This is marked as the priority target seat; in the three-dimensional acoustic geometry model, the spatial coordinates of the target seat are denoted as... Let the coordinates of the car's interior speaker be C. spk Define target direction The target direction indicator points from the center of the speaker towards the target seat.

[0035] To achieve directional sound beams, the phases of the signals from each channel under different time delays are superimposed and controlled; assuming the array contains N independent channels, their positions in the three-dimensional acoustic geometry model are A... n n = 1, 2, ..., N;

[0036] Define phase shift function Used to perform phase correction on the nth channel in the frequency domain, so that it is in the target direction. Generate coherent superposition and minimize phase cancellation in other directions; the constraint is denoted as... Where <·,·> denotes the vector dot product, O represents the set of interference directions that are perpendicular or opposite to the target direction, and Δ n This represents the comprehensive correction amount for the nth channel in terms of phase dimension and minute coordinate offset; this constraint ensures that the beam energy in the target direction is higher than that in other interference directions.

[0037] In a preferred embodiment, the beam optimization module further includes the following:

[0038] In addition to phase control, the amplitude of each channel output is allocated; an amplitude function is defined. Where ζ is the amplification factor and τ represents the discrete-time index; It is the amplitude adjustment factor;

[0039] Meanwhile, in order to suppress sidelobe energy, a sidelobe domain is defined within a certain angle range from the target direction vector. If an amplitude superposition trend higher than the standard is detected in the sidelobe domain region, the amplitude function of the corresponding channel is reduced.

[0040] In the time domain, the direction and amplitude of the main lobe are not constant. Dynamic beamwidth correction is performed to adapt to changes in the target position caused by passenger movement or seat angle changes.

[0041] The instantaneous value of the main lobe beamwidth is the sum of the initially set basic beamwidth and the correction amount that changes over time; if a displacement of the target position is detected, the beamwidth range is automatically expanded or contracted, and the phase shift function is updated accordingly.

[0042] The dynamic beamwidth correction process monitors the energy distribution of the directivity pattern output by the array in the high-frequency and mid-frequency bands. If the main lobe leaves the target area, the instantaneous value of the main lobe beamwidth and the amplification coefficient in the amplitude function are adjusted in real time, and the phase shift function is finely adjusted in real time to redirect the main lobe peak.

[0043] Finally, a directional beamforming filter is defined and synthesized for each frequency band. For frequency band b∈{LF,MF,HF}, a separate set of filter coefficients is generated, and the results are combined to obtain a multi-band directional beamforming filter. The multi-channel signal output by the multi-band directional beamforming filter forms a phase superposition and amplitude gain enhancement effect in the target direction, and exhibits phase cancellation and amplitude attenuation in the non-target direction, thereby improving the sound field consistency and listening performance of key seats.

[0044] The technical effects and advantages of the automotive DSP power amplifier audio effect intelligent processing system of this invention are as follows:

[0045] This invention utilizes a microphone array to acquire acoustic data in real time and combines it with a three-dimensional acoustic geometric model constructed using ray tracing and image source methods. This model can accurately capture the sound wave propagation path and its dynamic changes in space. Based on this, by dividing the low-frequency, mid-frequency, and high-frequency audio signals into frequency bands and evaluating the differences in spectral distribution and the location of gain fluctuation centers at each seat in different frequency bands, a sound field consistency adjustment coefficient is generated by measuring the distribution dispersion and gain offset of each frequency band. This coefficient guides the design and optimization of directional beamforming filters. Based on the sound field consistency adjustment coefficient, the location of the main audio target sources in the vehicle is identified, and the amplitude and phase of each channel are designed and adjusted to form a directional sound beam pointing towards the target source, while effectively suppressing noise interference from non-target directions. Furthermore, by dynamically adapting to changes in the in-vehicle acoustic environment, the balance and high fidelity of the in-vehicle sound effects are significantly improved, enhancing the passenger's auditory experience and satisfaction. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the intelligent audio processing system for automotive DSP amplifiers of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1: Figure 1 The present invention provides an intelligent audio processing system for automotive DSP amplifiers, comprising:

[0049] Data acquisition module: Uses a microphone array and acoustic sensors to transmit the acquired data to the central processing unit;

[0050] 3D Modeling Module: The central processing unit uses ray tracing and image source methods to construct a 3D acoustic geometry model of the vehicle interior based on data collected from multiple points, and calculates the reflection path and propagation delay of sound waves on various surfaces inside the vehicle.

[0051] Frequency band analysis module: Divides the audio signal into low frequency, mid frequency and high frequency according to the predetermined frequency band. Based on the difference in spectral distribution and the position of the gain fluctuation center of each seat in the three-dimensional acoustic geometry model, it measures the distribution dispersion and gain offset of each frequency band, generates sound field consistency adjustment coefficients to evaluate the frequency band gain adjustment effect, and passes the sound field consistency adjustment coefficients to beam optimization.

[0052] Beam Optimization Module: Based on the sound field consistency adjustment coefficient results, the module identifies the location of the main audio target sound source in the vehicle, designs a directional beamforming filter, and forms a directional sound beam pointing towards the target sound source by adjusting the amplitude and phase of each channel, while suppressing noise interference from non-target directions.

[0053] Optimizing in-vehicle audio relies on accurate sound field data acquisition, and the completeness and real-time nature of this data directly determine the accuracy of subsequent sound field modeling and optimization. In the complex acoustic environment of a vehicle, the sound pressure level, spectral characteristics, and phase information of different seating areas exhibit significant dynamic differences, and are significantly affected by vehicle speed, external ambient noise, and the vehicle's layout. To support the construction of a three-dimensional sound field model, targeted real-time acquisition technology is needed to ensure the acquisition and transmission of high-precision data.

[0054] The data acquisition module includes the following:

[0055] By deploying microphone arrays and acoustic sensors in key locations such as the front, middle, and rear seats and doors of the vehicle, a multi-point distributed acquisition network covering the main acoustic areas of the entire vehicle is formed. Each acquisition point samples synchronously at equal intervals, and a unified clock reference is used to achieve time synchronization of the acoustic signals at multiple points through a timestamp calibration method to avoid data misalignment.

[0056] Each microphone and sensor unit features a wideband design, capturing acoustic signals from low to high frequencies, and utilizes a built-in filtering module to eliminate external interference noise (such as wind and tire noise). Data is digitized via a high-precision analog-to-digital converter (ADC) at a preset sampling rate of 192kHz or higher, ensuring complete recording of spectral characteristics. To improve the real-time performance and integrity of data transmission, a high-speed communication bus (such as CAN or Ethernet) is used to transmit the acquired data to the central processing unit.

[0057] The real-time acquired acoustic data includes sound pressure level (to characterize sound field intensity), spectral characteristics (to describe frequency distribution), and phase information (to calculate sound wave propagation paths and interference). During transmission, the data stream is integrated through a distributed caching mechanism to support subsequent modeling calculations.

[0058] After the above processing is completed, the acquired multi-point acoustic data is stored in the central processing unit in a high-precision and high-time-response format. This data provides the necessary frequency, intensity, and phase information for the construction of the three-dimensional sound field model in the subsequent three-dimensional modeling module. In particular, the dynamic changes in the acoustic characteristics of each region will be directly used as input parameters for the calculation of reflection paths and propagation delays in the three-dimensional geometric model.

[0059] By acquiring high-precision and comprehensive acoustic data, the accuracy of subsequent 3D sound field modeling is ensured, thereby providing precise raw data support for optimizing in-vehicle sound effects.

[0060] In the data acquisition module, sound pressure levels, spectral characteristics, and phase information for various areas inside the vehicle have been collected. The comprehensiveness and real-time nature of this data provide a foundation for constructing an accurate three-dimensional sound field geometric model. The goal of this step is to utilize this acoustic data to establish a geometric model of the in-vehicle acoustic environment by combining ray tracing and image source methods, and further calculate the propagation path, delay, reflection, and interference characteristics of sound waves, providing accurate geometric and physical basis for subsequent frequency band analysis and dynamic adjustments.

[0061] The 3D modeling module includes the following:

[0062] After receiving the sound pressure level, spectral characteristics, and phase information transmitted from the data acquisition module, the central processing unit first sorts all the data from the acquisition points according to their spatial locations P. i =(x i ,y i ,z i A unified spatial coordinate system was established, and the interior space framework was constructed using a three-dimensional Cartesian coordinate system. Subsequently, the following specific methods were applied to construct the three-dimensional acoustic geometry model and calculate the reflection path:

[0063] 1. Initial geometric framework construction:

[0064] Based on the vehicle interior structural design parameters (such as the dimensions and material properties of doors, seats, and roof), create a three-dimensional geometric mesh model G that includes all acoustic surfaces. j Where j represents the spatial index of each surface. Each surface is labeled with specific attribute parameters A. j =(r j ,c j ,θ j ), where r j c is the reflection coefficient. jLet θ be the absorption coefficient. j The direction angle of the surface normal vector.

[0065] 2. Ray Tracing Path Calculation:

[0066] From each sound source point S k (e.g., the location of an acoustic wave) emits a sound wave path ray onto the mesh surface, and calculates the relationship between the ray and each surface mesh G. j The intersection point Q k,j and the angle of incidence φ k,j The formula for calculating the intersection point is: Q k,j =S k +t·d; where d is the ray direction vector and t is the path parameter, solved by geometric constraint equations.

[0067] Record the path length L of each ray k,j =||S k -Q k,j ||;and propagation time T k,j =L k,j / υ, where υ is the speed of sound.

[0068] 3. Multiple reflections supplemented by the image source method:

[0069] Based on the intersection point Q of the first reflection k,j Generate a virtual mirror point M corresponding to the sound source point. k,j Calculate the multiple reflection paths from the mirror point to other surfaces. The multiple reflection paths R are calculated using a recursive algorithm. m,n The length and propagation delay are calculated. The path recursion formula is: And cumulative transmission time

[0070] 4. Interference and Phase Difference Calculation:

[0071] Phase difference calculation is performed on the superimposed signals of all rays and reflection paths, based on the propagation time T. k,j And frequency f, through the phase formula: Δφ k,j =2πf·T k,j ; Calculate the phase shift of each path, and accumulate them to obtain the phase superposition effect of the entire sound field.

[0072] 5. Output of the 3D acoustic geometry model:

[0073] Based on the above results, a three-dimensional acoustic geometric model M is constructed, which includes information such as path length, propagation time, number of reflections, and phase change. acoustic And all its parameters are recorded in matrix form: M acoustic ={L k,j ,T k,j ,R m,n ,Δφk,j A j This model is used to comprehensively reflect the characteristics of the in-vehicle sound field, providing input for the next step of spectral distribution difference and gain adjustment.

[0074] Through the above processing, the central processing unit successfully constructed a three-dimensional acoustic geometry model of the vehicle interior, accurately calculating the reflection paths and propagation delays of sound waves on various surfaces within the vehicle. This detailed sound field distribution information will serve as the basis for spectral distribution differences and gain adjustments in the frequency band analysis module, ensuring that dynamic adjustments to the frequency band gain are based on precise sound field characteristics, thereby achieving consistency in frequency response at each seat within the vehicle.

[0075] In the data acquisition module, the system collects sound pressure level, spectral characteristics, and phase information for each seat using a microphone array and acoustic sensors. This information is then transmitted to the central processing unit after high-sampling-rate analog-to-digital conversion. In the 3D modeling module, the central processing unit constructs a 3D acoustic geometry model of the vehicle interior based on in-vehicle spatial geometry data, combined with ray tracing and image source methods. This model meticulously records the sound wave propagation and reflection characteristics of each seat. To achieve differentiated analysis and dynamic gain optimization for different seats in the low, mid, and high frequency bands, this step utilizes the data from the 3D acoustic geometry model to segment the audio signal and measure its distribution characteristics. Ultimately, this yields a sound field consistency adjustment coefficient that can be used to evaluate and guide frequency band gain adjustments.

[0076] The frequency band analysis module includes the following:

[0077] 1. Frequency band allocation and sub-band preprocessing:

[0078] Based on the original in-vehicle audio signal collected by the data acquisition module, the audio signal is divided into three major ranges: low frequency (LF), mid frequency (MF), and high frequency (HF) according to the preset boundary frequencies.

[0079] For each large interval, further subdivisions are made into several sub-bands to more precisely characterize the energy distribution within each frequency band. This allows for a more detailed depiction of the energy distribution within the band. b,u Let u represent the u-th subband in frequency band b, where b∈{LF,MF,HF} and u is the subband index.

[0080] Based on the 3D acoustic geometry model obtained from the 3D modeling module, the propagation attenuation coefficient and material absorption characteristics of each seat h in each subband are corrected to obtain the corrected subband energy E. h,b,u At this time, E h,b,u Multiple reflections of sound waves on the corresponding sub-bands, path length, incident angle, and surface properties have been comprehensively considered.

[0081] The propagation attenuation coefficient and material absorption characteristics of each seat in each sub-band are corrected using the following method: First, based on the total length of the sound wave along the propagation path and the reflection angle of each path segment, the attenuation factor along the path is calculated, and the total propagation attenuation coefficient is obtained by combining all paths; Second, the absorption coefficients of each reflecting surface recorded in the 3D model are queried, and the energy loss at each reflection point in the path is cumulatively calculated; Finally, the initial energy value of each seat in the sub-band is multiplied sequentially by the propagation attenuation coefficient and the absorption loss correction coefficient to obtain the corrected sub-band energy, which is used to describe the frequency band energy distribution under real propagation conditions.

[0082] 2. Subband coverage calculation with multi-level threshold progression:

[0083] To measure the degree of energy distribution dispersion of each seat in different frequency bands, a multi-layer threshold progressive coverage calculation method needs to be defined first.

[0084] First, a threshold sequence {ν1,ν2,…,ν} is set for each seat and sub-band. m}, where ν K Increasing and following a geometric or logarithmic distribution to capture changes in energy distribution from low to high.

[0085] For the threshold ν K With the corrected subband energy E h,b,u Define a subband coverage determination function: ;

[0086] This function determines whether the energy exceeds a certain threshold. Then, it sums the coverage determination results of all sub-bands within the same frequency band to obtain the position h at the threshold ν. K Subband coverage and: Among them, the sub-band coverage and the decreasing trend with increasing threshold can reflect the distribution pattern of energy from low to high in this frequency band, laying the foundation for subsequent quantification of the degree of distribution dispersion.

[0087] 3. Multilevel fractal measure of distribution dispersion:

[0088] To characterize the energy dispersion characteristics of seats across different frequency bands, a multi-level fractal measure method was used to obtain the distribution dispersion degree (FDI). h,b : in, This is a nonlinear exponent used to amplify or reduce the difference in subband coverage as the threshold increases; the larger the distribution dispersion value, the more layered and uneven the energy distribution of seat h in frequency band b. Since subband coverage depends on the energy threshold sequence and subband coverage conditions, this fractal measure can characterize dispersion from multiple angles at different energy levels.

[0089] 4. Nonlinear coupling analysis of gain offset connectivity:

[0090] In addition to dispersion, the gain offset situation also needs to be evaluated, that is, whether the gain allocation of seat h in frequency band b has been improperly offset.

[0091] First, define a relative scalar of gain: Among them, G h,b Set the current gain for seat h in frequency band b. For a predefined ideal reference value (which can be set according to the target acoustic environment or the average gain level in the vehicle in the 3D modeling module), tanh(·) is used to map the gain offset to the interval [0,1).

[0092] Subsequently, to further quantify the connectivity of the corresponding offsets between each subband, the gain offset connectivity is calculated: GDC h,b =exp(∑log(1+Z) h,b The purpose of using a combination of logarithms and exponentials is to avoid linear summation or simple multiplication from being too smooth. When there is a large offset between subbands, this value will increase significantly, thus highlighting the cumulative effect of improper gain.

[0093] 5. Calculation of sound field consistency adjustment coefficient:

[0094] By fusing the distribution dispersion and gain offset connectivity in frequency band b, the corresponding seat-level sound field deviation index is obtained: Π h,b =(FDI) h,b ) κ1 +ln(1+GDC h,b ); where κ1 is a nonlinear adjustment coefficient used to control the contribution of distribution dispersion to this deviation index; and ln(1+GDC) h,b This ensures that the effect of the gain offset is amplified rapidly when it is too high.

[0095] Finally, to comprehensively evaluate the acoustic field consistency of seats across low, mid, and high frequency bands, an acoustic field consistency adjustment factor (SCA) is defined. h SCA h =∑ b∈{LF,MF,HF} Π h,b When SCA h A higher value indicates that seat h exhibits high energy dispersion and severe gain offset across multiple frequency bands, requiring further optimization in subsequent steps; a lower value indicates that the seat is already in a relatively balanced and reasonable sound field state.

[0096] The calculation results of all seat sound field consistency adjustment coefficients are arranged according to seat index h to form a one-dimensional sequence {SCA1,SCA2,…}, and then passed to the beam optimization module.

[0097] By meticulously calculating the gain offset and energy distribution for all seats, this step successfully established the sound field consistency adjustment coefficients. This result will serve as the basis for the next step of priority optimization, guiding directional beamforming and dynamic gain adjustment to ensure a more balanced and efficient sound field distribution within the vehicle.

[0098] In the frequency band analysis module, after frequency band division, dispersion analysis, and gain offset measurement, a sound field consistency adjustment coefficient is obtained for each seat. This coefficient characterizes the overall deviation of each seat in the low, mid, and high frequency bands. Based on the numerical distribution of this coefficient, the system can identify which seats have significant sound field imbalance problems. Building upon this result, the current step involves integrating a three-dimensional acoustic geometry model (from the three-dimensional modeling module) to design and implement directional beamforming filters for the seats with the most significant imbalance or those requiring optimization. This enhances the sound effect in the target direction and suppresses noise from non-target directions.

[0099] The beam optimization module includes the following:

[0100] 1. Determining the target seat and direction vector:

[0101] First, based on the sequence {SCA1,SCA2,…} generated by the frequency band analysis module, the target seat index h with the largest value exceeding the consistency threshold is selected. crit Mark it as the priority target seat for optimization.

[0102] In the three-dimensional acoustic geometry model, let the spatial coordinates of the target seat be R. hcrit Let C be the coordinates of the center of the in-vehicle speaker (or array). spk Define the target direction D. hcrit =R hcrit -C spk The target direction indicates the direction from the center of the speaker to the target seat; in subsequent filter design, the directional gain and phase allocation need to be determined based on this direction vector.

[0103] 2. Phase shift and multi-angle interference suppression:

[0104] To achieve directional sound beams, the phases of the signals from each channel under different time delays need to be superimposed and controlled. Assume the array contains N independent channels, and their positions in the three-dimensional acoustic geometry model are A... n n = 1, 2, ..., N.

[0105] Define phase shift function Used to perform phase correction on the nth channel in the frequency domain, so that it is in the target direction. The goal is to generate coherent superposition while minimizing phase cancellation in other directions. This constraint can be denoted as... where <·,·> represents the vector dot product, O represents the set of interference directions perpendicular or contrary to the target direction, and Δ n represents the comprehensive correction amount for the nth channel in the phase dimension and the minute coordinate offset. This constraint aims to ensure that the beam energy in the target direction is higher than that in other interference directions.

[0106] 3. Amplitude distribution and sidelobe constraint:

[0107] In addition to phase control, non-linear distribution of the amplitude of each channel output is also required. Define the amplitude function where ζ is the amplification factor and τ represents the discrete time index. is the amplitude adjustment factor, which can be calculated by the following formula: where represents the cosine value of the angle between the position vector of the nth channel and the target direction vector, with a range of [-1, 1]; is the angle between the channel position vector and the target direction vector, calculated from the three-dimensional acoustic geometry model; κ1 is the intensity coefficient of amplitude adjustment, used to control the influence intensity of the sound field consistency adjustment coefficient on the amplitude factor.

[0108] Meanwhile, to suppress the sidelobe energy, a sidelobe domain S side is defined within a certain angle range from the target direction vector. If it is detected that there is a trend of amplitude superposition higher than the standard in the sidelobe domain area, the amplitude function of the corresponding channel is dynamically reduced to ensure that the main lobe energy is concentrated while the sidelobes are suppressed.

[0109] 4. Dynamic beamwidth correction and phase fine-tuning:

[0110] In the time domain dimension, the main lobe direction and amplitude are not constant. To adapt to the target position changes caused by the movement of passengers in the vehicle or the change of the seat angle, dynamic beamwidth correction is required.

[0111] Let Θ(τ) represent the instantaneous value of the main lobe beamwidth, which is the sum of the initial set basic beamwidth and the correction amount changing with time: where is the proportional constant for controlling the correction amplitude, can be updated in real time based on information such as in-vehicle motion monitoring (seat backrest angle, passenger displacement), etc. If it is detected that the target position has a displacement, the beamwidth range is automatically expanded or contracted, and the phase shift function is updated accordingly.

[0112] This dynamic correction process can be achieved by monitoring the energy distribution of the directivity pattern output by the array in the high-frequency band and the mid-frequency band. If the main lobe leaves the target area or the sidelobe rises too high, the instantaneous value of the main lobe beamwidth and the amplification factor in the amplitude function are immediately adjusted, and the phase shift function is fine-tuned synchronously to redirect the main lobe peak.

[0113] 5. Overall output of the beamforming filter:

[0114] Finally, a directional beamforming filter is defined and synthesized for each frequency band, and a separate set of filter coefficients is generated for each frequency band b∈{LF,MF,HF}. The multi-band directional beamforming filter F is synthesized. beam ={F LF ,F MF ,F HF}

[0115] The multi-channel signal output by the multi-band directional beamforming filter creates a phase superposition and amplitude gain enhancement effect in the target direction, and exhibits phase cancellation and amplitude attenuation in the non-target direction, thereby improving the sound field consistency and listening performance of key seats.

[0116] Based on the sound field consistency adjustment coefficients output by the frequency band analysis module, this module prioritizes seats in an unbalanced or unoptimized state. Through determining the target direction vector, phase shift function, nonlinear amplitude allocation, and dynamic beamwidth correction, a multi-band directional beamforming filter is designed. This filter concentrates energy in the target direction, suppressing lateral and rearward noise, thereby significantly enhancing the sound effect in severely unbalanced seating areas and effectively improving their sound field.

[0117] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0118] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0119] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely to distinguish one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0120] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An automobile DSP power amplifier sound effect intelligent processing system, characterized in that, Comprise: Data acquisition module, three-dimensional modeling module, frequency band analysis module and beam optimization module; Data acquisition module: use microphone array and acoustic sensor, and transmit the collected data to the central processing unit; Three-dimensional modeling module: the central processing unit is based on the data collected at multiple points, and the three-dimensional acoustic geometric model in the car is constructed by applying ray tracing and image source method, and the reflection path and propagation delay of sound wave on each surface in the car are calculated; Frequency band analysis module: the audio signal is divided into low frequency, medium frequency and high frequency according to the predetermined frequency band, the distribution discrete degree and gain offset degree of each frequency band are measured based on the frequency spectrum distribution difference and gain fluctuation center position of each seat in the three-dimensional acoustic geometric model, and the sound field consistency adjustment coefficient is generated for evaluating the frequency band gain adjustment effect, and the sound field consistency adjustment coefficient is transmitted to the beam optimization module; Beam optimization module: according to the sound field consistency adjustment coefficient result, the position of the main audio target seat in the car is identified, the directional beamforming filter is designed, the amplitude and phase of each sound channel are adjusted, the directional sound beam pointing to the target seat is formed, and the noise interference in the non-target direction is suppressed.

2. The automobile DSP power amplifier sound effect intelligent processing system according to claim 1, characterized in that, The three-dimensional modeling module is used for: First, categorize all collected data points by spatial location. A unified spatial coordinate calibration was performed, and the in-vehicle space framework was constructed using a three-dimensional Cartesian coordinate system. Then, the following specific method is applied to complete the construction of the three-dimensional acoustic geometric model and the calculation of the reflection path: According to the in-vehicle structure design parameters, create a three-dimensional geometric grid model containing all acoustic surfaces wherein represents the spatial index of each surface; each surface is marked with specific attribute parameters wherein is the reflection coefficient, is the absorption coefficient, is the directional angle of the surface normal vector; From each sound source point Sound wave path rays are emitted towards the mesh surfaces, the intersection of the rays with each surface mesh and the angle of incidence are calculated ; The intersection calculation formula is: ; where is the ray direction vector, is the path parameter, solved by the geometric constraint equation; record the path length of each ray ; and the propagation time , where is the sound speed; Intersection based on the first reflection Generate virtual mirror points corresponding to the sound source points. Calculate multiple reflection paths from the mirror point to other surfaces; complete the multiple reflection paths using a recursive algorithm. The length and propagation delay are calculated; the path recursive formula is: and cumulative transmission time ; The phase difference is calculated for all ray and reflection path stack signals based on the travel time and frequency using the phase equation: The phase shift for each path is calculated and the cumulative phase stack effect for the full acoustic field is obtained. The results are integrated to build a three-dimensional acoustic geometric model containing path length, travel time, number of reflections, phase change information and all its parameters are recorded in matrix form.

3. The automobile DSP power amplifier sound effect intelligent processing system according to claim 2, characterized in that, The frequency band analysis module is used for: Based on the original audio signal in the car, the audio signal is divided into three intervals of low frequency LF, medium frequency MF and high frequency HF according to the preset boundary frequency; For each large interval, several subbands are divided to depict the energy distribution within each frequency band; let denote the th subband in the th frequency band, where and is the subband index. In combination with the three-dimensional acoustic geometric model, the sound pressure level of each seat The propagation attenuation coefficient and material absorption characteristics on each sub-band are corrected to obtain the corrected sub-band energy ; In order to measure the energy distribution discrete degree of each seat in different frequency bands, the multi-layer threshold progressive coverage calculation method is defined first: First, a threshold sequence is set for each seat and sub-band wherein increasing and following a geometric or logarithmic distribution to capture the varying situation of energy distribution from low to high; For threshold values With the corrected subband energy A subband coverage decision function is defined as: ; The coverage determination results of all subbands under the same frequency band are accumulated to obtain the seat coverage The subband coverage under the threshold value is: ; Using the multi-level fractal measure method, the distribution dispersion degree is obtained : ; wherein, is a non-linear exponent used to amplify or reduce the difference in sub-band coverage progression with threshold.

4. The automobile DSP power amplifier sound effect intelligent processing system according to claim 3, characterized in that, The frequency band analysis module is also used for: To assess the gain excursion condition, define a gain relative scalar: ; where, is the current gain setting for the seat in the frequency band , is a predefined ideal reference value, is used to map the gain excursion to the interval [0, 1). Subsequently, to quantify the degree of connectedness of the corresponding offsets between subbands, a gain offset connectedness is computed: .

5. The automobile DSP power amplifier sound effect intelligent processing system according to claim 4, characterized in that, The frequency band analysis module is also used for: The distribution dispersion is connected with the gain offset connectivity in the frequency band Fusion is carried out to obtain a sound field deviation index corresponding to the seat frequency band level: ; wherein, The nonlinear adjustment coefficient is used to control the contribution of the distribution dispersion in the deviation index; finally, the sound field consistency adjustment coefficient : ; all seat sound field consistency adjustment coefficients are arranged according to seat index To form a one-dimensional sequence .

6. The automobile DSP power amplifier sound effect intelligent processing system according to claim 3, characterized in that: The propagation attenuation coefficient and material absorption characteristics of each seat on each subband are corrected by the following method: first, based on the total length of the sound wave on the propagation path and the reflection angle of each path, the attenuation factor on the path is calculated, and the total propagation attenuation coefficient is obtained by synthesizing all the paths; secondly, the absorption coefficient of each reflection surface recorded in the three-dimensional model is queried, and the energy loss of each reflection point in the path is cumulatively calculated; finally, the initial energy value of each seat on the subband is multiplied by the propagation attenuation coefficient and the absorption loss correction coefficient in turn to obtain the corrected subband energy, which is used to describe the frequency band energy distribution under the real propagation condition.

7. The automobile DSP power amplifier sound effect intelligent processing system according to claim 5, characterized in that, The beam optimization module is used for: First, according to the sequence , the target locus index exceeding the consistency threshold and having the largest value is selected as , which is marked as a priority optimization target locus; In the three-dimensional acoustic geometric model, the spatial coordinates of the target seat are denoted as , the coordinates of the in-vehicle loudspeaker are denoted as ; the target direction is defined as ; the target direction indicates the direction from the center of the loudspeaker to the target seat; To realize the directional sound beam, the phases of the signals of each sound channel at different time delays are superimposed and controlled; the array contains independent sound channels, the positions of which in the three-dimensional acoustic geometric model are respectively Defining a phase shift function , for phase modification of the first channel in the frequency domain range, so that it produces coherent superposition in the target direction and as much phase cancellation as possible in other directions; the constraint is denoted as ; where denotes the vector dot product, denotes the set of interference directions perpendicular or opposite to the target direction, denotes the comprehensive modification amount of the first channel in the phase dimension and the infinitesimal coordinate offset; this constraint ensures that the beam energy of the target direction is higher than that of other interference directions.

8. The automobile DSP power amplifier sound effect intelligent processing system according to claim 7, characterized in that, The beam optimization module is also used for: In addition to phase control, the amplitude of each channel output is assigned; define the amplitude function ; wherein is an amplification coefficient, denotes a discrete time index; is an amplitude adjustment factor; At the same time, in order to suppress the side lobe energy, the side lobe domain is defined within a certain angle range from the target direction vector, and if it is detected that there is a higher standard amplitude superposition trend in the side lobe domain area, the amplitude function of the corresponding sound channel is adjusted; In the time domain dimension, the main lobe direction and amplitude are not fixed, in order to adapt to the target position change caused by the movement of passengers in the car or the change of seat angle, dynamic beam width correction is carried out; Let the instantaneous value of the main lobe beam width be the sum of the basic beam width initially set and the correction amount changing with time; if it is detected that the target position has shifted, the beam width range is automatically expanded or contracted, and the phase shift function is updated accordingly; The dynamic beam width correction process monitors the energy distribution of the directivity pattern output by the array at high and medium frequencies. If the main lobe is found to be moving away from the target area, the instant value of the main lobe beam width and the amplification factor in the amplitude function are adjusted immediately, and the phase shift function is fine-tuned simultaneously to redirect the main lobe peak value. Finally, a directional beamforming filter is defined and synthesized for each frequency band, respectively, and the directional beamforming filters are combined for the frequency bands The filter coefficient sets are generated separately, and the multi-band directional beamforming filter is synthesized.

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