Noise reduction method, noise reduction system, vehicle, device, storage medium, and program product

Abstract

The application discloses a noise reduction method, a noise reduction system, a vehicle, equipment, a storage medium and a program product, relates to the technical field of vehicles, and aims to improve the noise reduction efficiency of a vehicle. The method comprises the following steps: collecting a sound signal in the vehicle; and performing noise reduction processing on the sound signal based on a reference signal of a target reference channel.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more particularly to a noise reduction method, noise reduction system, vehicle, device, storage medium, and program product. Background Technology

[0002] With the continuous development of the automotive industry and consumers' increasing emphasis on vehicle performance, road noise has gradually attracted attention. As a significant issue in transportation, road noise has a profound impact on driving experience and public health. Especially at high speeds, increased in-vehicle noise levels not only impair passenger comfort but may also adversely affect driver attention and reaction time, thereby threatening driving safety.

[0003] Compared to traditional noise reduction methods, most rely on Active Road Noise Cancellation (ARNC) technology. Chassis vibration sensors act as reference sensors to capture subtle changes in vehicle structural vibration. This vibration information serves as a reference signal for generating sound waves that are out of phase with the noise signal. Microphones monitor in-vehicle noise signals in real time, adjusting the phase and amplitude of the out-of-phase sound waves to achieve noise reduction. However, vehicles typically have multiple vibration sensors, meaning multiple reference signals. Relying on multiple reference signals significantly increases the complexity of the noise reduction process, resulting in relatively low efficiency. Summary of the Invention

[0004] The purpose of this application is to provide a noise reduction method, noise reduction system, vehicle, equipment, storage medium, and program product to address the problem of low noise reduction efficiency.

[0005] In a first aspect, this application provides a noise reduction method, comprising: acquiring sound signals inside a vehicle; and performing noise reduction processing on the sound signals based on reference signals from a target reference channel.

[0006] The noise reduction method provided in this application selects a target reference channel from all reference channels of the vibration sensor to obtain the reference signal of the target reference channel, thereby reducing noise in the sound signal. By selecting a target reference channel through screening, a reference signal that is strongly correlated with the sound signal and can truly reflect the noise characteristics is extracted. This simplifies the noise reduction process and improves noise reduction efficiency. At the same time, using the reference signal of the target reference channel for noise reduction can specifically suppress noise sources, achieving effective noise reduction while preserving the useful information in the sound signal to the greatest extent.

[0007] In some embodiments, the target reference channel is selected from the reference channel of the vehicle's target vibration sensor based on the sound signal.

[0008] In some embodiments, the target reference channel is determined by repeatedly performing a channel elimination operation from the reference channels of the target vibration sensor based on the sound signal until the remaining target reference channels meet a first preset condition.

[0009] In some embodiments, the first preset condition includes: the number of target reference channels is less than or equal to a preset channel number threshold, and / or the sum of the multicoherence coefficients of the reference signal and the audio signal at the peak frequency of the noise band of each target reference channel is less than a preset multicoherence coefficient and threshold.

[0010] In some embodiments, the channel elimination operation includes: determining multiple candidate reference channel sets, wherein a candidate reference channel set is the reference channel remaining after eliminating one reference channel from the reference channel set, and the eliminated reference channel is different for different candidate reference channel sets; wherein, when the channel elimination operation is performed for the first time, the reference channel set includes the reference channel of the target sensor; determining the multicoherence information content of each candidate reference channel set based on the audio signal; and, based on the multicoherence information content of each candidate reference channel set, selecting the candidate reference channel set with the largest multicoherence information content among the multiple candidate reference channel sets as the new reference channel set.

[0011] In some embodiments, determining the multicoherence information of each candidate reference channel set based on the audio signal includes: determining the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal within the noise reduction frequency band; and determining the multicoherence information of each candidate reference channel set based on the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal.

[0012] In some embodiments, the target vibration sensor is selected from the vehicle's vibration sensors based on sound signals.

[0013] In some embodiments, the target sensor is determined by: determining the sum of the multicoherence coefficients of the vibration sensors based on the sound signal; selecting a first target vibration sensor from the vibration sensors based on the sum of the multicoherence coefficients of the vibration sensors; determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal, wherein the remaining vibration sensors represent other vibration sensors besides the target vibration sensor; and selecting other target vibration sensors from the remaining vibration sensors based on the increment of the multicoherence information of the remaining vibration sensors.

[0014] In some embodiments, the above-mentioned selection of the first target vibration sensor from vibration sensors based on the sum of the multicoherence coefficients of vibration sensors includes: selecting the vibration sensor with the largest sum of multicoherence coefficients from vibration sensors as the first target vibration sensor based on the sum of the multicoherence coefficients of vibration sensors.

[0015] In some embodiments, the above-mentioned selection of other target vibration sensors from the remaining vibration sensors based on the increment of multicoherence information of the remaining vibration sensors includes: selecting the vibration sensor with the largest increment of multicoherence information from the remaining vibration sensors as the target vibration sensor based on the increment of multicoherence information of the remaining vibration sensors, until the second preset condition is met.

[0016] In some embodiments, the second preset condition includes the number of selected target vibration sensors being greater than or equal to a preset number.

[0017] In some embodiments, the second preset condition further includes: the sum of the multicoherence coefficients of the reference signals of each reference channel of the target vibration sensor and the sound signal at the peak frequency of the noise band is greater than or equal to a preset multicoherence coefficient and a threshold.

[0018] In some embodiments, the above-mentioned determination of the sum of multiple coherence coefficients of the vibration sensor based on the sound signal includes: performing correlation calculations between the sound signal and the reference signals of each reference channel of the vibration sensor in the noise reduction frequency band to obtain multiple multiple coherence coefficients, each multiple coherence coefficient corresponding to a reference channel of the vibration sensor; and determining the sum of the multiple multiple coherence coefficients as the sum of multiple coherence coefficients.

[0019] In some embodiments, the above-described determination of the increment of multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal includes: determining the sum of the multicoherence coefficients of the selected target vibration sensors to the sound signal within the noise reduction frequency band; determining the multicoherence information of the selected target vibration sensor based on the sum of the multicoherence coefficients of the selected target vibration sensors to the sound signal; determining the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal within the noise reduction frequency band; and determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the multicoherence information of the selected target vibration sensor and the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal.

[0020] In some embodiments, the target reference channel is a reference channel of the vehicle's vibration sensor whose correlation with the sound signal is greater than a preset correlation threshold.

[0021] In some embodiments, the above-mentioned acquisition of sound signals inside the vehicle includes: acquiring sound signals inside the vehicle through a microphone corresponding to the target seat; and performing noise reduction processing on the sound signals based on a reference signal of the target reference channel, including: outputting a noise-reduced signal of the sound signals through a speaker corresponding to the target seat, wherein the noise-reduced signal is determined based on the reference signal of the target reference channel.

[0022] In some embodiments, before acquiring sound signals inside the vehicle via the microphone corresponding to the target seat, the method further includes: determining that a passenger is present in the target seat.

[0023] In some embodiments, the method further includes: acquiring pressure detection information on the target seat; and detecting whether a passenger is present on the target seat based on the pressure detection information.

[0024] Secondly, this application provides a noise reduction system, including: a microphone, a speaker, a vibration sensor, and a controller; the controller is configured to: acquire sound signals collected by the microphone; and invoke the speaker to perform noise reduction processing on the sound signals based on the reference signal of the target reference channel of the vibration sensor.

[0025] In some embodiments, the target vibration sensor is selected from the vehicle's vibration sensors based on sound signals.

[0026] In some embodiments, the target reference channel is determined by repeatedly performing a channel elimination operation from the reference channel of the target vibration sensor based on the sound signal until the remaining target reference channel meets the first preset condition.

[0027] In some embodiments, the first preset condition includes: the number of target reference channels is less than or equal to a preset channel number threshold, and / or the sum of the multicoherence coefficients of the reference signal and the audio signal at the peak frequency of the noise band of each target reference channel is less than a preset multicoherence coefficient and threshold.

[0028] In some embodiments, the controller is configured to perform a channel elimination operation including: determining a plurality of candidate reference channel sets, wherein a candidate reference channel set is the reference channel remaining after eliminating one reference channel from the reference channel set, and the eliminated reference channel is different for different candidate reference channel sets; wherein, when performing the channel elimination operation for the first time, the reference channel set includes the reference channel of the target sensor; determining the multicoherence information content of each candidate reference channel set based on the audio signal; and, based on the multicoherence information content of each candidate reference channel set, selecting the candidate reference channel set with the largest multicoherence information content among the plurality of candidate reference channel sets as the new reference channel set.

[0029] In some embodiments, the controller is configured to determine the amount of multicoherence information for each candidate reference channel set based on the audio signal, including: determining the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal within the noise reduction frequency band; and determining the amount of multicoherence information for each candidate reference channel set based on the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal.

[0030] In some embodiments, the target vibration sensor is selected from the vehicle's vibration sensors based on sound signals.

[0031] In some embodiments, the target sensor is determined by: determining the sum of the multicoherence coefficients of the vibration sensors based on the sound signal; selecting a first target vibration sensor from the vibration sensors based on the sum of the multicoherence coefficients of the vibration sensors; determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal, wherein the remaining vibration sensors represent other vibration sensors besides the target vibration sensor; and selecting other target vibration sensors from the remaining vibration sensors based on the increment of the multicoherence information of the remaining vibration sensors.

[0032] In some embodiments, the controller is configured to select a first target vibration sensor from the vibration sensors based on the sum of the multicoherence coefficients of the vibration sensors, including: selecting the vibration sensor with the largest sum of multicoherence coefficients from the vibration sensors as the first target vibration sensor based on the sum of the multicoherence coefficients of the vibration sensors.

[0033] In some embodiments, the controller is configured to select other target vibration sensors from the remaining vibration sensors based on the increment of the multicoherence information of the remaining vibration sensors, including: selecting the vibration sensor with the largest increment of the multicoherence information from the remaining vibration sensors as the target vibration sensor based on the increment of the multicoherence information of the remaining vibration sensors, until a second preset condition is met.

[0034] In some embodiments, the second preset condition includes the number of selected target vibration sensors being greater than or equal to a preset number.

[0035] In some embodiments, the second preset condition further includes: the sum of the multicoherence coefficients of the reference signals of each reference channel of the target vibration sensor and the sound signal at the peak frequency of the noise band is greater than or equal to a preset multicoherence coefficient and a threshold.

[0036] In some embodiments, the controller is configured to determine the sum of multiple coherence coefficients of the vibration sensor based on the sound signal, including: performing correlation calculations between the sound signal and the reference signals of each reference channel of the vibration sensor in the noise reduction frequency band to obtain a plurality of multiple coherence coefficients, each multiple coherence coefficient corresponding to a reference channel of the vibration sensor; and determining the sum of the plurality of multiple coherence coefficients as the sum of multiple coherence coefficients.

[0037] In some embodiments, the controller is configured to determine the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal, including: determining the sum of the multicoherence coefficients of the selected target vibration sensors to the sound signal within a noise reduction frequency band; determining the multicoherence information of the selected target vibration sensor based on the sum of the multicoherence coefficients of the selected target vibration sensors to the sound signal; determining the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal within a noise reduction frequency band; and determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the multicoherence information of the selected target vibration sensor and the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal.

[0038] In some embodiments, the target reference channel is a reference channel of the vehicle's vibration sensor whose correlation with the sound signal is greater than a preset correlation threshold.

[0039] In some embodiments, the controller is configured to acquire sound signals inside the vehicle, including: acquiring sound signals inside the vehicle through a microphone corresponding to the target seat; the controller is configured to perform noise reduction processing on the sound signals based on a reference signal of a target reference channel of a vibration sensor, including: outputting a noise-reduced signal of the sound signals through a speaker corresponding to the target seat, the noise-reduced signal being determined based on the reference signal of the target reference channel.

[0040] In some embodiments, the microphones include microphones for each of the seats, and the speakers include speakers for each of the seats; a speaker for one seat is used to perform noise reduction processing on the sound signals collected by the microphones of the same seat.

[0041] In some embodiments, the controller includes a first controller and a plurality of second controllers for each of the seats; the first controller is configured to: acquire sound signals collected by the microphone of the target seat; select a target vibration sensor from the vibration sensors of the vehicle based on the sound signals; select a target reference channel from the reference channel of the target vibration sensor based on the sound signals; and transmit the reference signal of the target reference channel to the second controller of the target seat; the second controller is configured to: generate a noise reduction signal based on the reference signal of the target reference channel, and call the speaker of the target seat to output the noise reduction signal.

[0042] In some embodiments, the plurality of seats include at least: a driver's seat, a front passenger seat, a left rear seat, and a right rear seat.

[0043] In some embodiments, the microphone of the driver's seat includes at least one of the following: a first left headrest microphone and a first right headrest microphone; the microphone of the passenger seat includes at least one of the following: a second left headrest microphone and a second right headrest microphone; the microphone of the left rear seat includes at least one of the following: a third left headrest microphone and a third right headrest microphone; and the microphone of the right rear seat includes at least one of the following: a fourth left headrest microphone and a fourth right headrest microphone.

[0044] In some embodiments, the speaker of the driver's seat includes at least one of the following: a first door speaker and a first ceiling speaker; the speaker of the passenger seat includes at least one of the following: a second door speaker and a second ceiling speaker; the speaker of the left rear seat includes at least one of the following: a third door speaker and a third ceiling speaker; and the speaker of the right rear seat includes at least one of the following: a fourth door speaker and a fourth ceiling speaker.

[0045] In some embodiments, the system further includes: a pressure sensor, comprising a plurality of pressure sensors for each of the seats; the pressure sensor for the driver's seat includes: a first pressure sensor; the pressure sensor for the front passenger seat includes: a second pressure sensor; the pressure sensor for the left rear seat includes: a third pressure sensor; and the pressure sensor for the right rear seat includes: a fourth pressure sensor; the pressure sensor is configured to: detect pressure detection information on the target seat and send the pressure detection information to the controller.

[0046] In some embodiments, before acquiring sound signals inside the vehicle via the microphone corresponding to the target seat, the controller is further configured to determine that a passenger is present in the target seat.

[0047] In some embodiments, the controller is further configured to: acquire pressure detection information on the target seat; and detect whether a passenger is present on the target seat based on the pressure detection information.

[0048] Thirdly, this application provides a noise reduction system, including: multiple noise reduction units, multiple noise reduction controllers, and a vibration sensor; each noise reduction controller is connected to a noise reduction unit, wherein the noise reduction unit includes a microphone and a speaker.

[0049] In some embodiments, the microphones of the noise reduction unit include at least: a left headrest microphone and a right headrest microphone; the speakers of the noise reduction unit include at least: door speakers and ceiling speakers.

[0050] In some embodiments, the noise reduction units correspond one-to-one with the seats; the seats include at least: driver's seat, front passenger seat, left rear seat, and right rear seat.

[0051] In some embodiments, the noise reduction controller is configured to: acquire the sound signal collected by the microphone corresponding to the target seat; and, based on the reference signal of the target reference channel of the vibration sensor, call the speaker corresponding to the target seat to reduce the noise of the sound signal.

[0052] In some embodiments, the system further includes: a main controller; the main controller is configured to: select a target vibration sensor from the vehicle's vibration sensors based on an audio signal; select a target reference channel from the reference channel of the target vibration sensor based on an audio signal; and transmit the reference signal of the target reference channel to the noise reduction controller of the target seat.

[0053] Fourthly, this application provides an electronic device, including: a processor and a memory configured to store processor-executable instructions; wherein the processor is configured to execute the instructions to implement any of the optional noise reduction methods in the first aspect described above.

[0054] Fifthly, this application provides a computer-readable storage medium storing instructions that, when executed by a device, enable the device to perform any of the optional noise reduction methods described in the first aspect.

[0055] Sixthly, this application provides a vehicle comprising: the noise reduction system of the second aspect, or the noise reduction system of the third aspect, or the electronic device of the fourth aspect, or the computer-readable storage medium of the fifth aspect.

[0056] In a seventh aspect, this application provides a computer program product including computer instructions that, when executed on a processor of a device, enable the device to perform any of the optional noise reduction methods described in the first aspect above. Attached Figure Description

[0057] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a schematic diagram of the structure of a noise reduction system provided in an embodiment of this application;

[0059] Figure 2 This is a schematic diagram of another noise reduction system provided in an embodiment of this application;

[0060] Figure 3 A schematic diagram of the distribution of a vibration sensor provided in an embodiment of this application;

[0061] Figure 4 A control architecture diagram of a controller for a noise reduction system provided in an embodiment of this application;

[0062] Figure 5 A flowchart illustrating a noise reduction method provided in an embodiment of this application;

[0063] Figure 6 A flowchart illustrating another noise reduction method provided in an embodiment of this application;

[0064] Figure 7 This is a schematic diagram of the structure of a noise reduction device provided in an embodiment of this application;

[0065] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0066] Figure label:

[0067] Vibration sensor 10; microphone 20; controller 30; speaker 40;

[0068] Vibration sensors: 301-314; First controller 339; Second controller for driver's seat 315; Second controller for passenger seat 321; Second controller for left rear seat 327; Second controller for right rear seat 333;

[0069] First left headrest microphone 319; First right headrest microphone 320; Second left headrest microphone 325; Second right headrest microphone 326; Third left headrest microphone 331; Third right headrest microphone 332; Fourth left headrest microphone 337; Fourth right headrest microphone 338;

[0070] First door speaker 316; First roof speaker 317; Second door speaker 322, Second roof speaker 323; Third door speaker 328, Third roof speaker 329; Fourth door speaker 334; Fourth roof speaker 335;

[0071] First pressure sensor 318; second pressure sensor 324; third pressure sensor 330; fourth pressure sensor 336. Detailed Implementation

[0072] In the embodiments of this application, the terms "first," "second," "third," "fourth," "fifth," and "sixth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," "third," "fourth," "fifth," and "sixth" may explicitly or implicitly include one or more of that feature.

[0073] In embodiments of this application, 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 limitation, 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 that element.

[0074] "A and / or B" includes the following three combinations: A only, B only, and a combination of A and B.

[0075] With the continuous development of the automotive industry and consumers' increasing emphasis on vehicle performance, road noise has gradually attracted attention. As a significant issue in transportation, road noise has a profound impact on driving experience and public health. Especially at high speeds, increased in-vehicle noise levels not only impair passenger comfort but may also adversely affect driver attention and reaction time, thereby threatening driving safety.

[0076] Compared to traditional noise reduction methods, most rely on Active Road Noise Cancellation (ARNC) technology. Chassis vibration sensors act as reference sensors to capture subtle changes in vehicle structural vibration. This vibration information serves as a reference signal for generating sound waves that are out of phase with the noise signal. Microphones monitor in-vehicle noise signals in real time, adjusting the phase and amplitude of the out-of-phase sound waves to achieve noise reduction. However, vehicles typically have multiple vibration sensors, meaning multiple reference signals. Relying on multiple reference signals significantly increases the complexity of the noise reduction process, resulting in relatively low efficiency.

[0077] In related technologies, one method involves receiving multiple reference signals from a reference sensor and generating a cancellation signal based on these reference signals. The cancellation signal is then output by a speaker to eliminate road noise transmitted from the wheels to the driver's quiet zone. However, this method relies on user experience and database data to form multiple sensor subsets, and the efficiency and accuracy of this process may be limited, resulting in limited noise reduction effectiveness.

[0078] In other embodiments, the control filter coefficients are calculated using reference signals and road noise signals, and then the error signal is solved. The noise reduction amount is then calculated from the error signal. Local optima are obtained by progressively expanding the autocorrelation matrix of the filtered reference signals and their cross-correlation matrix with the desired signal, iterating to the required number of reference signal combinations. Noise reduction efficiency is improved by filtering the reference signals. However, this method selects multiple reference signals that may originate from multiple different vibration sensors, failing to adequately consider the limitation on the number of vibration sensors.

[0079] During vehicle operation, a multi-channel signal acquisition unit collects reference signals and desired signals from the road noise detection microphone to establish a reference optimization database and a reference combination generalization test set. The reference optimization database is used to select Q-channel reference signal combinations from the P-channel reference signals. The test set is used to perform generalization tests on the optimized combinations.

[0080] In other embodiments, K main noise peaks and their corresponding frequencies can be selected. For each frequency, the reference signals are sorted according to the constant coherence coefficient. First, the optimal number of reference points for each frequency is determined based on the multicoherence coefficient increment. Then, the optimal number of reference points for the entire frequency band is determined using the multicoherence function, thereby obtaining usable reference signals. The control effect is then verified. If the control effect meets the requirements, the process ends; otherwise, the reference point optimization is repeated. Noise reduction efficiency is improved by filtering the reference signals. However, this method may select multiple reference signals that originate from multiple different vibration sensors, failing to fully consider the limitation on the number of vibration sensors.

[0081] In other embodiments, by determining the frequency band to be denoised and the evaluation index, an initial reference signal with the highest coherence to the noise signal is selected, a reference signal with the largest amount of information is selected and included in the initial reference signal set, the initial reference signal set is updated, and so on until all reference signals are included in the initial reference signal set in sequence. Based on the required number of input reference signals, the required reference signals are determined in the initial sensor set. The denoising efficiency is improved by filtering the reference signals.

[0082] However, the multiple reference signals selected by each of the above methods may come from multiple vibration sensors. During the testing phase, it is necessary to select the vibration sensor to be set in the vehicle from among these multiple vibration sensors, and to achieve noise reduction based on the reference signal provided by the selected vibration sensor. However, the number of vibration sensors to be set using the above methods may exceed the limit on the number of vibration sensors allowed by vehicle manufacturing costs during the production phase, which does not meet the needs of the production phase. Therefore, the above noise reduction methods are not very applicable during the vehicle testing and production phase.

[0083] Based on this, this application provides a noise reduction method, noise reduction system, vehicle, device, storage medium, and program product, including: acquiring sound signals inside a vehicle; and performing noise reduction processing on the sound signals based on reference signals of a target reference channel. By selecting a target reference channel from all reference channels of a vibration sensor, a reference signal of the target reference channel is obtained, thereby reducing noise in the sound signal. Determining the target reference channel through reference channel selection extracts a reference signal that is strongly correlated with the sound signal and can accurately reflect the noise characteristics. This simplifies the noise reduction process and improves noise reduction efficiency. Furthermore, using the reference signal of the target reference channel for noise reduction allows for targeted suppression of noise sources, effectively reducing noise while preserving the most useful information in the sound signal.

[0084] This application provides a vehicle, which can be a gasoline vehicle or a hybrid vehicle, and the vehicle includes a noise reduction system.

[0085] like Figure 1 As shown, this application provides a noise reduction system, including: a microphone 20, a speaker 40, a vibration sensor 10, and a controller 30.

[0086] In some embodiments, the controller 30 is configured to: acquire the sound signal collected by the microphone 20, and call the speaker 40 to perform noise reduction processing on the sound signal based on the reference signal of the target reference channel of the vibration sensor 10.

[0087] In some embodiments, microphone 20 includes microphones for each seat, and speaker 40 includes speakers for each seat; a speaker for one seat is used to perform noise reduction processing on sound signals acquired by the microphones of the same seat.

[0088] The target reference channel is the reference channel of the vehicle's vibration sensor whose correlation with the sound signal is greater than a preset correlation threshold.

[0089] It is understandable that the vibrations of a vehicle during operation are closely related to the generation of noise in the sound signal. Many sounds are caused by the vibration of vehicle components; for example, the vibration of the engine produces sounds at specific frequencies, and the friction vibration between the tires and the ground also generates corresponding noise. Therefore, the signals collected by vibration sensors can reflect the source and characteristics of noise to a certain extent. By analyzing the correlation between the reference signal and the sound signal, and selecting a reference channel with a strong correlation to the sound signal as the reference channel, the variation patterns and characteristics of noise in the sound signal can be reflected more accurately.

[0090] One possible approach is to collect sound signals from inside the vehicle using a microphone corresponding to the target seat.

[0091] Understandably, treating only the seats where passengers are present, compared to comprehensively reducing noise throughout the entire vehicle interior, reduces system complexity and energy consumption. It eliminates the need to deploy numerous noise reduction devices and sensors throughout the vehicle, reducing hardware costs and energy consumption, and improving resource utilization efficiency. Therefore, before collecting sound signals from the target seat via its corresponding microphone, it's necessary to confirm the presence of a passenger in that seat. Only when a passenger is present should sound signals be collected, allowing for targeted noise reduction at the location of the seat with passengers.

[0092] As one possible implementation, a noise-reduced signal of the sound signal is output through the speaker 40 corresponding to the target seat, wherein the noise-reduced signal is determined based on the reference signal of the target reference channel.

[0093] In one possible implementation, the reference signal is analyzed to determine the main frequency components of the sound signal and information such as the frequency and amplitude of the noise. Based on the reference signal, a noise model is established. According to the noise model, a noise-reduced signal with the same magnitude but opposite phase to the noise is generated. The generated noise-reduced signal is input into a loudspeaker. When the noise-reduced signal encounters the noise in the environment, they cancel each other out due to their opposite phase, thus achieving noise reduction of the sound signal.

[0094] In some embodiments, when noise reduction processing is performed on the sound signal, only the speakers at the location of the seat with passengers are activated to perform noise reduction processing on the location of the seat with passengers. This can more accurately improve the passenger riding experience, concentrate noise reduction resources on where they are needed, effectively reduce noise interference around the passenger's ears, and improve comfort.

[0095] In some embodiments, a vehicle speed sensor and an engine speed sensor may also be installed in the vehicle. By collecting vehicle speed and engine speed, the sound insulation and sound absorption measures in the vehicle can be automatically adjusted based on information such as vehicle speed and engine speed to achieve the purpose of noise reduction.

[0096] Therefore, by selecting the target reference channel from all reference channels of the vibration sensor, the reference signal of the target reference channel is obtained, thereby reducing noise in the sound signal. Determining the target reference channel through selection extracts a reference signal that is strongly correlated with the sound signal and accurately reflects the noise characteristics. This simplifies the noise reduction process and improves efficiency. Furthermore, using the reference signal of the target reference channel for noise reduction allows for targeted suppression of noise sources, effectively reducing noise while preserving the most useful information in the sound signal.

[0097] During the testing phase, this application first screens target vibration sensors to ensure that their quantity meets the vehicle manufacturing cost requirements during the production phase. Based on this, it further screens target reference channels, which can reduce unnecessary sensors while ensuring noise reduction effect. This improves the applicability of this method in the vehicle testing phase and provides strong support for vehicle cost control and performance improvement.

[0098] In the production stage, this application first screens the target vibration sensor and then screens the target reference channel. Compared with the prior art of directly screening the target reference channel, the method of this application is faster and the screened reference signal can achieve the same noise reduction effect.

[0099] It can be seen that the solution proposed in this application is applicable to the testing and production stages of vehicles. In the testing stage, by accurately selecting target vibration sensors and target reference channels, it can meet the vehicle manufacturing cost budget. In the production stage, the solution improves noise reduction efficiency with its efficient screening process.

[0100] In some embodiments, the target vibration sensor is selected from the vehicle's vibration sensors based on sound signals.

[0101] The target reference channel refers to the reference channel in the target vibration sensor that is strongly correlated with the sound signal. The method for determining the target reference channel can refer to the method for determining the target vibration sensor.

[0102] As one possible approach, the reference channel with a higher correlation is selected as the target reference channel by analyzing the correlation between the reference signal provided by the reference channel and the audio signal.

[0103] As another possible implementation, the model is trained using the features of the labeled audio signal and the reference signals provided by each reference channel as input, and the target reference channel as output. After training, the model predicts and selects the target reference channel with the highest correlation between the audio signal and the signals provided by the reference channels.

[0104] In some embodiments, the target reference channel is determined by repeatedly performing a channel elimination operation from the reference channels of the target vibration sensor based on the sound signal until the remaining target reference channels meet a first preset condition.

[0105] In one possible implementation, multiple candidate reference channel sets are determined. Based on the audio signal, the multicoherence information content of each candidate reference channel set is determined. Based on the multicoherence information content of each candidate reference channel set, the candidate reference channel set with the largest multicoherence information content among the multiple candidate reference channel sets is selected as a new reference channel set. Then, it is evaluated whether the remaining reference channels meet a first preset condition. If they do not meet the condition, the channel elimination operation continues; if they do meet the condition, the operation stops, and the remaining reference channels are the target reference channels that meet the requirements.

[0106] The candidate reference channel set consists of the reference channels remaining after removing one reference channel from the reference channel set. Different candidate reference channel sets correspond to different removed reference channels. When the channel removal operation is performed for the first time, the reference channel set includes the reference channels of the target sensor.

[0107] In one possible implementation, the multicoherence information of each candidate reference channel set is determined based on the audio signal, including: determining the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal within the noise reduction frequency band, and determining the multicoherence information of each candidate reference channel set based on the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal.

[0108] For example, the target vibration sensor has 3M reference channels, and the multicoherence information of each candidate reference channel set can be determined according to the following formula:

[0109]

[0110] in, Let γ represent the sum of the multicoherence coefficients of the candidate reference channel set for the audio signal, Q0 represent the multicoherence information content of the candidate reference channel set, and γ represent the multicoherence information content of the candidate reference channel set.2 Represents the multicoherence coefficient, y j Represents sound signal, X i The reference signal represents the reference channel of the vibration sensor, and R is the set of selected target vibration sensors.

[0111] In some embodiments, the first preset condition includes: the number of target reference channels is less than or equal to a preset channel number threshold, and / or the sum of the multicoherence coefficients of the reference signal and the audio signal at the peak frequency of the noise band of each target reference channel is less than a preset multicoherence coefficient and threshold.

[0112] As one possible implementation, after performing a channel elimination operation, it is determined that the number of target reference channels is less than or equal to a preset channel number threshold. If so, the channel elimination operation is stopped.

[0113] For example, if the number of reference channels of the target vibration sensor is 3M and the preset number of target reference channels is W, determine whether the number of deleted reference channels is greater than or equal to (3M-W). If it is greater than or equal to (3M-W), then stop the iteration.

[0114] As one possible implementation, after performing a channel elimination operation, it is determined that the number of target reference channels is less than or equal to a preset channel number threshold. If not, the sum of the multicoherence coefficients of the reference signal and the audio signal of each target reference channel at the peak frequency of the noise band is calculated. It is then determined whether the sum of the multicoherence coefficients of the reference signal and the audio signal of each target reference channel at the peak frequency of the noise band is less than the preset multicoherence coefficient and threshold. If yes, the channel elimination operation is stopped; otherwise, the channel elimination operation continues.

[0115] Therefore, by selecting the reference channel that is most closely related to the sound signal based on the multicoherence coefficient of each reference channel, the target reference channel can better reflect the impact of noise generated by vehicle vibration on the sound signal.

[0116] In some embodiments, the target vibration sensor is selected from the vehicle's vibration sensors based on sound signals.

[0117] Here, the target vibration sensor refers to the vibration sensor in the vehicle that is strongly correlated with the sound signal. The reference signal provided by the target vibration sensor is a valuable signal for the analysis of vehicle noise reduction, and the reference signals provided by each target vibration sensor do not overlap.

[0118] One possible approach is to analyze the correlation between the reference signal provided by the vibration sensor and the sound signal, and then select the vibration sensor with the highest correlation as the target vibration sensor. For example, the correlation between the signal provided by the vibration sensor and the sound signal can be analyzed by calculating correlation coefficients, cross-correlation functions, and other methods.

[0119] As another possible implementation, features are extracted from the sound signal and the reference signal provided by the vibration sensor. Then, the matching degree between the features of the reference signal provided by each vibration sensor and the features of the sound signal is compared, and the vibration sensor with the most similar features is selected as the target vibration sensor.

[0120] In some embodiments, the target vibration sensor is determined by: determining the sum of the multicoherence coefficients of the vibration sensors based on the sound signal; selecting a first target vibration sensor from the vibration sensors based on the sum of the multicoherence coefficients of the vibration sensors; determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal, wherein the remaining vibration sensors represent other vibration sensors besides the target vibration sensor; and selecting other target vibration sensors from the remaining vibration sensors based on the increment of the multicoherence information of the remaining vibration sensors.

[0121] It should be understood that the multicoherence coefficient is an indicator of the degree of linear relationship between two variables (a reference signal and a sound signal). Signals acquired by vibration sensors at different locations may exhibit varying degrees of correlation with the sound signal. By calculating the multicoherence coefficient, the degree of correlation between the signal acquired by each vibration sensor and the sound signal can be assessed.

[0122] As one possible approach, correlation calculations are performed between the sound signal and the reference signals of each reference channel of the vibration sensor within the noise reduction frequency band to obtain multiple multicoherence coefficients. Each multicoherence coefficient corresponds to a reference channel of the vibration sensor, and the sum of the multiple multicoherence coefficients is determined as the multicoherence coefficient sum.

[0123] In one possible implementation, the sum of the multicoherence coefficients of the vibration sensor is determined by the following formula:

[0124]

[0125] in, The sum of the multicoherence coefficients of the vibration sensor, γ 2 Represents the multicoherence coefficient, y j Represents sound signal, X i S represents the reference signal of the reference channel of the vibration sensor, and S represents the set of reference channels.

[0126] As one possible approach, the noise reduction frequency band can be determined by calculating and analyzing the noise spectrum of the sound signal. The noise spectrum decomposes the sound signal according to frequency, revealing the energy distribution of different frequency components. The specific process includes: using Fourier transform to convert the time-domain sound signal into a frequency-domain noise spectrum; analyzing the noise spectrum to identify the main noise components in the sound signal; and determining the frequency band to be processed based on the distribution of the main noise components in the noise spectrum, combined with the performance and objectives of the noise reduction system. Generally, frequency bands with higher noise energy and greater impact on human hearing are selected as the noise reduction band. For example, if the main noise inside a car is the low-frequency roar of the engine, then 100-300Hz can be considered the key noise reduction frequency band.

[0127] As one possible implementation, based on the sum of the multicoherence coefficients of the vibration sensors, the vibration sensor with the largest sum of multicoherence coefficients is selected as the first target vibration sensor.

[0128] As one possible implementation, the sum of the multicoherence coefficients of the selected target vibration sensor to the sound signal is determined within the noise reduction frequency band, the multicoherence information of the selected target vibration sensor is determined, the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal is determined, and the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor is determined based on the multicoherence information of the selected target vibration sensor and the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal.

[0129] In one possible implementation, the increment of the multicoherence information of the remaining vibration sensor relative to the selected target vibration sensor is determined by the following formula:

[0130]

[0131] in, X represents the sum of the multicoherence coefficients of the selected target vibration sensors. R This represents the selected target vibration sensor, and Q0 represents the amount of multicoherence information of the selected target vibration sensor. X represents the sum of the multicoherence coefficients of any one of the remaining vibration sensors. i This represents the reference signal of the reference channel of any of the remaining vibration sensors. This represents the increment of multicoherence information of the remaining vibration sensor relative to the selected target vibration sensor.

[0132] It should be noted that Q0 can be calculated based on the Fisher Information Matrix (FIM).

[0133] As one possible implementation, based on the increment of multicoherence information of the remaining vibration sensors, the vibration sensor with the largest increment of multicoherence information is selected as the target vibration sensor, and the process continues until a second preset condition is met.

[0134] In some embodiments, the second preset condition includes that the number of selected target vibration sensors is greater than or equal to a preset number. The preset number can be determined based on the number of vibration sensors installed in the vehicle and the computing power of the controller.

[0135] One possible implementation is to set a counter to record the number of target vibration sensors selected each time. The counter increments by 1 each time a target vibration sensor is successfully selected. Each time a target vibration sensor is selected, the counter value is compared with a preset number. If the counter value is greater than or equal to the preset number, a stop-iteration condition is triggered, terminating the iteration process.

[0136] In some embodiments, the second preset condition further includes: the sum of the multicoherence coefficients of the reference signals of each reference channel of the target vibration sensor and the sound signal at the peak frequency of the noise band is greater than or equal to a preset multicoherence coefficient and a threshold.

[0137] As one possible implementation, when the number of target vibration sensors is greater than or equal to a preset number, the sum of the multicoherence coefficients of the reference signal and the sound signal at the peak frequency of the noise band for each reference channel of the target vibration sensor is calculated and compared with a preset multicoherence coefficient and a threshold. The sum of the multicoherence coefficients of the reference signal and the sound signal at the peak frequency of the noise band for each reference channel of the target vibration sensor can be determined according to formula (7).

[0138] In some embodiments, the preset multicoherence coefficient and threshold can be determined based on the peak value of the noise reduction frequency band.

[0139] As one possible approach, the peak frequency corresponding to the maximum peak noise in the noise reduction band is determined, and the multicoherence coefficient corresponding to the noise peak is calculated according to formula (8).

[0140] NR = -10log(1-γ) 2 ) Formula (8)

[0141] NR represents the noise level.

[0142] For example, when the noise at the maximum peak is 9dB, the corresponding multicoherence coefficient is 0.87, which is the preset multicoherence coefficient and threshold C. value It is 0.87.

[0143] Therefore, by selecting the sensor most closely related to the sound signal based on the multicoherence coefficient of the vibration sensor, the selected target vibration sensor can better reflect the impact of noise generated by vehicle vibration on the sound signal.

[0144] In some embodiments, controller 30 includes a first controller and a second controller for each of the plurality of seats.

[0145] As one possible implementation, the first controller is configured to: acquire sound signals collected by the microphone of the target seat; select a target vibration sensor from the vehicle's vibration sensors based on the sound signals; select a target reference channel from the reference channel of the target vibration sensor based on the sound signals; and transmit the reference signal of the target reference channel to the second controller of the target seat. The second controller is configured to: generate a noise-reducing signal based on the reference signal of the target reference channel; and invoke the speaker of the target seat to output the noise-reducing signal.

[0146] like Figure 2 The noise reduction system shown includes: vibration sensors including 301-314, and controllers including: a first controller 339 and a second controller (315, 321, 327, 333) for each seat. The second controllers include: the second controller 315 for the driver's seat, the second controller 321 for the passenger seat, the second controller 327 for the left rear seat, and the second controller 333 for the right rear seat.

[0147] In some embodiments, the plurality of seats includes at least: a driver's seat, a front passenger seat, a left rear seat, and a right rear seat.

[0148] In some embodiments, the microphone for the driver's seat includes at least one of the following: a first left headrest microphone 319 and a first right headrest microphone 320. The microphone for the passenger seat includes at least one of the following: a second left headrest microphone 325 and a second right headrest microphone 326. The microphone for the left rear seat includes at least one of the following: a third left headrest microphone 331 and a third right headrest microphone 332. The microphone for the right rear seat includes at least one of the following: a fourth left headrest microphone 337 and a fourth right headrest microphone 338.

[0149] In some embodiments, the driver's seat speaker includes at least one of the following: a first door speaker 316 and a first ceiling speaker 317. The passenger seat speaker includes at least one of the following: a second door speaker 322 and a second ceiling speaker 323. The left rear seat speaker includes at least one of the following: a third door speaker 328 and a third ceiling speaker 329. The right rear seat speaker includes at least one of the following: a fourth door speaker 334 and a fourth ceiling speaker 335.

[0150] It should be noted that this application does not limit the number or placement of microphones and speakers on each seat. The number of microphones and speakers can be freely determined based on actual needs, cost considerations, and other factors. For example, if more accurate voice capture is desired, multiple microphones may be placed on a single seat, such as one on the headrest, one on the armrest, and one on the side of the backrest, to capture sound signals from all directions.

[0151] In some embodiments, the noise reduction system further includes: pressure sensors, comprising a plurality of pressure sensors for each seat; the pressure sensor for the driver's seat includes: a first pressure sensor 318. The pressure sensor for the passenger seat includes: a second pressure sensor 324. The pressure sensor for the left rear seat includes: a third pressure sensor 330. The pressure sensor for the right rear seat includes: a fourth pressure sensor 336.

[0152] In some embodiments, the pressure sensor is configured to detect pressure information on the target seat and send the pressure information to the controller. The controller is also configured to acquire the pressure information on the target seat; based on the pressure information, detect whether a passenger is present on the target seat; and if a passenger is present, collect sound signals from inside the vehicle via the microphone corresponding to the target seat. By configuring the pressure sensor, it only sends a weight change signal to the controller when a passenger is present and the sensor detects a weight change. The selection of the reference signal and the activation of the noise reduction system at that seat then occur, which not only saves energy but also extends the system's lifespan.

[0153] It should be noted that the vibration sensor is mounted on the vehicle's chassis to directly acquire vibration information during vehicle operation. The specific location of the vibration sensor on the chassis can be flexibly selected according to actual needs. This application does not limit the location of the vibration sensor; for example, the vibration sensor may be mounted near the suspension system to more accurately monitor wheel bounce and road surface smoothness, or it may be mounted at the center of the vehicle to obtain overall vibration data. Figure 3The diagram shows the distribution of vibration sensors on the vehicle chassis. 101-108 represent vibration sensors, which are installed on the rear suspension of the vehicle. Each vibration sensor can measure signals from three independent channels (X / Y / Z).

[0154] like Figure 4 As shown, the controller of the noise reduction system in this application adopts a distributed control architecture, which can provide the most suitable reference signal for the second controller of each passenger's seat in the vehicle. When noise reduction is required, the first controller selects the most suitable reference signal for that position from the reference signal of the vibration sensor based on the sound signal collected by the microphone, and sends the reference signal to the second controller corresponding to that seat. The second controller then calls the speaker corresponding to that position to output the noise reduction signal.

[0155] It should be understood that the distributed control architecture reduces computational complexity, enhances the robustness of the noise reduction system, and improves the noise reduction effect through modular design. The noise reduction system based on this distributed control architecture has the following advantages:

[0156] The distributed control architecture integrates the microphones, ceiling speakers, and door speakers at each seat into an independent subsystem. Each subsystem selects the most suitable reference signal for control based on its own noise environment, allowing each seat to be optimized independently and avoiding signal interference or computing resource contention issues that may arise with traditional centralized control architectures.

[0157] Furthermore, since each seat only needs to process the noise in its own area, noise control can be more precisely targeted at specific areas, especially in complex road noise environments. In the distributed control architecture, even if the second controller at one seat fails, the second controllers at other seats can still function normally, without significantly impacting the overall noise reduction system.

[0158] In some embodiments, this application provides another noise reduction system, including: a plurality of noise reduction units, a plurality of noise reduction controllers, and a vibration sensor.

[0159] Each noise reduction controller (i.e., the second controller mentioned above) is connected to a noise reduction unit, which includes a microphone and a speaker.

[0160] As one possible implementation, the microphones of the noise reduction unit include at least: a left headrest microphone and a right headrest microphone; the speakers of the noise reduction unit include at least: door speakers and ceiling speakers.

[0161] As one possible implementation, the noise reduction units mentioned above correspond one-to-one with the seats; the seats include at least: driver's seat, front passenger seat, left rear seat, and right rear seat.

[0162] As one possible implementation, the noise reduction controller is configured to: acquire the sound signal collected by the microphone corresponding to the target seat, and, based on the reference signal of the target reference channel of the vibration sensor, call the speaker corresponding to the target seat to reduce the noise of the sound signal.

[0163] As one possible implementation, the system further includes a main controller (i.e., the first controller described above). The main controller is configured to: select a target vibration sensor from the vehicle's vibration sensors based on an audio signal, select a target reference channel from the reference channel of the target vibration sensor based on an audio signal, and transmit the reference signal of the target reference channel to the noise reduction controller of the target seat.

[0164] It should be noted that the specific working process of each module of the noise reduction system in this embodiment can be referred to the noise reduction system provided in the above embodiment, and will not be repeated here.

[0165] In some embodiments, the noise reduction method of this application is applicable to the controller of the vehicle or the controller of the vehicle noise reduction system described above. The controller can be an electronic control unit, a microcontroller, or a unit module with control logic. This application does not impose any limitations on this.

[0166] like Figure 5 As shown, the noise reduction method of this application embodiment includes:

[0167] S501, Collect sound signals inside the vehicle.

[0168] S502. Noise reduction processing of the audio signal based on the reference signal of the target reference channel.

[0169] In some embodiments, the target reference channel is selected from the reference channel of the vehicle's target vibration sensor based on the sound signal.

[0170] In some embodiments, the target reference channel is determined by repeatedly performing a channel elimination operation from the reference channels of the target vibration sensor based on the sound signal until the remaining target reference channels meet a first preset condition.

[0171] In some embodiments, the first preset condition includes: the number of target reference channels is less than or equal to a preset channel number threshold, and / or the sum of the multicoherence coefficients of the reference signal and the audio signal at the peak frequency of the noise band of each target reference channel is less than a preset multicoherence coefficient and threshold.

[0172] In some embodiments, the channel elimination operation includes: determining multiple candidate reference channel sets, wherein a candidate reference channel set is the reference channel remaining after eliminating one reference channel from the reference channel set, and the eliminated reference channel is different for different candidate reference channel sets; wherein, when the channel elimination operation is performed for the first time, the reference channel set includes the reference channel of the target sensor; determining the multicoherence information content of each candidate reference channel set based on the audio signal; and, based on the multicoherence information content of each candidate reference channel set, selecting the candidate reference channel set with the largest multicoherence information content among the multiple candidate reference channel sets as the new reference channel set.

[0173] In some embodiments, determining the multicoherence information of each candidate reference channel set based on the audio signal includes: determining the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal within the noise reduction frequency band; and determining the multicoherence information of each candidate reference channel set based on the sum of the multicoherence coefficients of each candidate reference channel set to the audio signal.

[0174] In some embodiments, the target vibration sensor is selected from the vehicle's vibration sensors based on sound signals.

[0175] In some embodiments, the target sensor is determined by: determining the sum of the multicoherence coefficients of the vibration sensors based on the sound signal; selecting a first target vibration sensor from the vibration sensors based on the sum of the multicoherence coefficients of the vibration sensors; determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal, wherein the remaining vibration sensors represent other vibration sensors besides the target vibration sensor; and selecting other target vibration sensors from the remaining vibration sensors based on the increment of the multicoherence information of the remaining vibration sensors.

[0176] In some embodiments, the above-mentioned selection of the first target vibration sensor from vibration sensors based on the sum of the multicoherence coefficients of vibration sensors includes: selecting the vibration sensor with the largest sum of multicoherence coefficients from vibration sensors as the first target vibration sensor based on the sum of the multicoherence coefficients of vibration sensors.

[0177] In some embodiments, the above-mentioned selection of other target vibration sensors from the remaining vibration sensors based on the increment of multicoherence information of the remaining vibration sensors includes: selecting the vibration sensor with the largest increment of multicoherence information from the remaining vibration sensors as the target vibration sensor based on the increment of multicoherence information of the remaining vibration sensors, until the second preset condition is met.

[0178] In some embodiments, the second preset condition includes the number of selected target vibration sensors being greater than or equal to a preset number.

[0179] In some embodiments, the second preset condition further includes: the sum of the multicoherence coefficients of the reference signals of each reference channel of the target vibration sensor and the sound signal at the peak frequency of the noise band is greater than or equal to a preset multicoherence coefficient and a threshold.

[0180] In some embodiments, the above-mentioned determination of the sum of multiple coherence coefficients of the vibration sensor based on the sound signal includes: performing correlation calculations between the sound signal and the reference signals of each reference channel of the vibration sensor in the noise reduction frequency band to obtain multiple multiple coherence coefficients, each multiple coherence coefficient corresponding to a reference channel of the vibration sensor; and determining the sum of the multiple multiple coherence coefficients as the sum of multiple coherence coefficients.

[0181] In some embodiments, the above-described determination of the increment of multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal includes: determining the sum of the multicoherence coefficients of the selected target vibration sensors to the sound signal within the noise reduction frequency band; determining the multicoherence information of the selected target vibration sensor based on the sum of the multicoherence coefficients of the selected target vibration sensors to the sound signal; determining the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal within the noise reduction frequency band; and determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the multicoherence information of the selected target vibration sensor and the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal.

[0182] In some embodiments, the target reference channel is a reference channel of the vehicle's vibration sensor whose correlation with the sound signal is greater than a preset correlation threshold.

[0183] In some embodiments, the above-mentioned acquisition of sound signals inside the vehicle includes: acquiring sound signals inside the vehicle through a microphone corresponding to the target seat; and performing noise reduction processing on the sound signals based on a reference signal of the target reference channel, including: outputting a noise-reduced signal of the sound signals through a speaker corresponding to the target seat, wherein the noise-reduced signal is determined based on the reference signal of the target reference channel.

[0184] In some embodiments, before acquiring sound signals inside the vehicle via the microphone corresponding to the target seat, the method further includes: determining that a passenger is present in the target seat.

[0185] In some embodiments, the method further includes: acquiring pressure detection information on the target seat; and detecting whether a passenger is present on the target seat based on the pressure detection information.

[0186] It should be noted that the implementation process of the noise reduction method can be referred to the description in the noise reduction system above, and will not be repeated here.

[0187] like Figure 6 As shown, this application provides a noise reduction method, including the following steps:

[0188] S601, Collect sound signals inside the vehicle.

[0189] S602. Calculate the noise spectrum of the sound signal.

[0190] S603. Determine the noise reduction frequency band through the noise spectrum, determine the peak frequency of the noise reduction frequency band, and determine the preset number of target sensors and the preset number of target reference channels based on the multicoherence coefficient corresponding to the noise peak.

[0191] As one possible implementation, the noise reduction frequency band can be 30Hz to 300Hz. The peak frequency corresponding to the maximum peak noise is found, and the multicoherence coefficient corresponding to the noise peak is calculated using the theoretical formula (8). The preset number of target sensors is determined to be M, and the preset number of target reference channels is determined to be W.

[0192] S604. Calculate the sum of the multiple coherence coefficients of each vibration sensor and the sound signal.

[0193] S605. Select the vibration sensor with the largest multicoherence coefficient as the first target vibration sensor, update the selected target vibration sensor sequence, and update the remaining vibration sensor sequence.

[0194] S606. Determine the sum of the multicoherence coefficients of the reference signal of the first target vibration sensor and the sound signal of each microphone, and then calculate the FIM.

[0195] S607. Based on the reference channel of the selected target vibration sensor, determine the sum of the multicoherence coefficients of the added vibration sensor and the sound signal, and determine the increment of the multicoherence information of the added vibration sensor relative to the selected target vibration sensor.

[0196] S608. The second target vibration sensor is determined based on the maximum value of the increment of the multicoherence information of the added vibration sensor relative to the selected target vibration sensor, and the selected target vibration sensor sequence is updated, and the remaining vibration sensor sequence is updated.

[0197] S609. Determine if the number of target vibration sensors is greater than or equal to M. If yes, proceed to S610; otherwise, proceed to S606.

[0198] S610. Determine the sum C of the multiple coherence coefficients of the reference signals and sound signals of each reference channel of the target vibration sensor at the peak frequency in the noise band.

[0199] S611. Determine if C is greater than or equal to C. value If yes, execute S612; otherwise, execute S606.

[0200] S612. Select a "reference channel" from all reference channels 3M of the target vibration sensor and calculate the FIM of the remaining channel after removing the "reference channel".

[0201] S613. Select the reference channel corresponding to the maximum value of the determinant of FIM and delete the reference channel.

[0202] S614. Determine if the number of reference channels to be deleted is greater than or equal to (3M-W). If yes, the process ends. If not, proceed to S615.

[0203] S615. Calculate the sum C of the multiple coherence coefficients C of the reference signal and the audio signal at the peak frequency of the noise band for each target reference channel.

[0204] S616. Determine if C is greater than or equal to C. value If yes, execute S612; otherwise, the process ends.

[0205] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the noise reduction device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0206] This application embodiment can, according to the above method, exemplarily divide the noise reduction device into functional modules. For example, the noise reduction device may include functional modules corresponding to each functional division, or two or more functions may be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0207] Figure 7This is a schematic diagram of a noise reduction device provided in an embodiment of this application. (Refer to...) Figure 7 The noise reduction device 700 includes: a data acquisition unit 710 and a processing unit 720.

[0208] Acquisition unit 710 is used to acquire sound signals inside the vehicle.

[0209] The processing unit 720 is used to perform noise reduction processing on the audio signal based on the reference signal of the target reference channel.

[0210] In some embodiments, the target reference channel is selected from the reference channel of the vehicle's target vibration sensor based on the sound signal.

[0211] In some embodiments, the processing unit 720 is specifically used to repeatedly perform a channel elimination operation from the reference channel of the target vibration sensor based on the sound signal until the remaining target reference channel meets the first preset condition.

[0212] In some embodiments, the first preset condition includes: the number of target reference channels is less than or equal to a preset channel number threshold, and / or the sum of the multicoherence coefficients of the reference signal and the audio signal at the peak frequency of the noise band of each target reference channel is less than a preset multicoherence coefficient and threshold.

[0213] In some embodiments, the processing unit 720 is specifically used to determine multiple candidate reference channel sets, wherein a candidate reference channel set is the reference channel remaining after removing one reference channel from the reference channel set, and the removed reference channel is different for different candidate reference channel sets; wherein, when the channel removal operation is performed for the first time, the reference channel set includes the reference channel of the target sensor; based on the sound signal, the multicoherence information content of each candidate reference channel set is determined; based on the multicoherence information content of each candidate reference channel set, the candidate reference channel set with the largest multicoherence information content among the multiple candidate reference channel sets is taken as the new reference channel set.

[0214] In some embodiments, the processing unit 720 is specifically used to determine the sum of the multicoherence coefficients of each candidate reference channel set for the audio signal within the noise reduction frequency band; and to determine the multicoherence information of each candidate reference channel set based on the sum of the multicoherence coefficients of each candidate reference channel set for the audio signal.

[0215] In some embodiments, the target vibration sensor is selected from the vehicle's vibration sensors based on sound signals.

[0216] In some embodiments, the processing unit 720 is specifically configured to: determine the sum of the multicoherence coefficients of the vibration sensors based on the sound signal; select a first target vibration sensor from the vibration sensors based on the sum of the multicoherence coefficients of the vibration sensors; determine the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal, wherein the remaining vibration sensors represent other vibration sensors besides the target vibration sensor; and select other target vibration sensors from the remaining vibration sensors based on the increment of the multicoherence information of the remaining vibration sensors.

[0217] In some embodiments, the processing unit 720 is specifically used to select the vibration sensor with the largest sum of multicoherence coefficients from the vibration sensors as the first target vibration sensor based on the sum of the multicoherence coefficients of the vibration sensors.

[0218] In some embodiments, the processing unit 720 is specifically used to select the vibration sensor with the largest increment of multicoherence information from the remaining vibration sensors as the target vibration sensor based on the increment of multicoherence information of the remaining vibration sensors, until the second preset condition is met.

[0219] In some embodiments, the second preset condition includes the number of selected target vibration sensors being greater than or equal to a preset number.

[0220] In some embodiments, the second preset condition further includes: the sum of the multicoherence coefficients of the reference signals of each reference channel of the target vibration sensor and the sound signal at the peak frequency of the noise band is greater than or equal to a preset multicoherence coefficient and a threshold.

[0221] In some embodiments, the processing unit 720 is specifically used to perform correlation calculations between the sound signal and the reference signal of each reference channel of the vibration sensor within the noise reduction frequency band to obtain multiple multiple coherence coefficients, each multiple coherence coefficient corresponding to a reference channel of the vibration sensor; and to determine the sum of the multiple multiple coherence coefficients as the sum of multiple coherence coefficients.

[0222] In some embodiments, the processing unit 720 is specifically configured to: determine the sum of the multicoherence coefficients of the selected target vibration sensor to the sound signal within the noise reduction frequency band; determine the multicoherence information of the selected target vibration sensor based on the sum of the multicoherence coefficients of the selected target vibration sensor to the sound signal; determine the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal within the noise reduction frequency band; and determine the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the multicoherence information of the selected target vibration sensor and the sum of the multicoherence coefficients of any one of the remaining vibration sensors to the sound signal.

[0223] In some embodiments, the target reference channel is a reference channel of the vehicle's vibration sensor whose correlation with the sound signal is greater than a preset correlation threshold.

[0224] In some embodiments, the acquisition unit 710 is specifically used to acquire sound signals inside the vehicle through the microphone corresponding to the target seat; the processing unit 720 is specifically used to output a noise reduction signal of the sound signal through the speaker corresponding to the target seat, the noise reduction signal being determined based on the reference signal of the target reference channel.

[0225] In some embodiments, before acquiring sound signals inside the vehicle via the microphone corresponding to the target seat, the processing unit 720 is further configured to determine that a passenger is present in the target seat.

[0226] In some embodiments, the processing unit 720 is further configured to acquire pressure detection information on the target seat; and based on the force detection information, detect whether there is a passenger on the target seat.

[0227] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 8 As shown, the electronic device 800 includes, but is not limited to, a processor 801 and a memory 802.

[0228] The memory 802 described above is used to store the executable instructions of the processor 801. It is understood that the processor 801 is configured to execute instructions to implement the noise reduction method in the above embodiments.

[0229] It should be noted that those skilled in the art will understand that Figure 8 The electronic device structure shown does not constitute a limitation on the electronic device; the electronic device may include, but is not limited to, other electronic devices. Figure 8 This may indicate more or fewer components, or combinations of certain components, or different component arrangements.

[0230] The processor 801 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 802, and by calling data stored in the memory 802, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. The processor 801 may include one or more processing units. Optionally, the processor 801 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 801.

[0231] The memory 802 can be used to store software programs and various data. The memory 802 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required by at least one functional module (such as a determination unit, processing unit, etc.), etc. Furthermore, the memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0232] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 802 including instructions, which can be executed by a processor 801 of an electronic device 800 to implement the methods in the above embodiments.

[0233] In actual implementation, Figure 7 Both the acquisition unit 710 and the processing unit 720 can be derived from... Figure 8 The processor 801 calls the computer program stored in the memory 802 to implement the process. The specific execution process can be found in the method section of the previous embodiment, and will not be repeated here.

[0234] Optionally, the computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0235] In an exemplary embodiment, this application also provides a vehicle that can be executed by a processor 801 of an electronic device to perform the methods described in the above embodiments.

[0236] In an exemplary embodiment, this application also provides a computer program product including one or more instructions, which can be executed by a processor 801 of an electronic device to perform the methods described above.

[0237] It should be noted that when one or more instructions in the computer-readable storage medium or computer program product are executed by the processor of an electronic device, they implement the various processes of the above method embodiments and achieve the same technical effect as the above method. To avoid repetition, they will not be described again here.

[0238] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0239] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0240] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the classified units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0241] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0242] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, essentially, or the part that contributes to the prior art, or a complete or partial classification of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0243] In the description of the embodiments of this application, specific features, structures, materials or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0244] The above are merely specific embodiments 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. A noise reduction method, characterized in that, The method includes: Collect sound signals from inside the vehicle; The audio signal is denoised based on the reference signal of the target reference channel.

2. The method according to claim 1, characterized in that, The target reference channel is selected from the reference channel of the target vibration sensor of the vehicle based on the sound signal.

3. The method according to claim 2, characterized in that, The target reference channel is determined in the following way: Based on the sound signal, the channel elimination operation is repeatedly performed from the reference channel of the target vibration sensor until the remaining target reference channel meets the first preset condition.

4. The method according to claim 3, characterized in that, The first preset condition includes: the number of target reference channels is less than or equal to a preset channel number threshold, and / or the sum of the multicoherence coefficients of the reference signal and the sound signal of each target reference channel at the peak frequency of the noise band is less than a preset multicoherence coefficient and threshold.

5. The method according to claim 3, characterized in that, The channel rejection operation includes: Multiple candidate reference channel sets are determined. Each candidate reference channel set consists of the reference channels remaining after removing one reference channel from the reference channel set. The removed reference channels are different for different candidate reference channel sets. When the channel removal operation is performed for the first time, the reference channel set includes the reference channels of the target sensor. Based on the sound signal, the amount of multicoherence information for each candidate reference channel set is determined; Based on the multicoherence information of each candidate reference channel set, the candidate reference channel set with the largest multicoherence information among the multiple candidate reference channel sets is taken as the new reference channel set.

6. The method according to claim 5, characterized in that, The determination of the multicoherence information of each candidate reference channel set based on the sound signal includes: Within the noise reduction frequency band, determine the sum of the multicoherence coefficients of each candidate reference channel set for the audio signal; The multicoherence information of each candidate reference channel set is determined based on the sum of the multicoherence coefficients of the audio signal for each candidate reference channel set.

7. The method according to any one of claims 2-6, characterized in that, The target vibration sensor is selected from the vehicle's vibration sensors based on the sound signal.

8. The method according to claim 7, characterized in that, The target sensor is determined in the following way: The multicoherence coefficient of the vibration sensor is determined based on the sound signal; Based on the sum of the multiple coherence coefficients of the vibration sensors, the first target vibration sensor is selected from the vibration sensors; The increment of multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor is determined based on the sound signal, wherein the remaining vibration sensors represent other vibration sensors besides the target vibration sensor. Based on the increment of the multicoherence information of the remaining vibration sensors, other target vibration sensors are selected from the remaining vibration sensors.

9. The method according to claim 8, characterized in that, The step of selecting the first target vibration sensor from the vibration sensors based on the sum of the multiple coherence coefficients of the vibration sensors includes: Based on the sum of the multicoherence coefficients of the vibration sensors, the vibration sensor with the largest sum of multicoherence coefficients is selected as the first target vibration sensor.

10. The method according to claim 8 or 9, characterized in that, The step of selecting other target vibration sensors from the remaining vibration sensors based on the increment of the multicoherence information of the remaining vibration sensors includes: Based on the increment of the multicoherence information of the remaining vibration sensors, the vibration sensor with the largest increment of multicoherence information is selected as the target vibration sensor, and the process continues until the second preset condition is met.

11. The method according to claim 10, characterized in that, The second preset condition includes that the number of selected target vibration sensors is greater than or equal to a preset number.

12. The method according to claim 10, characterized in that, The second preset condition also includes: the sum of the multicoherence coefficients of the reference signals and the sound signals of each reference channel of the target vibration sensor at the peak frequency of the noise band is greater than or equal to the preset multicoherence coefficient and threshold.

13. The method according to any one of claims 8 to 10, characterized in that, Determining the sum of the multicoherence coefficients of the vibration sensor based on the sound signal includes: Within the noise reduction frequency band, the sound signal is correlated with the reference signals of each reference channel of the vibration sensor to obtain multiple multiple coherence coefficients, each of which corresponds to a reference channel of the vibration sensor. The sum of the plurality of multicoherence coefficients is determined as the sum of the multicoherence coefficients.

14. The method according to any one of claims 8 to 10, characterized in that, The step of determining the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor based on the sound signal includes: Within the noise reduction frequency band, determine the sum of the multiple coherence coefficients of the selected target vibration sensor for the sound signal; The multicoherence information of the selected target vibration sensor is determined based on the sum of the multicoherence coefficients of the sound signal. Within the noise reduction frequency band, determine the sum of the multicoherence coefficients of any one of the remaining vibration sensors for the sound signal; Based on the multicoherence information of the selected target vibration sensor and the sum of the multicoherence coefficients of any one of the remaining vibration sensors for the sound signal, the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor is determined.

15. The method according to claim 1, characterized in that, The target reference channel is the reference channel of the vehicle's vibration sensor that has a correlation with the sound signal greater than a preset correlation threshold.

16. The method according to any one of claims 1 to 15, characterized in that, The method of collecting sound signals inside the vehicle includes: The sound signals inside the vehicle are collected using the microphone corresponding to the target seat; The noise reduction processing of the audio signal based on the reference signal of the target reference channel includes: The noise reduction signal is output by the speaker corresponding to the target seat, and the noise reduction signal is determined based on the reference signal of the target reference channel.

17. The method according to claim 16, characterized in that, Before acquiring the sound signal inside the vehicle via the microphone corresponding to the target seat, the method further includes: It is determined that there is a passenger in the target seat.

18. The method according to claim 17, characterized in that, The method further includes: Obtain pressure detection information on the target seat; Based on the pressure detection information, it is determined whether there is a passenger on the target seat.

19. A noise reduction system, characterized in that, include: Microphone, speaker, vibration sensor, and controller; The controller is configured to acquire sound signals collected by the microphone; The speaker is invoked to perform noise reduction processing on the sound signal based on the reference signal of the target reference channel of the vibration sensor.

20. The noise reduction system according to claim 19, characterized in that, The target reference channel is selected from the reference channel of the vehicle's target vibration sensor based on the sound signal.

21. The noise reduction system according to claim 20, characterized in that, The target reference channel is determined in the following way: Based on the sound signal, the channel elimination operation is repeatedly performed from the reference channel of the target vibration sensor until the remaining target reference channel meets the first preset condition.

22. The noise reduction system according to claim 21, characterized in that, The first preset condition includes: the number of target reference channels is less than or equal to a preset channel number threshold, and / or the sum of the multicoherence coefficients of the reference signal and the sound signal of each target reference channel at the peak frequency of the noise band is less than a preset multicoherence coefficient and threshold.

23. The noise reduction system according to claim 21, characterized in that, The controller is configured to perform channel rejection operations, including: Multiple candidate reference channel sets are determined. Each candidate reference channel set consists of the reference channels remaining after removing one reference channel from the reference channel set. The removed reference channels are different for different candidate reference channel sets. When the channel removal operation is performed for the first time, the reference channel set includes the reference channels of the target sensor. Based on the sound signal, the amount of multicoherence information for each candidate reference channel set is determined; Based on the multicoherence information of each candidate reference channel set, the candidate reference channel set with the largest multicoherence information among the multiple candidate reference channel sets is taken as the new reference channel set.

24. The noise reduction system according to claim 23, characterized in that, The controller is configured to determine the amount of multicoherence information for each candidate reference channel set based on the audio signal, including: Within the noise reduction frequency band, determine the sum of the multicoherence coefficients of each candidate reference channel set for the audio signal; The multicoherence information of each candidate reference channel set is determined based on the sum of the multicoherence coefficients of the audio signal for each candidate reference channel set.

25. The noise reduction system according to any one of claims 20-24, characterized in that, The target vibration sensor is selected from the vehicle's vibration sensors based on the sound signal.

26. The noise reduction system according to claim 25, characterized in that, The target sensor is determined in the following way: The multicoherence coefficient of the vibration sensor is determined based on the sound signal; Based on the sum of the multiple coherence coefficients of the vibration sensors, the first target vibration sensor is selected from the vibration sensors; The increment of multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor is determined based on the sound signal, wherein the remaining vibration sensors represent other vibration sensors besides the target vibration sensor. Based on the increment of the multicoherence information of the remaining vibration sensors, other target vibration sensors are selected from the remaining vibration sensors.

27. The noise reduction system according to claim 26, characterized in that, The controller is configured to select a first target vibration sensor from the vibration sensors based on the sum of the multiple coherence coefficients of the vibration sensors, including: Based on the sum of the multicoherence coefficients of the vibration sensors, the vibration sensor with the largest sum of multicoherence coefficients is selected as the first target vibration sensor.

28. The noise reduction system according to claim 26 or 27, characterized in that, The controller is configured to select other target vibration sensors from the remaining vibration sensors based on the increment of multicoherence information of the remaining vibration sensors, including: Based on the increment of the multicoherence information of the remaining vibration sensors, the vibration sensor with the largest increment of multicoherence information is selected as the target vibration sensor, and the process continues until the second preset condition is met.

29. The noise reduction system according to claim 28, characterized in that, The second preset condition includes that the number of selected target vibration sensors is greater than or equal to a preset number.

30. The noise reduction system according to claim 29, characterized in that, The second preset condition also includes: the sum of the multicoherence coefficients of the reference signals and the sound signals of each reference channel of the target vibration sensor at the peak frequency of the noise band is greater than or equal to the preset multicoherence coefficient and threshold.

31. The noise reduction system according to any one of claims 26 to 28, characterized in that, The controller is configured to determine the sum of the multiple coherence coefficients of the vibration sensor based on the sound signal, including: Within the noise reduction frequency band, the sound signal is correlated with the reference signals of each reference channel of the vibration sensor to obtain multiple multiple coherence coefficients, each of which corresponds to a reference channel of the vibration sensor. The sum of the plurality of multicoherence coefficients is determined as the sum of the multicoherence coefficients.

32. The noise reduction system according to any one of claims 26 to 28, characterized in that, The controller is configured to determine, based on the acoustic signal, the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor, including: Within the noise reduction frequency band, determine the sum of the multiple coherence coefficients of the selected target vibration sensor for the sound signal; The multicoherence information of the selected target vibration sensor is determined based on the sum of the multicoherence coefficients of the sound signal. Within the noise reduction frequency band, determine the sum of the multicoherence coefficients of any one of the remaining vibration sensors for the sound signal; Based on the multicoherence information of the selected target vibration sensor and the sum of the multicoherence coefficients of any one of the remaining vibration sensors for the sound signal, the increment of the multicoherence information of the remaining vibration sensors relative to the selected target vibration sensor is determined.

33. The noise reduction system according to claim 19, characterized in that, The target reference channel is used to indicate the reference channel of the vehicle's vibration sensor that has a correlation with the sound signal greater than a preset correlation threshold.

34. The noise reduction system according to any one of claims 19 to 33, characterized in that, The controller is configured to acquire sound signals within the vehicle, including: The sound signals inside the vehicle are collected using the microphone corresponding to the target seat; The controller is configured to perform noise reduction processing on the sound signal based on a reference signal from the target reference channel of the vibration sensor, including: The noise reduction signal is output by the speaker corresponding to the target seat, and the noise reduction signal is determined based on the reference signal of the target reference channel.

35. The noise reduction system according to claim 19, characterized in that, The microphones include individual microphones for each of the multiple seats, and the speakers include individual speakers for each of the multiple seats; the speaker of one seat is used to perform noise reduction processing on the sound signals collected by the microphones of the same seat.

36. The noise reduction system according to claim 25, characterized in that, The controller includes a first controller and a second controller for each of the plurality of seats; The first controller is configured to: acquire sound signals collected by the microphone of the target seat; select a target vibration sensor from the vibration sensors of the vehicle based on the sound signals; and select a target reference channel from the reference channel of the target vibration sensor based on the sound signals. The reference signal of the target reference channel is transmitted to the second controller of the target seat; The second controller is configured to generate a noise-reduced signal based on the reference signal of the target reference channel, and to invoke the speaker of the target seat to output the noise-reduced signal.

37. The noise reduction system according to claim 35 or 36, characterized in that, The plurality of seats includes at least: driver's seat, front passenger seat, left rear seat, and right rear seat.

38. The noise reduction system according to claim 37, characterized in that, The microphone for the driver's seat includes at least one of the following: a first left headrest microphone and a first right headrest microphone; The microphone in the passenger seat includes at least one of the following: a second left headrest microphone and a second right headrest microphone; The microphone for the left rear seat includes at least one of the following: a third left headrest microphone and a third right headrest microphone; The microphone for the right rear seat includes at least one of the following: a fourth left headrest microphone and a fourth right headrest microphone.

39. The noise reduction system according to claim 37, characterized in that, The speaker in the driver's seat includes at least one of the following: a first door speaker and a first ceiling speaker; The speaker in the passenger seat includes at least one of the following: a second door speaker and a second roof speaker; The speaker for the left rear seat includes at least one of the following: a third door speaker and a third roof speaker; The speaker for the right rear seat includes at least one of the following: a fourth door speaker and a fourth roof speaker.

40. The noise reduction system according to claim 37, characterized in that, The system also includes: a pressure sensor, which includes pressure sensors for each of the multiple seats; The pressure sensor is configured to detect pressure information on the target seat and send the pressure information to the controller.

41. The noise reduction system according to claim 40, characterized in that, Before acquiring the sound signal inside the vehicle via the microphone corresponding to the target seat, the controller is further configured to: It is determined that there is a passenger in the target seat.

42. The noise reduction system according to claim 41, characterized in that, The controller is also configured to acquire pressure detection information on the target seat; Based on the pressure detection information, it is determined whether there is a passenger on the target seat.

43. A noise reduction system, characterized in that, include: The system includes multiple noise reduction units, multiple noise reduction controllers, and a vibration sensor; each noise reduction controller is connected to one of the noise reduction units, wherein the noise reduction unit includes a microphone and a speaker.

44. The noise reduction system according to claim 43, characterized in that, The microphones of the noise reduction unit include at least: a left headrest microphone and a right headrest microphone; The noise reduction unit's speakers include at least: door speakers and ceiling speakers.

45. The noise reduction system according to claim 43 or 44, characterized in that, The noise reduction unit corresponds to each seat; the seats include at least: driver's seat, front passenger seat, left rear seat, and right rear seat.

46. ​​The noise reduction system according to claim 45, characterized in that, The noise reduction controller is configured to: acquire the sound signal collected by the microphone corresponding to the target seat; and, based on the reference signal of the target reference channel of the vibration sensor, call the speaker corresponding to the target seat to reduce the noise of the sound signal.

47. The noise reduction system according to claim 46, characterized in that, The system further includes: a main controller; the main controller is configured to: The target vibration sensor is selected from the vehicle's vibration sensors based on the sound signal; Select a target reference channel from the reference channels of the target vibration sensor based on the sound signal; The reference signal of the target reference channel is transmitted to the noise reduction controller of the target seat.

48. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the noise reduction method as described in any one of claims 1 to 18.

49. A computer-readable storage medium, characterized in that, When the computer-executable instructions stored in the computer-readable storage medium are executed by the processor of the device, the device is capable of performing the noise reduction method as described in any one of claims 1 to 18.

50. A vehicle, characterized in that, include: The noise reduction system as claimed in any one of claims 19-42, or the noise reduction system as claimed in any one of claims 43-47, or the electronic device as claimed in claim 48, or the computer-readable storage medium as claimed in claim 49.

51. A computer program product, the computer program product comprising computer instructions, characterized in that, When the computer instructions are executed on the processor of the device, the device is able to perform the noise reduction method as described in any one of claims 1 to 18.

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