Sound field holography method and device, active noise reduction method and device

Abstract

The application provides a sound field holographic method and device, an active noise reduction method and device, and relates to the technical field of signal processing. The method comprises determining sound pressure information corresponding to each of a plurality of observation points in a sound field; determining basis coefficient information corresponding to sound field basis information based on the sound field basis information and the sound pressure information corresponding to each of the plurality of observation points; and determining sub-sound field information of a corresponding frequency of the sound field based on the basis coefficient information. The application can realize real-time holographic global sound field information, rather than only local sound field information obtained by a limited number of microphones. Therefore, the application provides a data basis for realizing global minimization of narrow-frequency noise energy of the entire space sound field. Furthermore, the application does not need to perform Fourier transform on sound signals collected by microphones at the observation points, thereby better meeting the real-time requirement of active noise reduction.

Description

Technical Field

[0001] This application relates to the field of signal processing technology, specifically to a sound field holography method and apparatus, and an active noise reduction method and apparatus. Background Technology

[0002] With the rapid development of noise reduction technology, active noise cancellation technology has gradually become popular in the market and is widely used in scenarios with noise reduction requirements. In order to achieve good active noise cancellation effects, it is necessary to quickly and accurately obtain specific information about the noise signal.

[0003] Currently, noise reduction primarily relies on microphone arrays and spectrum estimation algorithms to determine specific noise data in a 3D spatial scene, followed by noise reduction operations based on this data. However, for 3D spatial scenes, the cost of deploying microphone arrays to accurately construct the entire sound field is extremely high, and even with numerous observation points, only local information about the sound field can be represented. Furthermore, spectrum estimation algorithms have significant time delays and cannot track the random amplitude fluctuations of sound signals at various frequencies in real time, making it difficult to meet real-time noise reduction requirements. Summary of the Invention

[0004] To address the aforementioned technical problems, this application is proposed. Embodiments of this application provide a sound field holography method and apparatus, and an active noise reduction method and apparatus.

[0005] In a first aspect, one embodiment of this application provides a sound field holography method, which includes: determining sound pressure information corresponding to each of multiple observation points in a sound field; determining fundamental coefficient information corresponding to the fundamental information of the sound field based on the fundamental information and sound pressure information corresponding to each of the multiple observation points; and determining sub-sound field information of the corresponding frequency of the sound field based on the fundamental coefficient information.

[0006] In conjunction with the first aspect, in one embodiment of this application, determining the basis coefficient information corresponding to the sound field basis information based on the sound field basis information and sound pressure information corresponding to each of the multiple observation points includes: determining the initial estimation error information corresponding to the multiple observation points based on the sound field basis information, sound pressure information, and the initial basis coefficient information corresponding to the sound field basis information; updating the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information.

[0007] In conjunction with the first aspect, in one embodiment of this application, updating the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information includes: dividing the initial basis coefficient information into first amplitude information and second amplitude information based on the trigonometric function signal model form corresponding to the corresponding frequency; updating the first amplitude information and second amplitude information respectively based on the initial estimation error information to obtain the updated basis coefficient information; obtaining the updated estimation error information based on the sound field basis information, sound pressure information and the updated basis coefficient information corresponding to multiple observation points; and determining the updated basis coefficient information as the basis coefficient information corresponding to the sound field basis information when the updated estimation error information meets the preset optimal conditions.

[0008] In conjunction with the first aspect, in one embodiment of this application, updating the first amplitude information and the second amplitude information based on the initial estimation error information to obtain the updated basis coefficient information includes: performing cyclic iterations on the first amplitude information and the second amplitude information based on the initial estimation error information to determine the Nth iteration result and the N+1th iteration result corresponding to the first amplitude information and the second amplitude information respectively, where N≥1; and obtaining the updated basis coefficient information based on the Nth iteration result and the N+1th iteration result corresponding to the first amplitude information and the second amplitude information respectively.

[0009] In conjunction with the first aspect, in one embodiment of this application, the first amplitude information and the second amplitude information are iteratively processed based on the initial estimation error information, including: determining the objective function information corresponding to the initial estimation error information based on the initial estimation error information; determining the adaptive iteration information corresponding to the first amplitude information and the second amplitude information based on the objective function information; and iteratively processing the first amplitude information and the second amplitude information based on the initial estimation error information, the objective function information, and the adaptive iteration information.

[0010] Secondly, an embodiment of this application also provides an active noise reduction method, the method comprising: determining sub-sound field information corresponding to a target noise reduction frequency in a sound field, wherein the sub-sound field information is determined using the sound field holography method mentioned in the first aspect; and performing active noise reduction on the sound signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

[0011] Thirdly, one embodiment of this application also provides a sound field holographic device, which includes: a first determining module for determining sound pressure information corresponding to each of multiple observation points in the sound field; a second determining module for determining the fundamental coefficient information corresponding to the sound field fundamental information based on the sound field fundamental information and sound pressure information corresponding to each of the multiple observation points; and a third determining module for determining the sub-sound field information of the corresponding frequency of the sound field based on the fundamental coefficient information.

[0012] Fourthly, an embodiment of this application also provides an active noise reduction device, which includes: a sub-sound field information determination module, used to determine sub-sound field information corresponding to a target noise reduction frequency in a sound field, wherein the sub-sound field information is determined using the sound field holographic method mentioned in the first aspect; and a noise reduction module, used to actively reduce noise on the sound signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

[0013] Fifthly, an embodiment of this application also provides an electronic device, including: a processor; and a memory storing computer program instructions, which, when executed by the processor, cause the processor to perform the methods mentioned in the first and / or second aspects above.

[0014] In a sixth aspect, one embodiment of this application also provides a computer-readable storage medium storing computer program instructions that, when executed by a processor, cause the processor to perform the methods mentioned in the first and / or second aspects above.

[0015] The sound field holography method and apparatus, and the active noise reduction method and apparatus provided in this application, achieve the purpose of determining the sub-sound field information of each corresponding frequency based on the basis coefficient information by determining the sound pressure information corresponding to each of the multiple observation points in the sound field, and determining the basis coefficient information corresponding to the sound field basis information based on the sound field basis information and sound pressure information corresponding to each of the multiple observation points. For any space, its sound field can be decomposed into multiple sub-sound field components according to frequency, and the superposition of multiple sub-sound field information is the overall sound field information. That is to say, the embodiments of this application can holographically represent the global sound field information in real time, rather than just the local sound field information collected by a limited number of microphones. It can be seen that the embodiments of this application provide a data foundation for achieving global minimization of narrow-frequency noise energy in the entire spatial sound field. Furthermore, the embodiments of this application do not require Fourier transform of the sound signals collected by the microphones at the observation points, have no statistical time delay, and can track the amplitude fluctuations of narrow-frequency signals in real time, thereby better meeting the real-time requirements of active noise reduction. Attached Figure Description

[0016] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0017] Figure 1 The diagram shown is a schematic flowchart of a sound field holography method provided in an embodiment of this application.

[0018] Figure 2The diagram shown is a flowchart of a sound field holography method provided in another embodiment of this application.

[0019] Figure 3 The diagram shown is a schematic representation of a process provided in this application to update the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information.

[0020] Figure 4 The diagram shown is a schematic diagram of the principle of the sound field holography method provided in another embodiment of this application.

[0021] Figure 5 The diagram shown is a flowchart illustrating the process of updating the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information, according to another embodiment of this application.

[0022] Figure 6 The diagram shown is a flowchart illustrating the process of iteratively performing first amplitude information and second amplitude information based on initial estimation error information according to an embodiment of this application.

[0023] Figure 7 The diagram shown is a flowchart of an active noise reduction method provided in an embodiment of this application.

[0024] Figure 8 The diagram shown is a structural schematic of a sound field holographic device provided in an embodiment of this application.

[0025] Figure 9 The diagram shown is a structural schematic of the second determining module provided in an embodiment of this application.

[0026] Figure 10 The diagram shown is a structural schematic of a base coefficient information determination unit provided in an embodiment of this application.

[0027] Figure 11 The diagram shown is a structural schematic of the second determining subunit provided in an embodiment of this application.

[0028] Figure 12 The diagram shown is a structural schematic of the fifth determining subunit provided in an embodiment of this application.

[0029] Figure 13 The diagram shown is a structural schematic of an active noise reduction device provided in an embodiment of this application.

[0030] Figure 14 The diagram shown is a structural schematic of an electronic device provided in an embodiment of this application. Detailed Implementation

[0031] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0032] Figure 1 The diagram shows a schematic flowchart of a sound field holography method provided in an embodiment of this application. Exemplarily, the sound field holography method provided in this embodiment can be applied to a sound field including narrowband sound signals. For example, when a hair dryer operates at a single speed, the fan rotates at the same rotation speed, and the noise emitted by the hair dryer contains significant narrowband noise signals. Similarly, the noise generated by a computer fan at a stable speed also contains narrowband noise signals. The same applies to engine noise in a car cabin. Based on this, the sound field holography method provided in this embodiment is used to determine sub-sound field information of corresponding frequencies in a sound field.

[0033] Specifically, such as Figure 1 As shown, the sound field holography method provided in this application includes the following steps.

[0034] Step 10: Determine the sound pressure information corresponding to each of the multiple observation points in the sound field.

[0035] For example, the sound field mentioned in step S10 includes a narrowband signal (narrowband noise signal). The specific frequency and / or frequency band of the narrowband can be determined according to the actual situation of the spatial sound field noise source, and this application embodiment does not impose a uniform limitation on this.

[0036] Specifically, each observation point may be equipped with at least one microphone to collect sound pressure information corresponding to that observation point at multiple different times based on the at least one microphone.

[0037] It should be understood that multiple microphones can be arranged in a square array, a ring array, or a non-uniform distribution, etc. The embodiments of this application do not limit the distribution method of multiple microphones.

[0038] Step 20: Based on the acoustic field basis information and sound pressure information corresponding to each of the multiple observation points, determine the basis coefficient information corresponding to the acoustic field basis information.

[0039] For example, the acoustic field basis information mentioned in step 20 is a acoustic field basis matrix predetermined based on the three-dimensional wave equation and the actual situation of the acoustic field boundary. By determining the basis coefficient information corresponding to the acoustic field basis information in real time, the distribution of the corresponding frequency signal in the acoustic field can be accurately characterized, thereby determining the sub-acoustic field information of the corresponding frequency.

[0040] Step 30: Based on the fundamental coefficient information, determine the sub-sound field information of the corresponding frequency of the sound field.

[0041] In some embodiments, the sub-sound field information of the corresponding frequency mentioned in step S30 refers to the sub-sound field information of each narrow frequency present in the sound field decomposed by frequency. That is, based on the sound pressure information corresponding to multiple observation points in the sound field, the embodiments of this application finally determine the sub-sound field information of the narrow frequencies, and the sub-sound field information of each narrow frequency is superimposed to obtain the overall information of the narrow frequencies present in the sound field.

[0042] For example, the sound field includes L observation points. For each observation point in the three-dimensional sound field, the result can be calculated using the following formula (1).

[0043]

[0044] In formula (1), p(n) is the instantaneous sound pressure value collected by the microphone at the observation point, and n is a discrete time point. This is the m-th order acoustic field basis at the observation point. c is the basis (row) vector of the sound field at this observation point. m (n) represents the basis coefficients corresponding to the m-th order sound field basis at this observation point. The basis coefficient (column) vector characterizing the spatial sound field. All parameters are real values.

[0045] Extending formula (1) to L observation points in a three-dimensional sound field, we can obtain the following formula (2).

[0046]

[0047] In formula (2), [ψ(n)] is the acoustic field basis matrix established for the L observation points. Based on formula (2), the following formula (3) can be obtained.

[0048]

[0049] In formula (3), M represents the total dimension of the spatial sound field information. One of the purposes of the sound field holography method in this application is to construct the overall sound field information with as few microphones as possible. Therefore, in the embodiments of this application, L < <M。

[0050] For example, in practical applications, the sound pressure information corresponding to each of the multiple observation points in the sound field is first determined. Then, based on the sound field basis information and sound pressure information corresponding to each of the multiple observation points, the basis coefficient information corresponding to the sound field basis information is determined. Finally, based on the basis coefficient information, the sub-sound field information of the corresponding frequency of the sound field is determined.

[0051] The sound field holography method provided in this application achieves the goal of accurately characterizing the distribution of corresponding frequency signals in the sound field in real time by determining the fundamental coefficient information in real time, thereby determining the sub-sound field information of each corresponding frequency. In other words, this application embodiment can holographically represent the global sound field information in real time, rather than just the local sound field information collected by a limited number of microphones. Therefore, this application embodiment provides a data foundation for achieving global minimization of narrowband noise energy in the entire spatial sound field. Furthermore, this application embodiment does not require Fourier transform of the sound signals collected by the microphones at the observation point, has no statistical delay, and can track the amplitude fluctuations of narrowband signals in real time, thus better meeting the real-time requirements of active noise reduction.

[0052] Figure 2 The diagram shown is a schematic flowchart of a sound field holography method provided in another embodiment of this application. Figure 1 Extending from the illustrated embodiment Figure 2 The illustrated embodiment will be described in detail below. Figure 2 The illustrated embodiments and Figure 1 The differences between the embodiments shown are not repeated here, and the similarities are not repeated here.

[0053] like Figure 2 As shown, in the sound field holography method provided in this application embodiment, the basis coefficient information corresponding to the sound field basis information is determined based on the sound field basis information and sound pressure information corresponding to multiple observation points (step 20), including the following steps.

[0054] Step 200: Based on the acoustic field basis information, sound pressure information and initial basis coefficient information corresponding to the acoustic field basis information of each of the multiple observation points, determine the initial estimation error information corresponding to the multiple observation points.

[0055] For example, the initial basis coefficient information mentioned in step 200 is an initial basis coefficient vector.

[0056] It should be understood that the initial basis coefficients can be set to a zero vector or other vectors. This application does not specifically limit this.

[0057] For example, the initial estimation error information mentioned in step 200 can be in vector form to characterize the errors corresponding to multiple microphones in the sound field.

[0058] Step 201: Update the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information.

[0059] Specifically, the initial basis coefficient information is updated based on the initial estimation error information to obtain the adjusted basis coefficient information, and the estimation error information is recalculated using the adjusted basis coefficient information. When the estimation error information meets the preset optimal conditions, the basis coefficient information corresponding to the sound field basis information is determined as the updated basis coefficients of the spatial sound field.

[0060] The process of repeatedly adjusting the base coefficient information and recalculating the estimation error information can be implemented based on an adaptive algorithm, such as the Least Mean Square (LMS) algorithm, updating each time until the estimation error information reaches its optimal value. It should be understood that the embodiments of this application do not limit the actual algorithm used.

[0061] The sound field holography method provided in this application determines the initial estimation error information corresponding to multiple observation points based on the sound field basis information, sound pressure information, and initial basis coefficient information corresponding to the sound field basis information. Then, it updates the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information. By constructing the initial estimation error information and updating the basis coefficient information in real time, the basis coefficient information corresponding to the sound field basis information is determined when the estimation error information meets a preset optimal condition, thereby further achieving the purpose of determining the sub-sound field information for each corresponding frequency. Furthermore, the real-time calculation method ensures the real-time nature of constructing the sub-sound field information.

[0062] Figure 3 The diagram shown is a schematic representation of a process provided in this application to update the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information. Figure 4 The diagram shown is a schematic representation of the sound field holography method provided in an embodiment of this application. Figure 2 Extending from the illustrated embodiment Figure 3 The illustrated embodiment will be described in detail below. Figure 3 The illustrated embodiments and Figure 2 The differences between the embodiments shown are not repeated here, and the similarities are not repeated here.

[0063] like Figure 3 As shown, in the sound field holography method provided in this application embodiment, the initial basis coefficient information is updated based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information (step 201), which includes the following steps.

[0064] Step 221: Based on the trigonometric function signal model form corresponding to the corresponding frequency, the initial basis coefficient information is divided into first amplitude information and second amplitude information.

[0065] For example, in the real number domain, the trigonometric function signal model corresponding to the corresponding frequency can be represented by the following expression (4). It should be noted that, compared with the standard sinusoidal signal in theory, the amplitude of the sound signal of the corresponding frequency emitted by the noise source in reality cannot be a constant value, but is a variable that fluctuates randomly around a certain value.

[0066] For example, in a sound field that includes narrowband sound signals, the narrowband signal model can be determined based on the following formula (4).

[0067] f(t)=a(t)cos2πf0t+b(t)sin2πf0t (4)

[0068] In formula (4), f0 represents the signal frequency (such as the center frequency of a narrowband signal).

[0069] The initial basis coefficients are also determined based on the following formula (5).

[0070]

[0071] Where cos2πf0n and sin2πf0n are the reference cosine and reference sine signals, respectively, and n is a discrete time point. From the above, it can be seen that the basis coefficient vector... It can be broken down into and Two parts.

[0072] Step 222: Update the first amplitude information and the second amplitude information based on the initial estimation error information to obtain the updated basic coefficient information.

[0073] Step 223: Based on the acoustic field basis information, sound pressure information and updated basis coefficient information corresponding to each of the multiple observation points, the updated estimation error information is obtained.

[0074] Step 224: When the updated estimation error information meets the preset optimal conditions, the updated basis coefficient information is determined to be the basis coefficient information corresponding to the sound field basis information.

[0075] For example, such as Figure 4 As shown, the first amplitude information is obtained by using the initial estimation error information. Second amplitude information Perform adaptive estimation separately, and update the first amplitude information. Second amplitude information The updated base coefficient information is obtained by merging. Updated base coefficient information With sound field fundamental information The sound pressure information p(n) is used to perform calculations to obtain the updated estimation error information. Updated estimation error information As feedback, the first amplitude information is then further updated. Second amplitude information Through continuous iterative iterations, the updated estimation error information continues until it meets the preset optimal conditions, i.e., the estimation error information is considered optimal. The square of the modulus eventually converges to a minimum value, and the convergent values ​​are obtained respectively. and Merging convergent and The updated fundamental coefficient information is confirmed to be the fundamental coefficient information corresponding to the sound field fundamental information.

[0076] The sound field holography method provided in this application, based on the trigonometric function signal model form corresponding to the frequency, divides the initial fundamental coefficient information into first amplitude information and second amplitude information. Then, based on the initial estimation error information, the first amplitude information and second amplitude information are updated respectively to obtain updated fundamental coefficient information. Based on the sound field fundamental information, sound pressure information, and updated fundamental coefficient information corresponding to multiple observation points, updated estimation error information is obtained. When the updated estimation error information meets a preset optimal condition, the updated fundamental coefficient information is determined to be the fundamental coefficient information corresponding to the sound field fundamental information. By adopting a real-time calculation and iterative update method, the fundamental coefficient information corresponding to the sound field fundamental information can be determined without performing Fourier transform on the sound signals collected by the microphone at the observation point, thus better meeting the real-time requirements of noise reduction.

[0077] Figure 5 The diagram shown is a schematic representation of a process for updating initial basis coefficient information based on initial estimation error information to obtain basis coefficient information corresponding to sound field basis information, according to another embodiment of this application. Figure 3 Extending from the illustrated embodiment Figure 5 The illustrated embodiment will be described in detail below. Figure 5 The illustrated embodiments and Figure 3 The differences between the embodiments shown are not repeated here, and the similarities are not repeated here.

[0078] like Figure 5 As shown, in the sound field holography method provided in this application embodiment, the first amplitude information and the second amplitude information are updated based on the initial estimation error information to obtain the updated basis coefficient information (step 222), including:

[0079] Step 231: Based on the initial estimation error information, perform cyclic iterations on the first amplitude information and the second amplitude information respectively to determine the Nth iteration result and the N+1th iteration result corresponding to the first amplitude information and the second amplitude information respectively, where N≥1.

[0080] Specifically, such as Figure 4 In the algorithm framework shown, the basis coefficient information Divided into the first amplitude information Second amplitude information The algorithm performs calculations on two paths. A reference signal is input to the left side of the algorithm framework, and the first amplitude information is adjusted based on the initial estimation error. Perform a loop iteration, where z -1 It's a delay module; the difference between the results of two iterations is equal to... Similarly, the second amplitude information The difference between the results of the two iterations is equal to

[0081] Step 232: Based on the Nth iteration result and the N+1th iteration result corresponding to the first amplitude information and the second amplitude information, the updated basic coefficient information is obtained.

[0082] like Figure 4 As shown, the adaptive algorithm is essentially based on the estimation error information. Real-time calculation of first amplitude information Second amplitude information Based on the first amplitude information Second amplitude information The updated base coefficient information is obtained by taking the corresponding Nth iteration result and the N+1th iteration result. When the base coefficient information The convolution of the sound field basis matrix [ψ(n)] gradually converges to the actual measured sound pressure information. Estimation error information Approaching The updated basis coefficient information is determined to be the basis coefficient information corresponding to the sound field basis information.

[0083] The sound field holography method provided in this application iteratively estimates the first and second amplitude information using initial estimation error information. This determines the Nth and N+1th iteration results for each amplitude information, respectively. Then, based on these Nth and N+1th iteration results, updated basis coefficient information is obtained. By splitting the amplitude information into two separate iterations, effective basis coefficient information can be determined in real time, resulting in better real-time performance and better meeting the real-time requirements of noise reduction.

[0084] Figure 6 The diagram shown is a schematic representation of a process provided in an embodiment of this application, which iteratively processes the first amplitude information and the second amplitude information based on initial estimation error information. Figure 5 Extending from the illustrated embodiment Figure 6The illustrated embodiment will be described in detail below. Figure 6 The illustrated embodiments and Figure 5 The differences between the embodiments shown are not repeated here, and the similarities are not repeated here.

[0085] like Figure 6 As shown, in the sound field holography method provided in this application embodiment, the first amplitude information and the second amplitude information are iteratively performed based on the initial estimation error information (step 231), including the following steps.

[0086] Step 241: Based on the initial estimation error information, determine the objective function information corresponding to the initial estimation error information.

[0087] For example, the objective function information can be the objective function of an adaptive algorithm. The objective function can be determined according to the following formula (6). It should be understood that the objective function is not unique, but this form is usually chosen.

[0088]

[0089] Step 242: Based on the objective function information, determine the adaptive iterative information corresponding to the first amplitude information and the second amplitude information.

[0090] Based on the objective function in the above formula (6), the adaptive iterative formulas corresponding to the first amplitude information and the second amplitude information can be expressed as the following formula (7) and the following formula (8).

[0091]

[0092]

[0093] The estimation error information is the error obtained by adaptively estimating the basic coefficient information at each step. The estimation error information can be determined according to the following formula (9).

[0094]

[0095] The base coefficient information in the above formula (5) Substituting into the above formula (9), we can obtain the following formula (10).

[0096]

[0097] Substituting the above formulas (6) and (10) into formula (7), we can obtain the following formula (11).

[0098]

[0099] Substituting the above formulas (6) and (10) into formula (8), we can obtain the following formula (12).

[0100]

[0101] Step 243: Based on the initial estimation error information, objective function information, and adaptive iteration information, the first amplitude information and the second amplitude information are iterated cyclically respectively.

[0102] Based on the initial estimation error information, objective function information, and adaptive iteration information, the first magnitude information and the second magnitude information are iteratively estimated to obtain the error vector corresponding to the estimation error information. The square of the modulus eventually converges to a minimum value, and the convergent values ​​are obtained respectively. and Thus, the basis coefficient vector is obtained.

[0103]

[0104] The sound field holography method provided in this application first determines the target function information corresponding to the initial estimation error information based on the initial estimation error information; then, based on the target function information, it determines the adaptive iteration information corresponding to the first amplitude information and the second amplitude information; finally, iterates the first amplitude information and the second amplitude information cyclically based on the initial estimation error information, the target function information, and the adaptive iteration information. By introducing the target function information and combining it with the adaptive iteration information and the initial estimation error information, the first amplitude information and the second amplitude information are iterated continuously to obtain converged first amplitude information and second amplitude information, thereby determining effective basis coefficient information. Furthermore, it offers better real-time performance, which is more conducive to meeting the real-time requirements of active noise reduction.

[0105] Figure 7 The diagram shown is a flowchart of an active noise reduction method provided in an embodiment of this application. Figure 7 As shown, one embodiment of this application also provides an active noise reduction method, including the following steps.

[0106] Step 40: Determine the sub-sound field information corresponding to the target noise reduction frequency in the sound field, wherein the sub-sound field information is determined using the sound field holographic method mentioned in any of the above embodiments.

[0107] Step 50: Actively denoise the acoustic signal of the target denoising frequency in the sound field based on the sub-sound field information.

[0108] The active noise reduction method provided in this application can track the amplitude fluctuation of the acoustic signal corresponding to the target noise reduction frequency in real time, thereby achieving the purpose of actively denoising the acoustic signal of the target noise reduction frequency in the sound field based on the noise reduction wave of the target noise reduction frequency output by the active noise reduction system. In other words, the active noise reduction method provided in this application can not only achieve accurate global noise reduction of the spatial sound field with as few microphone arrays as possible, but also greatly meet the real-time requirements of active noise reduction.

[0109] The above text combined Figures 1 to 7 The method embodiments of this application are described in detail below, in conjunction with... Figures 8 to 14 The present application provides a detailed description of the apparatus embodiments. It should be understood that the descriptions of the method embodiments correspond to the descriptions of the apparatus embodiments; therefore, any parts not described in detail can be found in the foregoing method embodiments.

[0110] Figure 8 The diagram shown is a structural schematic of a sound field holographic device provided in an embodiment of this application. Figure 8 As shown, one embodiment of this application also provides a sound field holographic device, which includes a first determining module 100, a second determining module 200 and a third determining module 300.

[0111] The first determining module 100 is configured to determine the sound pressure information corresponding to each of the multiple observation points in the sound field. The second determining module 200 is configured to determine the fundamental coefficient information corresponding to the sound field fundamental information based on the sound field fundamental information and sound pressure information corresponding to each of the multiple observation points. The third determining module 300 is configured to determine the sub-sound field information of the corresponding frequency of the sound field based on the fundamental coefficient information.

[0112] Figure 9 The diagram shown is a structural schematic of the second determining module provided in an embodiment of this application. Figure 9 As shown, in the sound field holographic device provided in this application embodiment, the second determining module 200 includes an initial estimation error information determining unit 2000 and a basic coefficient information determining unit 2001.

[0113] The initial estimation error information determination unit 2000 is configured to determine the initial estimation error information corresponding to multiple observation points based on the sound field basis information, sound pressure information, and initial basis coefficient information corresponding to the sound field basis information. The basis coefficient information determination unit 2001 is configured to update the initial basis coefficient information based on the initial estimation error information to obtain the basis coefficient information corresponding to the sound field basis information.

[0114] Figure 10 The diagram shown is a structural schematic of a basic coefficient information determination unit provided in an embodiment of this application. Figure 10As shown, in the sound field holographic device provided in this application embodiment, the basic coefficient information determination unit 2001 includes a first determination subunit 2221, a second determination subunit 2222, a third determination subunit 2223, and a fourth determination subunit 2224.

[0115] The first determining subunit 2221 is configured to divide the initial basis coefficient information into first amplitude information and second amplitude information based on the trigonometric function signal model form corresponding to the corresponding frequency. The second determining subunit 2222 is configured to update the first amplitude information and second amplitude information respectively based on the initial estimation error information to obtain the updated basis coefficient information. The third determining subunit 2223 is configured to obtain the updated estimation error information based on the sound field basis information, sound pressure information, and the updated basis coefficient information corresponding to multiple observation points. The fourth determining subunit 2224 is configured to determine the updated basis coefficient information as the basis coefficient information corresponding to the sound field basis information when the updated estimation error information meets the preset optimal conditions.

[0116] Figure 11 The diagram shown is a structural schematic of the second defined subunit provided in an embodiment of this application. Figure 11 As shown, in the sound field holographic device provided in this application embodiment, the second determining subunit 2222 includes a fifth determining subunit 2231 and a sixth determining subunit 2232.

[0117] The fifth determining subunit 2231 is configured to iterate the first amplitude information and the second amplitude information respectively based on the initial estimation error information to determine the Nth iteration result and the (N+1)th iteration result corresponding to the first amplitude information and the second amplitude information, where N≥1. The sixth determining subunit 2232 is configured to obtain the updated base coefficient information based on the Nth iteration result and the (N+1)th iteration result corresponding to the first amplitude information and the second amplitude information.

[0118] Figure 12 The diagram shown is a structural schematic of the fifth determining subunit provided in an embodiment of this application. Figure 12 As shown, in the sound field holographic device provided in this application embodiment, the fifth determining subunit 2231 includes an objective function information determining subunit 2241, an adaptive iteration information determining subunit 2242, and a cyclic iteration subunit 2243.

[0119] The objective function information determination subunit 2241 is configured to determine the objective function information corresponding to the initial estimation error information based on the initial estimation error information. The adaptive iteration information determination subunit 2242 is configured to determine the adaptive iteration information corresponding to the first amplitude information and the second amplitude information based on the objective function information. The cyclic iteration subunit 2243 is configured to perform cyclic iteration on the first amplitude information and the second amplitude information respectively based on the initial estimation error information, the objective function information, and the adaptive iteration information.

[0120] Figure 13 The diagram shown is a structural schematic of an active noise cancellation device provided in an embodiment of this application. Figure 13 As shown, one embodiment of this application also provides an active noise reduction device, which includes a sub-sound field information determination module 400 and a noise reduction module 500.

[0121] The sub-sound field information determination module 400 is configured to determine the sub-sound field information corresponding to the target noise reduction frequency in the sound field, wherein the sub-sound field information is determined using the sound field holography method mentioned in any of the above embodiments. The noise reduction module 500 is configured to perform active noise reduction on the acoustic signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

[0122] Figure 14 The diagram shown is a structural schematic of an electronic device provided in an embodiment of this application. Figure 14 As shown, one embodiment of this application also provides an electronic device 1000, including: a processor 1004; and a memory 1005, in which computer program instructions are stored. When the computer program instructions are executed by the processor 1004, the processor 1004 performs the sound field holography method and / or active noise reduction method mentioned in the above embodiments.

[0123] The processor 1004 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 1000 to perform desired functions.

[0124] The memory 1005 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 1004 may execute the program instructions to implement the functions of the sound field holography method and / or active noise reduction method mentioned in the above embodiments of this application. Various contents, such as sound pressure information corresponding to multiple observation points, may also be stored in the computer-readable storage medium.

[0125] In one example, the electronic device 1000 may also include an input device 1006 and an output device 1007, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0126] The input device 1006 may include, for example, a keyboard, a mouse, a microphone, etc.

[0127] The output device 1007 can output various information to the outside, including sub-sound field information. The output device 1007 may include, for example, a display, a communication network, a speaker, and a remote output device connected thereto.

[0128] Of course, for the sake of simplicity, Figure 14 Only some of the components of the electronic device 1000 relevant to this application are shown in this illustration; components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device 1000 may include any other suitable components depending on the specific application.

[0129] For example, the electronic device 1000 can be at least one of a speaker, headphones, a voice recorder, and a hearing aid.

[0130] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the sound field holographic method and / or active noise reduction method according to various embodiments of this application as described in the "Exemplary Methods" section of this specification.

[0131] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0132] Furthermore, embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps in the sound field holographic method and / or active noise reduction method according to various embodiments of this application as described in the "Exemplary Methods" section of this specification.

[0133] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0134] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the application to the necessity of employing the aforementioned specific details for implementation.

[0135] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0136] It should also be noted that in the apparatus, equipment, and methods of this application, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of this application.

[0137] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0138] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A sound field holography method, characterized in that, include: Determine the sound pressure information corresponding to each of multiple observation points in the sound field, wherein each of the multiple observation points is equipped with at least one microphone to collect the sound pressure information corresponding to the observation point at multiple different times based on the at least one microphone. Based on the acoustic field fundamental information and sound pressure information corresponding to each of the multiple observation points, the fundamental coefficient information corresponding to the acoustic field fundamental information is determined, including: Based on the sound field fundamental information, sound pressure information, and initial basis coefficient information corresponding to the sound field fundamental information at each of the multiple observation points, initial estimation error information corresponding to the multiple observation points is determined; based on the initial estimation error information, the initial basis coefficient information is repeatedly adjusted and the estimation error information is recalculated, updating each time until the estimation error information meets a preset optimal condition, to obtain the basis coefficient information corresponding to the sound field fundamental information, including: Based on the trigonometric function signal model form corresponding to the corresponding frequency, the initial basis coefficient information is divided into first amplitude information and second amplitude information; Based on the initial estimation error information, the first amplitude information and the second amplitude information are updated respectively to obtain the updated basic coefficient information; Based on the acoustic field basis information, sound pressure information, and updated basis coefficient information corresponding to each of the multiple observation points, the updated estimation error information is obtained; When the updated estimation error information meets the preset optimal condition, the updated basis coefficient information is determined to be the basis coefficient information corresponding to the sound field basis information; Based on the fundamental coefficient information, the sub-sound field information of the corresponding frequency of the sound field is determined.

2. The acoustic field holographic method according to claim 1, characterized in that, The step of updating the first amplitude information and the second amplitude information based on the initial estimation error information to obtain the updated base coefficient information includes: Based on the initial estimation error information, the first amplitude information and the second amplitude information are iteratively processed to determine the Nth iteration result and the (N+1)th iteration result corresponding to the first amplitude information and the second amplitude information, respectively, where N≥1; Based on the Nth iteration result and the N+1th iteration result corresponding to the first amplitude information and the second amplitude information, the updated basis coefficient information is obtained.

3. The acoustic field holographic method according to claim 2, characterized in that, The step of iteratively performing the first amplitude information and the second amplitude information based on the initial estimation error information includes: Based on the initial estimation error information, determine the objective function information corresponding to the initial estimation error information; Based on the objective function information, the adaptive iteration information corresponding to the first amplitude information and the second amplitude information is determined; Based on the initial estimation error information, the objective function information, and the adaptive iteration information, the first amplitude information and the second amplitude information are iterated cyclically respectively.

4. An active noise reduction method, characterized in that, include: Determine the sub-sound field information corresponding to the target noise reduction frequency in the sound field, wherein the sub-sound field information is determined using the sound field holography method according to any one of claims 1 to 3; Active noise reduction is performed on the acoustic signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

5. A sound field holographic device, characterized in that, include: The first determining module is used to determine the sound pressure information corresponding to each of the multiple observation points in the sound field. Each of the multiple observation points is equipped with at least one microphone to collect the sound pressure information corresponding to the observation point at multiple different times based on the at least one microphone. The second determining module is used to determine the basis coefficient information corresponding to the sound field basis information based on the sound field basis information and sound pressure information corresponding to each of the plurality of observation points, including: determining the initial estimation error information corresponding to the plurality of observation points based on the sound field basis information, sound pressure information, and the initial basis coefficient information corresponding to the sound field basis information; repeatedly adjusting the initial basis coefficient information and recalculating the estimation error information based on the initial estimation error information, updating each time until the estimation error information meets the preset optimal condition, to obtain the basis coefficient information corresponding to the sound field basis information, including: Based on the trigonometric function signal model form corresponding to the corresponding frequency, the initial basis coefficient information is divided into first amplitude information and second amplitude information; Based on the initial estimation error information, the first amplitude information and the second amplitude information are updated respectively to obtain the updated basic coefficient information; Based on the acoustic field basis information, sound pressure information, and updated basis coefficient information corresponding to each of the multiple observation points, the updated estimation error information is obtained; When the updated estimation error information meets the preset optimal condition, the updated basis coefficient information is determined to be the basis coefficient information corresponding to the sound field basis information; The third determining module is used to determine the sub-sound field information of the corresponding frequency of the sound field based on the basic coefficient information.

6. An active noise reduction device, characterized in that, include: A sub-sound field information determination module is used to determine the sub-sound field information corresponding to the target noise reduction frequency in the sound field, wherein the sub-sound field information is determined using the sound field holography method according to any one of claims 1 to 3; The noise reduction module is used to actively reduce the noise of the acoustic signal at the target noise reduction frequency in the sound field based on the sub-sound field information.

7. An electronic device, comprising: processor; as well as A memory storing computer program instructions that, when executed by the processor, cause the processor to perform the method as described in any one of claims 1 to 4.

8. A computer-readable storage medium storing computer program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1 to 4.

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