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

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal processing, in particular to a sound field holography method and device, and an active noise reduction method and device. BACKGROUND

[0002] In recent years, with the rapid development of intelligent technology, active noise reduction technology has been widely concerned and widely applied in three-dimensional space scenes (such as car cabin scenes). As we all know, the premise of achieving good noise reduction effect is to quickly and accurately determine the specific noise data in the three-dimensional space scene.

[0003] At present, the specific noise data in the three-dimensional space scene is mainly determined based on a spectrum estimation algorithm by relying on a microphone array, and then noise reduction operation is performed based on the specific noise data. However, for a three-dimensional space scene, the cost of the microphone array to be arranged for accurately constructing the overall view of the sound field is extremely high, and more observation points can only represent local information of the sound field. In addition, the spectrum estimation algorithm has a large time delay and cannot track the random fluctuations of the amplitude of each frequency sound signal in real time, which is difficult to meet the real-time noise reduction requirement. SUMMARY

[0004] In order to solve the above technical problems, the present application is proposed. The embodiments of the present application provide a sound field holography method and device, and an active noise reduction method and device.

[0005] In a first aspect, an embodiment of the present application provides a sound field holography method, which comprises: determining a complex sound pressure vector corresponding to a plurality of observation points in a sound field based on sound pressure value information corresponding to each of the plurality of observation points; determining a basis coefficient vector corresponding to a sound field basis vector based on the complex sound pressure vector and the sound field basis vector 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 vector.

[0006] In combination with the first aspect, in some implementations of the first aspect, determining the complex sound pressure vector corresponding to the plurality of observation points based on the sound pressure value information corresponding to each of the plurality of observation points in the sound field comprises: determining a complex number domain signal form of the complex sound pressure vector based on a trigonometric function signal model form corresponding to the corresponding frequency; determining initial real part information and initial imaginary part information corresponding to the complex sound pressure vector based on the complex number domain signal form; and determining the complex sound pressure vector based on the sound pressure value information corresponding to each of the plurality of observation points, the initial real part information and the initial imaginary part information.

[0007] In some implementations of the first aspect, the determining the complex sound pressure error estimation information based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points comprises: determining initial complex sound pressure error estimation information based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points, and an initial basis coefficient vector corresponding to the sound field basis vector; updating the initial basis coefficient vector based on the initial complex sound pressure error estimation information to obtain the complex sound pressure error estimation information.

[0008] In some implementations of the first aspect, the determining the basis coefficient vector corresponding to the sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points comprises: determining initial basis coefficient error estimation information corresponding to the multiple observation points based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points, and the initial basis coefficient vector corresponding to the sound field basis vector; updating the initial basis coefficient vector based on the initial basis coefficient error estimation information to obtain the basis coefficient vector corresponding to the sound field basis vector.

[0009] In some implementations of the first aspect, the updating the initial basis coefficient vector based on the initial basis coefficient error estimation information to obtain the basis coefficient vector corresponding to the sound field basis vector comprises: determining sine amplitude information and cosine amplitude information corresponding to the initial basis coefficient vector based on a trigonometric function signal model form corresponding to a corresponding frequency; updating the sine amplitude information and the cosine amplitude information based on the initial basis coefficient error estimation information to obtain an updated basis coefficient vector; obtaining updated basis coefficient error estimation information based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points, and the updated basis coefficient vector; and determining the updated basis coefficient vector as the basis coefficient vector corresponding to the sound field basis vector when the updated basis coefficient error estimation information satisfies a preset basis coefficient error estimation condition.

[0010] In some implementations of the first aspect, the determining the basis coefficient vector corresponding to the sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points comprises: determining initial basis coefficient error estimation information corresponding to the multiple observation points based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points, and the initial basis coefficient vector corresponding to the sound field basis vector; updating the initial basis coefficient vector based on the initial complex sound pressure error estimation information to obtain the complex sound pressure error estimation information.

[0011] In a third aspect, an embodiment of the present application provides a sound field holographic device, which comprises: a first determining module configured to determine a complex sound pressure vector corresponding to a plurality of observation points in a sound field based on sound pressure value information corresponding to each of the plurality of observation points; a second determining module configured to determine a basis coefficient vector corresponding to a sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points; and a third determining module configured to determine sub-sound field information of a corresponding frequency of the sound field based on the basis coefficient vector.

[0012] In a fourth aspect, an embodiment of the present application provides an active noise reduction device, which comprises: a sub-sound field information determining module configured 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 by using the sound field holographic method mentioned in the first aspect; and a noise reduction module configured to perform active noise reduction on a sound signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

[0013] In a fifth aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is used to execute the method mentioned in the first aspect and / or the second aspect.

[0014] In a sixth aspect, an embodiment of the present application provides an electronic device, which comprises: a processor; a memory configured to store instructions executable by the processor; and the processor configured to execute the method mentioned in the first aspect and / or the second aspect.

[0015] The sound field holographic method provided by the embodiments of the present application realizes real-time and accurate representation of corresponding frequency signals in the sound field by means of the determined basis coefficient vector, so as to determine the sub-sound field information of each corresponding frequency. For any space, the sound field thereof can be decomposed into a plurality of sub-sound field components according to frequency, and the superposition of the plurality of sub-sound field information is the overall sound field information. That is, the embodiments of the present application can realize real-time holographic global sound field information, rather than only local sound field information collected by a limited number of microphones. As can be seen, the embodiments of the present application provide a data basis for realizing global minimization of narrow frequency noise energy of the entire space sound field. Furthermore, the embodiments of the present application do not need to perform Fourier transform on the sound signals collected by the microphones at the observation points, and can track the amplitude fluctuation of the narrow frequency signal in real time without statistical delay, thereby better meeting the real-time requirement of active noise reduction. BRIEF DESCRIPTION OF DRAWINGS

[0016] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description thereof when taken in conjunction with the accompanying drawings in which like reference characters refer to like parts throughout the figures, and which figures are representative of exemplary embodiments of the present application. The accompanying drawings provide illustration of the exemplary embodiments of the present application and constitute a part of the specification, together with the detailed description, to explain the principles of the present application, and the exemplary embodiments of the present application serve to explain the present application, but are not intended to limit the present application. In the drawings, like reference numerals refer to like parts or steps throughout the figures.

[0017] Figure 1 Fig. 1 shows a flowchart of a sound field holography method according to an exemplary embodiment of the present application.

[0018] Figure 2 Fig. 2 shows a flowchart of determining a complex sound pressure vector corresponding to a plurality of observation points based on sound pressure value information corresponding to each of the plurality of observation points in a sound field according to an exemplary embodiment of the present application.

[0019] Figure 3 Fig. 2 shows a flowchart of determining a complex sound pressure vector corresponding to a plurality of observation points based on sound pressure value information corresponding to each of the plurality of observation points in a sound field according to an exemplary embodiment of the present application.

[0020] Figure 4 Fig. 3 shows a schematic diagram of a principle of a sound field holography method according to an exemplary embodiment of the present application.

[0021] Figure 5 Fig. 4 shows a flowchart of determining a basis coefficient vector corresponding to a sound field basis vector based on a complex sound pressure vector and the sound field basis vector corresponding to each of a plurality of observation points according to an exemplary embodiment of the present application.

[0022] Figure 6 Fig. 4 shows a flowchart of determining a basis coefficient vector corresponding to a sound field basis vector based on a complex sound pressure vector and the sound field basis vector corresponding to each of a plurality of observation points according to an exemplary embodiment of the present application.

[0023] Figure 7 Fig. 5 shows a flowchart of an active noise reduction method according to an exemplary embodiment of the present application.

[0024] Figure 8 Fig. 6 shows a schematic diagram of a sound field holography device according to an exemplary embodiment of the present application.

[0025] Figure 9 Fig. 7 shows a schematic diagram of an active noise reduction device according to an exemplary embodiment of the present application.

[0026] Figure 10 Fig. 8 shows a schematic diagram of an electronic device according to an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0028] Figure 1 A flowchart of a sound field holography method provided by an exemplary embodiment of the present application is shown. As shown in the figure, Figure 1 The sound field holography method provided by the embodiment of the present application includes the following steps.

[0029] In step S100, a complex sound pressure vector corresponding to a plurality of observation points is determined based on sound pressure value information corresponding to each of the plurality of observation points in a sound field.

[0030] In some embodiments, the sound field mentioned in step S100 includes a narrow frequency signal (a narrow frequency noise signal). The specific frequency and / or frequency band of the narrow frequency can be determined according to the actual situation of the spatial sound field noise source, and the embodiments of the present application do not make unified limitation.

[0031] Exemplarily, the observation point refers to an observation point for collecting sound signals in a sound field. In order to more accurately collect sound signals, the distribution mode of the plurality of observation points mentioned in step S100 includes but is not limited to square array distribution, ring array distribution and non-uniform distribution, etc., and the embodiments of the present application do not make unified limitation. In addition, it can be understood that each observation point can be provided with at least one microphone, so as to collect sound pressure value information corresponding to the observation point at a plurality of different time instants based on the at least one microphone provided.

[0032] Exemplarily, the sound pressure value information corresponding to the observation point refers to the sound signal information collected by the microphone at the observation point, which is a real value. Correspondingly, the complex sound pressure vector is a complex value. That is, for each observation point, the purpose of performing step S100 is to estimate the complex sound pressure information (including both instantaneous amplitude information and phase information) corresponding to each time instant according to the measured sound pressure value information (only including instantaneous amplitude information).

[0033] In step S200, a basis coefficient vector corresponding to a sound field basis vector is determined based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points.

[0034] The sound field basis vector corresponding to each of the plurality of observation points can be determined in advance according to the three-dimensional wave equation and the actual situation of the sound field boundary, and the embodiments of the present application do not make unified limitation. It should be noted that after the basis coefficient vector is determined, the corresponding frequency signal in the sound field can be accurately characterized by means of the basis coefficient vector, and then the sub-sound field information of the corresponding frequency can be determined.

[0035] For example, the sound field includes L observation points in total, and for each observation point, the following expression (1) can be used to describe it.

[0036]

[0037] In expression (1), p(n) represents the instantaneous complex sound pressure (complex value) of the observation point, and n represents a discrete time point. represents the mth-order sound field basis (complex value) of the observation point, represents the sound field basis (row) vector of the observation point. m represents the basis coefficient (complex value) corresponding to the mth-order sound field basis of the observation point, represents the basis coefficient (column) vector of the spatial sound field.

[0038] Then, for the L observation points included in the sound field, the following expression (2) can be obtained based on expression (1).

[0039]

[0040] In expression (2), [ψ(n)] represents the sound field basis matrix determined based on the L observation points. According to expression (2), the following expression (3) can be obtained.

[0041]

[0042] In expression (3), M represents the total dimension number of the spatial sound field information, and one of the purposes of the sound field holography method of the embodiments of the present application is to construct the sound field panorama information with as few microphones as possible. Therefore, in the embodiments of the present application, L << M, that is, L is much smaller than M.

[0043] In step S300, the sub-sound field information of the corresponding frequency of the sound field is determined based on the basis coefficient vector.

[0044] In some embodiments, the sub-sound field information of the corresponding frequency mentioned in step S300 is the sub-sound field information of each narrow frequency existing in the sound field decomposed by frequency. That is, the embodiments of the present application ultimately determine the sub-sound field information of each narrow frequency based on the sound pressure value information corresponding to each of the multiple observation points in the sound field, and the narrow frequency panorama information existing in the sound field is obtained by superimposing the sub-sound field information of each narrow frequency.

[0045] For example, in actual application, first, the complex sound pressure vector corresponding to the multiple observation points is determined based on the sound pressure value information corresponding to each of the multiple observation points in the sound field, then the basis coefficient vector corresponding to the sound field basis vector is determined based on the complex sound pressure vector and the sound field basis vector corresponding to each of the multiple observation points, and then the sub-sound field information of the corresponding frequency of the sound field is determined based on the basis coefficient vector.

[0046] The sound field holography method provided in this application achieves the goal of accurately representing the corresponding frequency signals in the sound field in real time by determining the basis coefficient vector 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.

[0047] Figure 2 The diagram illustrates a flowchart of an exemplary embodiment of this application, illustrating the process of determining the complex sound pressure vector corresponding to multiple observation points based on their respective sound pressure value information within a sound field. 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.

[0048] like Figure 2 As shown in the embodiments of this application, the step of determining the complex sound pressure vector corresponding to multiple observation points based on the sound pressure value information corresponding to each of the multiple observation points in the sound field includes the following steps.

[0049] Step S110: Based on the trigonometric function signal model form corresponding to the corresponding frequency, determine the complex domain signal form of the complex sound pressure vector.

[0050] In the real number domain, the trigonometric function signal model corresponding to the corresponding frequency can be expressed using the following expression (4) or expression (5). It should be noted that, compared to 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.

[0051] a(t)cos2πf0t+b(t)sin2πf0t(4)

[0052]

[0053] In expressions (4) and (5), f0 represents the signal frequency (e.g., the center frequency of a narrowband signal). p(t) represents the initial phase of the signal, and p(t) represents the amplitude of the signal.

[0054] Therefore, it can be understood that, in the real number domain, the trigonometric function signal model corresponding to the respective frequency can be expressed by the following expression (6) based on expression (4).

[0055] p r (n)=q r (n)cos2πf0n+q i (n)sin2πf0n (6)

[0056] In addition, it can be understood that, in the complex number domain, the trigonometric function signal model corresponding to the respective frequency can be expressed by the following expression (7) based on expression (5).

[0057]

[0058] It can be understood that the expressions (6) and (7) are essentially the same. Then, it can be known from expressions (6) and (7) that the sound pressure value vector actually measured by the plurality of observation points The corresponding complex sound pressure vector can be expressed in the form of .

[0059] In step S120, the initial real part information and the initial imaginary part information corresponding to the complex sound pressure vector are determined based on the complex number domain signal form.

[0060] For example, if the complex sound pressure vector is expressed in the form of , then the real part information corresponding to the complex sound pressure vector can be represented by , and the imaginary part information corresponding to the complex sound pressure vector can be represented by . In addition, it should be noted that the specific values of the initial real part information and the initial imaginary part information can be determined according to actual conditions, and the embodiments of the present application do not make unified limitations thereon. For example, the initial real part information and the initial imaginary part information are both zero vectors.

[0061] In step S130, the complex sound pressure vector is determined based on the sound pressure value information corresponding to each of the plurality of observation points, the initial real part information, and the initial imaginary part information.

[0062] For example, based on the sound pressure value information corresponding to each of the plurality of observation points, the initial real part information, and the initial imaginary part information, the actual real part information and the actual imaginary part information are estimated, and then the complex sound pressure vector is determined.

[0063] The sound field holography method provided in this application determines the complex domain signal form of the complex sound pressure vector based on the trigonometric function signal model corresponding to the frequency. Based on the complex domain signal form, it determines the initial real and imaginary parts of the complex sound pressure vector. Then, based on the sound pressure value information, initial real and imaginary parts of multiple observation points, it determines the complex sound pressure vector. This achieves the goal of determining the complex sound pressure vector corresponding to multiple observation points based on their respective sound pressure values. Therefore, this application embodiment can determine the complex sound pressure vector without performing a Fourier transform on the sound signal collected by the microphone at the observation point, exhibiting good real-time performance and better meeting the real-time requirements of noise reduction.

[0064] Figure 3 The diagram illustrates a flowchart of an exemplary embodiment of this application, illustrating the process of determining the complex sound pressure vector corresponding to multiple observation points based on their respective sound pressure value information within a sound field. 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.

[0065] like Figure 3 As shown in the embodiments of this application, the step of determining the complex sound pressure vector based on the sound pressure value information, initial real part information and initial imaginary part information corresponding to multiple observation points includes the following steps.

[0066] Step S131: Based on the sound pressure value information, initial real part information and initial imaginary part information corresponding to each of the multiple observation points, determine the initial complex sound pressure error estimation information corresponding to the complex sound pressure vector.

[0067] For example, the complex sound pressure error estimation information corresponding to the complex sound pressure vector can be described using the following expression (8).

[0068]

[0069] In expression (8), cos2πf0n and sin2πf0n are the reference cosine signal and the reference sine signal, respectively. Correspondingly, the initial basis coefficient error estimation information for multiple observation points can be determined based on expression (8) according to the actual situation. This application does not impose a uniform limitation on this.

[0070] Step S132: Update the initial real part information and the initial imaginary part information based on the initial complex sound pressure error estimation information to obtain the updated real part information and imaginary part information.

[0071] Exemplarily, based on the above expression (8), a target function corresponding to the complex sound pressure error estimation information is determined, and then the initial real part information and the initial imaginary part information are updated by adaptive iterative calculation based on the determined target function, to obtain updated real part information and imaginary part information.

[0072] In some embodiments, the target function corresponding to the complex sound pressure error estimation information can be represented by the following expression (9).

[0073]

[0074] The following iterative expressions (10) and (11) can be obtained.

[0075]

[0076]

[0077] Based on the above expressions (8) and (9) and the iterative expressions (10) and (11), the following expressions (12) and (13) can be obtained, respectively.

[0078]

[0079]

[0080] In step S133, updated complex sound pressure error estimation information is obtained based on the updated real part information and the updated imaginary part information.

[0081] As can be known from the above description, the updated complex sound pressure error estimation information can be obtained based on the updated real part information and the updated imaginary part information.

[0082] In step S134, it is determined whether the updated complex sound pressure error estimation information satisfies a preset complex sound pressure error estimation condition.

[0083] It can be understood that the preset complex sound pressure error estimation condition can be determined according to actual conditions, and the embodiments of the present application do not make unified limitation thereto.

[0084] Exemplarily, if the determination result is yes, that is, the updated complex sound pressure error estimation information satisfies the preset complex sound pressure error estimation condition, step S135 can be executed. If the determination result is no, that is, the updated complex sound pressure error estimation information does not satisfy the preset complex sound pressure error estimation condition, step S132 can be continuously executed, that is, the iterative calculation is continuously performed until the updated complex sound pressure error estimation information satisfies the preset complex sound pressure error estimation condition.

[0085] In step S135, a complex sound pressure vector is determined based on the updated real part information and the updated imaginary part information.

[0086] That is, the sound field holography method provided by the embodiments of the present application achieves the purpose of determining the complex sound pressure vector based on the adaptive iterative updating manner. Specifically, the embodiments of the present application can calculate the complex sound pressure vector with higher accuracy and better real-time performance, thereby being more helpful to meet the real-time requirement of active noise reduction.

[0087] The principles of the method of the embodiments of the present application will be described below in conjunction with Figure 4 Further examples will be described below in conjunction with Figure 3 The principles of the method of the embodiments of the present application will be described below in conjunction with

[0088] Figure 4 The principles of the sound field holography method provided by an exemplary embodiment of the present application are shown in FIG. 2. As shown in FIG. 2, the sound field holography method provided by the embodiments of the present application can be used to determine the complex sound pressure vector based on the adaptive iterative updating manner. Figure 4 As shown in FIG. 2, The error obtained by the adaptive estimation of each iteration step can be represented by the following expression (3). And The error obtained by the adaptive estimation of each iteration step can be represented by the following expression (3). The error obtained by the adaptive estimation of each iteration step can be represented by the following expression (3). The error obtained by the adaptive estimation of each iteration step can be represented by the following expression (3). The specific calculation manner of the error obtained by the adaptive estimation of each iteration step can refer to the embodiments shown in FIG. 3 and FIG. 4. Figure 5 And Figure 6 The specific calculation manner of the error obtained by the adaptive estimation of each iteration step can refer to the embodiments shown in FIG. 3 and FIG. 4.

[0089] Figure 5 The flowchart of determining the basis coefficient vector corresponding to the sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points is shown in FIG. 5. The embodiments shown in FIG. 5 extend the embodiments shown in FIG. 4. Figure 1 The embodiments shown in FIG. 5 extend the embodiments shown in FIG. 4. Figure 5 The differences between the embodiments shown in FIG. 5 and FIG. 4 will be described below, and the same parts will not be described again. Figure 5 The differences between the embodiments shown in FIG. 5 and FIG. 4 will be described below, and the same parts will not be described again. Figure 1 The differences between the embodiments shown in FIG. 5 and FIG. 4 will be described below, and the same parts will not be described again.

[0090] As shown in FIG. 5, in the embodiments of the present application, the step of determining the basis coefficient vector corresponding to the sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points includes the following steps. Figure 5 Step S210, based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points, and the initial basis coefficient vector corresponding to the sound field basis vector, determine the initial basis coefficient error estimation information corresponding to the plurality of observation points.

[0091] Exemplarily, the basis coefficient error estimation information corresponding to the plurality of observation points can be described by the following expression (14).

[0092]

[0093]

[0094] ​Correspondingly, the initial base coefficient error estimation information corresponding to multiple observation points can be determined based on the actual situation according to the expression (14), and this application embodiment does not impose a uniform limitation on this.

[0095] Step S220: Update the initial basis coefficient vector based on the initial basis coefficient error estimation information to obtain the basis coefficient vector corresponding to the sound field basis vector.

[0096] For example, the initial basis coefficient vector is updated based on the initial basis coefficient error estimation information, and the actual basis coefficient vector (i.e. the basis coefficient vector corresponding to the sound field basis vector) is estimated.

[0097] For example, in practical applications, the initial basis coefficient vector is updated based on the initial basis coefficient error estimation information to obtain the updated basis coefficient vector, and the basis coefficient error estimation information is calculated again based on the updated basis coefficient vector. This iterative calculation continues until the basis coefficient error estimation information meets the preset optimal conditions, at which point the updated basis coefficient vector is used as the basis coefficient vector corresponding to the sound field basis vector.

[0098] The sound field holography method provided in this application determines the initial basis coefficient error estimation information for multiple observation points based on the complex sound pressure vector, the sound field basis vectors corresponding to each of the multiple observation points, and the initial basis coefficient vectors corresponding to the sound field basis vectors. Then, it updates the initial basis coefficient vectors based on the initial basis coefficient error estimation information to obtain the basis coefficient vectors corresponding to the sound field basis vectors. This achieves the goal of determining the basis coefficient vectors corresponding to the sound field basis vectors based on the complex sound pressure vector and the sound field basis vectors corresponding to each of the multiple observation points. Therefore, this application embodiment can determine the basis coefficient vectors corresponding to the sound field basis vectors without performing Fourier transform on the sound signals collected by the microphones at the observation points, exhibiting good real-time performance and better meeting the real-time requirements of noise reduction.

[0099] Figure 6 The diagram illustrates a flowchart of an exemplary embodiment of this application, showing the process of determining the basis coefficient vector corresponding to the sound field basis vector based on the complex sound pressure vector and the sound field basis vectors corresponding to multiple observation points. Figure 5 Extending from the illustrated embodiment Figure 6 The 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.

[0100] like Figure 6 As shown in the embodiment of this application, the step of updating the initial basis coefficient vector based on the initial basis coefficient error estimation information to obtain the basis coefficient vector corresponding to the sound field basis vector includes the following steps.

[0101] Step S221, based on the trigonometric function signal model form corresponding to the corresponding frequency, determine the initial basis coefficient vector corresponding to the sine amplitude information and cosine amplitude information.

[0102] For example, the basis coefficient vector may be split into (cosine amplitude information) and (sine amplitude information) two parts.

[0103] Step S222, update the sine amplitude information and cosine amplitude information based on the initial basis coefficient error estimation information respectively, to obtain the updated basis coefficient vector.

[0104] For example, based on the above embodiment content (especially expressions (2) to (7)), it can be known that Figure 4 the basis coefficient error estimation information mentioned in the embodiments (that is, the basis coefficient error estimation information) can be described by the above expression (14).

[0105] For example, based on the above expression (14), determine the objective function corresponding to the basis coefficient error estimation information, and then update the sine amplitude information and cosine amplitude information based on the adaptive iterative calculation of the determined objective function, to obtain the updated basis coefficient vector.

[0106] In some embodiments, the objective function corresponding to the basis coefficient error estimation information can be represented by the following expression (15).

[0107]

[0108] The following iterative expression (16) can be obtained.

[0109]

[0110] Based on the above expressions (14), (15) and iterative expression (16), the following expression (17) can be obtained.

[0111]

[0112] Step S223, based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points, and the updated basis coefficient vector, obtain the updated basis coefficient error estimation information.

[0113] Step S224, determine whether the updated basis coefficient error estimation information satisfies the preset basis coefficient error estimation condition.

[0114] It can be understood that the preset basis coefficient error estimation condition can be determined according to actual conditions, and the embodiments of the present application do not make unified limitation.

[0115] Exemplarily, if the judgment result is yes, i.e., the updated basis coefficient error estimation information satisfies the preset basis coefficient error estimation condition, step S225 can be executed. If the judgment result is no, i.e., the updated basis coefficient error estimation information does not satisfy the preset basis coefficient error estimation condition, step S222 can be continuously executed, i.e., the iterative calculation is continuously performed until the updated basis coefficient error estimation information satisfies the preset basis coefficient error estimation condition.

[0116] Step S225, determining the updated basis coefficient vector as the basis coefficient vector corresponding to the sound field basis vector.

[0117] That is to say, the sound field holographic method provided by the embodiments of the present application achieves the purpose of determining the basis coefficient vector corresponding to the sound field basis vector based on the adaptive iterative updating mode. Specifically, the embodiments of the present application can calculate the basis coefficient vector with higher accuracy and better real-time performance, which is more helpful to meet the real-time requirement of active noise reduction.

[0118] It can be understood that, when Figure 6 the embodiment shown in Figure 4 is combined with the embodiment shown in , the two adaptive links can be looped and iterated synchronously. That is, when the square of the modulus of the error vector and the square of the modulus of the error vector converge to the minimum value respectively, the converged complex sound pressure vector and the converged basis coefficient vector are obtained respectively.

[0119] Figure 7 As shown in the figure, the active noise reduction method provided by an exemplary embodiment of the present application is shown. Exemplarily, the active noise reduction method provided by the embodiments of the present application can be executed in the three-dimensional space of a three-dimensional scene to be reduced. As shown in the figure, the active noise reduction method provided by the embodiments of the present application includes the following steps. Figure 7

[0120] Step S400, determining the sub-sound field information corresponding to the target noise reduction frequency in the sound field.

[0121] Exemplarily, the sub-sound field information corresponding to the target noise reduction frequency mentioned in step S400 is obtained by using the sound field holographic method mentioned in any of the above embodiments.

[0122] Step S500, 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.

[0123] The active noise reduction method provided in the embodiments of the present application can track the amplitude fluctuation of the sound signal corresponding to the target noise reduction frequency in real time, and then realize the purpose of actively reducing the sound signal of the target noise reduction frequency in the sound field based on the noise reduction sound wave of the corresponding target noise reduction frequency output by the active noise reduction system. That is, the active noise reduction method provided in the embodiments of the present application can not only achieve precise noise reduction of the global sound field with as few microphone arrays as possible, but also greatly meet the real-time demand of active noise reduction.

[0124] The method embodiments of the present application are described in detail above, and the device embodiments of the present application are described in detail below. Figure 1 to Figure 7 , the device embodiments of the present application are described in detail below. Figure 8 to Figure 10 , the device embodiments of the present application are described in detail below.

[0125] Figure 8 As shown in FIG. 1, the structure of the sound field holographic device provided in an example embodiment of the present application is shown. As shown in FIG. 2, the sound field holographic device provided in the embodiments of the present application includes a first determination module 100, a second determination module 200 and a third determination module 300. Figure 8 The first determination module 100 is configured to determine a complex sound pressure vector corresponding to a plurality of observation points in a sound field based on sound pressure value information corresponding to each of the plurality of observation points. The second determination module 200 is configured to determine a basis coefficient vector corresponding to a sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points. The third determination module 300 is configured to determine sub-sound field information of a corresponding frequency of the sound field based on the basis coefficient vector.

[0126] In some embodiments, the first determination module 100 is further configured to determine a complex number domain signal form of the complex sound pressure vector based on a trigonometric function signal model form corresponding to the corresponding frequency, determine initial real part information and initial imaginary part information corresponding to the complex sound pressure vector based on the complex number domain signal form, and determine the complex sound pressure vector based on the sound pressure value information corresponding to each of the plurality of observation points, the initial real part information and the initial imaginary part information.

[0127] In some embodiments, the first determining module 100 is further configured to: determine initial complex sound pressure error estimation information corresponding to the complex sound pressure vector based on the sound pressure value information, initial real part information, and initial imaginary part information corresponding to each of the multiple observation points; update the initial real part information and initial imaginary part information based on the initial complex sound pressure error estimation information to obtain updated real part information and imaginary part information; obtain updated complex sound pressure error estimation information based on the updated real part information and imaginary part information; determine whether the updated complex sound pressure error estimation information meets the preset complex sound pressure error estimation conditions; if the updated complex sound pressure error estimation information meets the preset complex sound pressure error estimation conditions, then determine the complex sound pressure vector based on the updated real part information and imaginary part information; if the updated complex sound pressure error estimation information does not meet the preset complex sound pressure error estimation conditions, then continue iterative calculation.

[0128] In some embodiments, the second determining module 200 is further configured to determine the initial basis coefficient error estimation information corresponding to the multiple observation points based on the complex sound pressure vector, the sound field basis vector corresponding to each of the multiple observation points, and the initial basis coefficient vector corresponding to the sound field basis vector, update the initial basis coefficient vector based on the initial basis coefficient error estimation information, and obtain the basis coefficient vector corresponding to the sound field basis vector.

[0129] In some embodiments, the second determining module 200 is further configured to: determine the sine amplitude information and cosine amplitude information corresponding to the initial basis coefficient vector based on the trigonometric function signal model form corresponding to the corresponding frequency; update the sine amplitude information and cosine amplitude information respectively based on the initial basis coefficient error estimation information to obtain the updated basis coefficient vector; obtain the updated basis coefficient error estimation information based on the complex sound pressure vector and the sound field basis vectors corresponding to multiple observation points, as well as the updated basis coefficient vector; determine whether the updated basis coefficient error estimation information meets the preset basis coefficient error estimation conditions; if the updated basis coefficient error estimation information meets the preset basis coefficient error estimation conditions, then determine the updated basis coefficient vector as the basis coefficient vector corresponding to the sound field basis vector; if the updated basis coefficient error estimation information does not meet the preset basis coefficient error estimation conditions, then continue iterative calculation.

[0130] Figure 9 The diagram shown is a structural schematic of an active noise cancellation device provided in an exemplary embodiment of this application. Figure 9 As shown in the embodiment of this application, the active noise reduction device includes a sub-sound field information determination module 400 and a noise reduction module 500. The sub-sound field information determination module 400 is used to determine the sub-sound field information corresponding to the target noise reduction frequency in the sound field. The noise reduction module 500 is used to actively reduce the sound signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

[0131] Below, for reference Figure 10 This describes an electronic device according to embodiments of the present application.Figure 10 Fig. 1 shows a structural schematic diagram of an electronic device according to an example embodiment of the present application. As shown in Fig. 1, the electronic device 600 according to the example embodiment of the present application comprises one or more processors 610 and a memory 620. Figure 10

[0132] The processor 610 can be a central processing unit (CPU) or other form of processing unit having data processing and / or instruction execution capabilities, and can control other components in the electronic device 600 to perform desired functions.

[0133] The memory 620 can comprise one or more computer program products, which can comprise various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory, for example, can include random access memory (RAM), cache memory, and / or the like. The non-volatile memory, for example, can include read-only memory (ROM), hard disk, flash memory, and / or the like. One or more computer program instructions can be stored on the computer-readable storage media, and the processor 610 can run the program instructions to implement the sound field holography method and / or the active noise reduction method of various embodiments of the present application described above and / or other desired functions. Various contents, such as basis coefficient vectors, etc., can also be stored in the computer-readable storage media.

[0134] In one example, the electronic device 600 can further comprise an input device 630 and an output device 640, which are interconnected through a bus system and / or other forms of connection mechanism (not shown).

[0135] The input device 630 can comprise, for example, an audio switching button, etc.

[0136] The output device 640 can output various information, including sub-sound field information of corresponding frequency, etc., to the outside. The output device 640 can comprise, for example, a display, a communication network, a loudspeaker and a remote output device connected thereto, etc.

[0137] Of course, in order to simplify, Figure 10 Only some of the components in the electronic device 600 related to the present application are shown in Fig. 1, and components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device 600 can comprise any other appropriate components according to specific application cases.

[0138] By way of example, the electronic device 600 can be at least one of a sound box, a recording pen, and a hearing aid.

[0139] ​In addition to the methods and devices described above, embodiments of the present application can also be a computer program product including computer program instructions that, when run by a processor, cause the processor to perform steps of the sound field holography method and / or the active noise reduction method determination method according to various embodiments of the present application described in the above “Exemplary Methods” section of the present specification.

[0140] The computer program product can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, etc., and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server.

[0141] In addition, embodiments of the present application can also be a computer readable storage medium having stored thereon computer program instructions, which, when run by a processor, cause the processor to perform steps of the sound field holography method and / or the active noise reduction method according to various embodiments of the present application described in the above “Exemplary Methods” section of the present specification.

[0142] The computer readable storage medium can be any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0143] The above describes the basic principles of the present application in combination with specific embodiments, but it should be noted that the advantages, advantages, effects, etc. mentioned in the present application are only examples and are not limiting, and these advantages, advantages, effects, etc. cannot be considered as the must-have of each embodiment of the present application. In addition, the above specific details are only for the purpose of example and understanding, and are not limiting, and the above details do not limit the present application to the must-use of the above specific details to realize.

[0144] The block diagrams of the devices, apparatuses, equipment, systems referred to in this application are only illustrative examples and are not intended to require or imply that the connection, arrangement, configuration must be as shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as "include," "contain," "have," and the like are open-ended words that are intended to mean "including but not limited to," and are to be used interchangeably. The words "or" and "and" as used herein are intended to mean "and / or," and are to be used interchangeably, unless the context clearly indicates otherwise. The word "such as" as used herein is intended to mean "such as but not limited to," and is to be used interchangeably.

[0145] It is also important to note that each of the devices, apparatuses, and methods described in this application can be embodied in a variety of forms, including but not limited to a device, a system, a method, a computer program product, a process, a business method, a data structure, and the like.

[0146] The above description of disclosed aspects is given for illustrative purposes and is not intended to limit the scope of the application. Although various examples and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations of the aspects and embodiments discussed above. Accordingly, the application is not intended to be limited to the specific aspects and embodiments disclosed herein.

[0147] The above description has been given for illustrative purposes and is not intended to limit the embodiments of the application to the forms disclosed herein. Although various example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations of the aspects and embodiments discussed above.

Claims

1. A method of sound field holography, characterized by, The method comprises: determining a complex sound pressure vector corresponding to a plurality of observation points in a sound field based on sound pressure value information corresponding to each of the plurality of observation points, comprising: determining a complex number domain signal form of the complex sound pressure vector based on a trigonometric function signal model form corresponding to a corresponding frequency; determining initial real part information and initial imaginary part information corresponding to the complex sound pressure vector based on the complex number domain signal form; determining the complex sound pressure vector based on the sound pressure value information corresponding to each of the plurality of observation points, the initial real part information and the initial imaginary part information; determining a basis coefficient vector corresponding to a sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points, comprising: determining initial basis coefficient error estimation information corresponding to the plurality of observation points based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points, and an initial basis coefficient vector corresponding to the sound field basis vector; updating the initial basis coefficient vector based on the initial basis coefficient error estimation information to obtain the basis coefficient vector corresponding to the sound field basis vector; determining sub-sound field information of a corresponding frequency of the sound field based on the basis coefficient vector.

2. The acoustic field holography method of claim 1, wherein, The method comprises: determining an initial complex sound pressure error estimation information corresponding to the complex sound pressure vector based on the sound pressure value information corresponding to each of the plurality of observation points, the initial real part information and the initial imaginary part information; updating the initial real part information and the initial imaginary part information based on the initial complex sound pressure error estimation information to obtain updated real part information and imaginary part information; obtaining updated complex sound pressure error estimation information based on the updated real part information and the imaginary part information; determining the complex sound pressure vector based on the updated real part information and the imaginary part information when the updated complex sound pressure error estimation information meets a preset complex sound pressure error estimation condition.

3. The acoustic field holography method of claim 1, wherein, The method comprises: determining sine amplitude information and cosine amplitude information corresponding to the initial basis coefficient vector based on the trigonometric function signal model form corresponding to the corresponding frequency; updating the sine amplitude information and the cosine amplitude information based on the initial basis coefficient error estimation information to obtain an updated basis coefficient vector; obtaining updated basis coefficient error estimation information based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points, and the updated basis coefficient vector; determining the updated basis coefficient vector as the basis coefficient vector corresponding to the sound field basis vector when the updated basis coefficient error estimation information meets a preset basis coefficient error estimation condition.

4. An active noise reduction method, characterized by, The method comprises: determining sub-sound field information corresponding to a target noise reduction frequency in a sound field, wherein the sub-sound field information is determined by the sound field holography method of any one of claims 1 to 3; performing active noise reduction on a sound signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

5. An acoustic field holographic device characterized by, The method comprises: The first determining module is configured to determine a complex sound pressure vector corresponding to a plurality of observation points in a sound field based on sound pressure value information corresponding to each of the plurality of observation points, including: determining a complex number domain signal form of the complex sound pressure vector based on a trigonometric function signal model form corresponding to a corresponding frequency; determining initial real part information and initial imaginary part information corresponding to the complex sound pressure vector based on the complex number domain signal form; determining the complex sound pressure vector based on the sound pressure value information corresponding to each of the plurality of observation points, the initial real part information, and the initial imaginary part information; The second determining module is configured to determine a basis coefficient vector corresponding to a sound field basis vector based on the complex sound pressure vector and the sound field basis vector corresponding to each of the plurality of observation points, including: determining initial basis coefficient error estimation information corresponding to the plurality of observation points based on the complex sound pressure vector, the sound field basis vector corresponding to each of the plurality of observation points, and an initial basis coefficient vector corresponding to the sound field basis vector; updating the initial basis coefficient vector based on the initial basis coefficient error estimation information to obtain the basis coefficient vector corresponding to the sound field basis vector; The third determining module is configured to determine sub-sound field information of a corresponding frequency of the sound field based on the basis coefficient vector.

6. An active noise reduction device, characterized by, including: The sub-sound field information determining module is configured 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 by the sound field holography method of any one of claims 1 to 3; The noise reduction module is configured to perform active noise reduction on a sound signal of the target noise reduction frequency in the sound field based on the sub-sound field information.

7. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is used to execute the method of any one of claims 1 to 4.

8. An electronic device, comprising: The electronic device includes: a processor; a memory for storing instructions executable by the processor; The processor is configured to execute the method of any one of claims 1 to 4.

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