Sound source localization method and device based on improved generalized cross-correlation algorithm, and medium

Abstract

The invention discloses a sound source localization method and device based on an improved generalized cross-correlation algorithm and a medium, and belongs to the field of sound source localization, and the method comprises the steps: collecting a sound source signal through a quaternary cross sensor array; constructing an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function; performing generalized cross-correlation operation according to the sound source signal and the improved weighting function to obtain time delay; and performing geometric operation in the three-dimensional rectangular coordinate system based on the time delay to obtain a sound source position. Therefore, the accuracy and robustness of sound source localization can be improved in a low signal-to-noise ratio environment and a strong reverberation environment by implementing the method and the device.

Description

Technical Field

[0001] The present invention relates to the field of sound source localization, and in particular to a sound source localization method, device and medium based on an improved generalized cross-correlation algorithm. Background Art

[0002] As a clean energy source, hydrogen is widely used in industry, energy, and transportation, especially in fuel cells, hydrogen storage, and hydrogen-powered drive systems. However, hydrogen is highly flammable in air and is colorless and odorless. Therefore, once a leak occurs, it can easily cause a fire or explosion, posing a serious threat to personnel safety and the environment. Therefore, accurate and timely detection of hydrogen leaks is key to ensuring safety. To improve the accuracy of hydrogen leak detection, sound source localization technology has been introduced into the leak detection system. When hydrogen leaks, the pressure difference causes the gas to eject at high speed and generate sound waves. In particular, the turbulence and shock waves formed near the leak point generate detectable ultrasonic signals. By collecting sound wave signals with a multi-sensor array, the sound source can be located, thereby determining the specific location of the leak.

[0003] Sound source localization relies primarily on methods based on time delay (TDOA) or direction of arrival (DOA). The time delay method is currently the most widely used technology. It determines the location of the sound source by calculating the time delay of ultrasonic signals from the sound source to different sensors. Since ultrasonic signals take different amounts of time to propagate to sensors at different locations, the time delay can be calculated using the following formula:

[0004]

[0005] Here, r1 and r2 are the distances from the sound source to the two sensors, respectively; v is the speed of sound wave propagation; and τ is the time delay of the ultrasonic signal between the two sensors. By performing a series of processing on the received ultrasonic signal, the location of the sound source can be determined based on the geometric relationship between the target and the element position. To accurately estimate the time delay and achieve high-precision sound source localization, the generalized cross-correlation (GCC) algorithm is widely used. The GCC algorithm calculates the cross-correlation function of two ultrasonic signals and extracts the time difference corresponding to the peak to determine the time delay. However, the GCC algorithm is susceptible to noise interference in low signal-to-noise ratio environments, resulting in blurred cross-correlation peaks, which affects the accuracy of time delay estimation. To address this issue, researchers invented the generalized quadratic cross-correlation (GQCC) algorithm, which adds a quadratic correlation operation to the GCC algorithm to enhance the ultrasonic signal component while suppressing the influence of noise. The quadratic correlation operation utilizes the autocorrelation characteristics of the signal to improve peak clarity and make time delay estimation more accurate. However, although the GQCC algorithm improves the noise resistance, it still faces the problem of high computational complexity and may still cause estimation errors in strong reverberation environments. Summary of the Invention

[0006] The present invention provides a sound source localization method, device and medium based on an improved generalized cross-correlation algorithm, which can improve the accuracy and robustness of sound source localization in low signal-to-noise ratio environments and strong reverberation environments.

[0007] An embodiment of the present invention provides a sound source localization method based on an improved generalized cross-correlation algorithm, comprising:

[0008] Acquiring sound source signals through a four-element cross sensor array; wherein the four-element cross sensor array is composed of four sensors located in the same coordinate axis plane of a three-dimensional rectangular coordinate system, wherein two sensors are included on each of the two coordinate axes of the coordinate axis plane, and the two sensors are respectively located on either side of the origin of the three-dimensional rectangular coordinate system, and the four sensors are equidistant from the origin;

[0009] Constructing an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function;

[0010] Performing a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay;

[0011] A geometric operation is performed in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position.

[0012] The embodiment of the present invention collects sound source signals through a four-element cross sensor array. The position and layout of the sensors ensure that the position of the sound source can be calculated through a certain number of time delays. An improved weighting function is obtained by weighting the phase transformation weighting function and the maximum likelihood weighting function, so that the improved weighting function can combine the good robustness of the phase transformation weighting function in a strong reverberation environment and the good robustness of the maximum likelihood weighting function in a low signal-to-noise ratio environment. The generalized cross-correlation operation is performed on the improved weighting function to suppress the influence of reverberation and environmental noise on the accuracy of time delay estimation. A set of equations is constructed through a certain number of time delays and the geometric relationship between the four-element cross sensor array and the sound source, and the accurate sound source position can be solved. Compared with the existing technology that is easily affected in low signal-to-noise ratio environments and strong reverberation environments, the present application can improve the accuracy and robustness of sound source positioning.

[0013] Furthermore, collecting the sound source signal by using a four-element cross sensor array includes:

[0014] The four sensors of the four-element cross sensor array respectively collect a first sound source analog signal; wherein the first sound source analog signal is emitted by the same sound source;

[0015] performing signal amplification processing on the four first sound source analog signals respectively to obtain four second sound source analog signals;

[0016] Analog-to-digital conversion is performed on the four second sound source analog signals respectively to obtain four sound source signals; wherein each sound source signal corresponds to a noise signal.

[0017] The embodiment of the present invention can enhance the quality of the sound source signal and improve the calculation efficiency by performing signal amplification and analog-to-digital conversion processing on the sound source analog signal.

[0018] Furthermore, constructing an improved weighting function according to the sound source signal includes:

[0019] Performing Fourier transform on the four sound source signals and their corresponding noise signals respectively to obtain four frequency domain sound source signals and their corresponding frequency domain noise signals;

[0020] An improved weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal; wherein, one improved weighting function corresponds to any two sensors.

[0021] The embodiment of the present invention provides a data basis for the subsequent construction of an improved weighting function by performing Fourier transform on a sound source signal and its corresponding noise signal.

[0022] Furthermore, constructing an improved weighting function according to the frequency domain sound source signal and the frequency domain noise signal includes:

[0023] A phase transformation weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal, specifically:

[0024]

[0025] in, is the phase transformation weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor; is the cross-power spectrum function between the frequency domain noise signal of the i-th sensor and the frequency domain noise signal of the j-th sensor; ρ is the noise parameter factor; is the signal coherence function between the i-th sensor and the j-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the i-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the jth sensor;

[0026] A maximum likelihood weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal, specifically:

[0027]

[0028] in, is the maximum likelihood weighted function corresponding to the i-th sensor and the j-th sensor; X i (ω) is the frequency domain sound source signal of the i-th sensor; X j (ω) is the frequency domain sound source signal of the jth sensor; N i (ω) is the frequency domain noise signal of the i-th sensor; N j (ω) is the frequency domain noise signal of the jth sensor;

[0029] The phase transformation weighting function and the maximum likelihood weighting function are weighted and summed to obtain an improved weighting function, specifically:

[0030]

[0031] in, is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the weight factor, Q is the directivity factor, R is the space constant, and D is the prior distance.

[0032] The embodiment of the present invention obtains an improved weighting function by weighting the phase transform weighting function and the maximum likelihood weighting function, so that the improved weighting function can combine the good robustness of the phase transform weighting function in a strong reverberation environment and the good robustness of the maximum likelihood weighting function in a low signal-to-noise ratio environment.

[0033] Furthermore, performing a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay includes:

[0034] Constructing a generalized cross-correlation function based on the sound source signal and the improved weighting function; wherein, there is one generalized cross-correlation function corresponding to any two sensors;

[0035] The absolute value operation and peak detection are performed on the generalized cross-correlation function to obtain the time delay, which is specifically:

[0036]

[0037] Among them, τ ij is the time delay of collecting the sound source signal between the i-th sensor and the j-th sensor; To find the operation of τ corresponding to the maximum value of the objective function; R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor.

[0038] The embodiment of the present invention can suppress the influence of reverberation and environmental noise on the accuracy of time delay estimation by performing generalized cross-correlation calculation through an improved weighting function.

[0039] Furthermore, constructing a generalized cross-correlation function based on the sound source signal and the improved weighting function includes:

[0040] In the frequency domain, weighting processing is performed on the sound source signal by using the improved weighting function;

[0041] Perform inverse Fourier transform on the weighted result to obtain the generalized cross-correlation function, which is:

[0042]

[0043] Among them, R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor; is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor.

[0044] The embodiment of the present invention provides a data basis for the subsequent solution of time delay by constructing a generalized cross-correlation function.

[0045] Furthermore, performing geometric operations in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position includes:

[0046] Based on the time delay, a set of equations is constructed in the three-dimensional rectangular coordinate system, specifically:

[0047]

[0048] Where (x, y, z) are the coordinates of the sound source; R is the distance from the sound source to the origin of the three-dimensional rectangular coordinate system; r1, r2, r3, and r4 are the distances from the sound source to the four sensors respectively; d is the distance from any sensor to the origin; Δτ 12 ,Δτ 13 ,Δτ 14 are the time delays between any sensor and the other three sensors in collecting the sound source signal; c is the speed of sound propagation in the air;

[0049] Solve the equations to get the sound source position, specifically:

[0050]

[0051] The embodiment of the present invention constructs a set of equations by using a certain number of time delays and the geometric relationship between the four-element cross sensor array and the sound source, and can solve the problem to obtain the accurate sound source position.

[0052] Another embodiment of the present invention further provides a sound source localization device based on an improved generalized cross-correlation algorithm, comprising: a signal acquisition module, a weighting function module, a generalized cross-correlation module, and a geometric operation module;

[0053] The signal acquisition module is configured to acquire sound source signals through a four-element cross sensor array; wherein the four-element cross sensor array is composed of four sensors located in the same coordinate axis plane of a three-dimensional rectangular coordinate system, wherein two sensors are included on each of the two coordinate axes of the coordinate axis plane, and the two sensors are respectively located on either side of the origin of the three-dimensional rectangular coordinate system, and the four sensors are equidistant from the origin;

[0054] The weighting function module is used to construct an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function;

[0055] The generalized cross-correlation module is used to perform a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay;

[0056] The geometric operation module is used to perform geometric operations in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position.

[0057] Another embodiment of the present invention further provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the steps of a sound source localization method based on an improved generalized cross-correlation algorithm as described in the present invention are implemented.

[0058] Another embodiment of the present invention further provides a computer-readable storage medium item, comprising: a stored computer program, which, when the computer program is executed, controls the device where the computer-readable storage medium is located to execute the steps of a sound source localization method based on an improved generalized cross-correlation algorithm as described in the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A schematic flow chart of an embodiment of a sound source localization method based on an improved generalized cross-correlation algorithm provided by the present invention;

[0060] Figure 2 A schematic structural diagram of an embodiment of a four-element cross sensor array provided by the present invention;

[0061] Figure 3 A schematic flow chart of an embodiment of the generalized cross-correlation algorithm provided by the present invention;

[0062] Figure 4 A flow chart of an embodiment of a sound source localization system based on an improved generalized cross-correlation algorithm provided by the present invention;

[0063] Figure 5 This is a structural schematic diagram of an embodiment of a sound source localization device based on an improved generalized cross-correlation algorithm provided by the present invention. DETAILED DESCRIPTION

[0064] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0066] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0067] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0068] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0069] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0070] See also Figure 1 To solve the problem that the existing technology is easily affected in low signal-to-noise ratio environments and strong reverberation environments, an embodiment of the present invention provides a sound source localization method based on an improved generalized cross-correlation algorithm, including steps S101 to S104:

[0071] Step S101, collecting sound source signals through a four-element cross sensor array; wherein the four-element cross sensor array is composed of four sensors located in the same coordinate axis plane of a three-dimensional rectangular coordinate system, including two sensors on each of the two coordinate axes of the coordinate axis plane, and the two sensors are respectively located on both sides of the origin of the three-dimensional rectangular coordinate system, and the distances between the four sensors and the origin are equal.

[0072] Specifically, the sensor can be an ultrasonic sensor that can convert the collected sound signal into an analog electrical signal. Time delay refers to the time difference between the signal propagating from the sound source to different sensors. In order to calculate the coordinate value of the sound source in three-dimensional space, three different time delays are needed to construct a set of equations. Therefore, the number of sensors cannot be less than four. In one embodiment of the present invention, a regular quadrilateral four-element cross sensor array is used to collect the sound source signal. The structure of the four-element cross sensor array is as follows: Figure 2The four-element cross sensor array includes four sensors (M1, M2, M3, M4) located in the xy coordinate plane of the three-dimensional rectangular coordinate system, where M1 is located on the positive x-axis, M3 is located on the negative x-axis, M4 is located on the positive y-axis, and M2 is located on the negative y-axis. The distances d between the four sensors and the origin O are all.

[0073] Step S102: constructing an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function.

[0074] Specifically, a generalized cross-correlation algorithm can be used to calculate the cross-correlation function of two signals, and the time difference corresponding to the peak can be extracted to determine the time delay. The weighting function can significantly improve the clarity of the cross-correlation peak by adjusting the frequency domain characteristics of the cross-correlation function, thereby improving the accuracy of sound source positioning. The phase transformation weighting function and the maximum likelihood weighting function are two weighting functions used in the generalized cross-correlation algorithm. The phase transformation weighting function has good robustness to reverberation, and the maximum likelihood weighting function has good robustness to ambient noise. By jointly weighting the phase transformation weighting function and the maximum likelihood weighting function, an improved weighting function is obtained, so that the improved weighting function has good robustness to both ambient noise and reverberation.

[0075] Step S103: performing a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay.

[0076] Specifically, the process of solving the time delay by generalized cross-correlation operation is as follows: Figure 3 As shown in the figure: first, the cross-power spectrum function of the received signal is obtained, where the cross-power spectrum function is obtained by Fourier transforming the sound source signals collected by the two sensors; second, the cross-power spectrum function is weighted by improving the weighting function to suppress the influence of reverberation and environmental noise on the accuracy of delay estimation; then, the weighted cross-power spectrum function is inverse Fourier transformed to obtain a generalized cross-correlation function; finally, the peak value of the absolute value of the cross-correlation function is detected, and the peak value is used as the time delay of the sound source signals collected by the two sensors.

[0077] Step S104: performing geometric operations in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position.

[0078] Specifically, there are eight unknowns in total, including the three-dimensional coordinates (x, y, z) of the sound source and the distances from the sound source to the origin of the three-dimensional rectangular coordinate system and the four sensors. Based on the geometric relationship between the sound source and the four sensors and three different time delays, a system of eight equations can be constructed to solve the unknowns. In one embodiment of the present invention, the geometric relationship between the sound source and the four sensors is as follows: Figure 2As shown, the three-dimensional coordinates of the sound source S are (x, y, z); according to the geometric relationship between the sound source S and the origin of the three-dimensional rectangular coordinate system, the equation x can be established. 2 +y 2 +z 2 =R 2 , where R is the distance from the sound source S to the origin of the three-dimensional rectangular coordinate system; according to the geometric relationship between the sound source S and the four sensors, equations (xd) can be established respectively 2 +y 2 +z 2 =r1 2 、x 2 +(yd) 2 +z 2 =r2 2 、(x+d) 2 +y 2 +z 2 =r3 2 and x 2 +(y+d) 2 +z 2 =r4 2 , where r1, r2, r3, and r4 are the distances from the sound source S to the four sensors respectively; according to the three different time delays, the equation r2-r1=Δτ can be constructed respectively 12 c. r3-r1=Δτ 13 c and r4-r1=Δτ 14 c, where Δτ 12 ,Δτ 13 ,Δτ 14 are the time delays for collecting sound source signals between any sensor and the other three sensors, and c is the speed of sound propagation in air. By constructing a system of equations based on the above eight equations and solving them, the three-dimensional coordinates (x, y, z) of the sound source S can be obtained.

[0079] The embodiment of the present invention collects sound source signals through a four-element cross sensor array. The position and layout of the sensors ensure that the position of the sound source can be calculated through a certain number of time delays. An improved weighting function is obtained by weighting the phase transformation weighting function and the maximum likelihood weighting function, so that the improved weighting function can combine the good robustness of the phase transformation weighting function in a strong reverberation environment and the good robustness of the maximum likelihood weighting function in a low signal-to-noise ratio environment. The generalized cross-correlation operation is performed on the improved weighting function to suppress the influence of reverberation and environmental noise on the accuracy of time delay estimation. A set of equations is constructed through a certain number of time delays and the geometric relationship between the four-element cross sensor array and the sound source, and the accurate sound source position can be solved. Compared with the existing technology that is easily affected in low signal-to-noise ratio environments and strong reverberation environments, the present application can improve the accuracy and robustness of sound source positioning.

[0080] In order to enhance the quality of the sound source analog signal and improve the computational efficiency, it is necessary to perform signal amplification and analog-to-digital conversion on the sound source analog signal. Optionally, in an embodiment of the present invention, the sound source signal is collected by a four-element cross sensor array, including:

[0081] The four sensors of the four-element cross sensor array respectively collect a first sound source analog signal; wherein the first sound source analog signal is emitted by the same sound source;

[0082] performing signal amplification processing on the four first sound source analog signals respectively to obtain four second sound source analog signals;

[0083] Analog-to-digital conversion is performed on the four second sound source analog signals respectively to obtain four sound source signals; wherein each sound source signal corresponds to a noise signal.

[0084] Specifically, the sound source signal collected by the sensor is usually a weak analog signal, which needs to be amplified by the signal amplification part so that its amplitude meets the analog-to-digital conversion range of the subsequent signal acquisition part. Specifically:

[0085] x i ′ (t) = Gx i (t);

[0086] Among them, x i ′ (t) is the analog signal of the sound source after signal amplification; G is the amplification gain; x i (t) is the sound source simulation signal.

[0087] The amplified sound source analog signal is sent to the analog-to-digital converter (ADC) and discretized at the sampling rate to obtain the sound source digital signal, specifically:

[0088] x i [n] = x i (nT s );

[0089] Among them, x i [n] is the digital signal of the sound source; n is the number of sampling cycles; T s =1 / f s is the sampling period.

[0090] The embodiment of the present invention can enhance the quality of the sound source signal and improve the calculation efficiency by performing signal amplification and analog-to-digital conversion processing on the sound source analog signal.

[0091] In order to run the generalized cross-correlation algorithm, a weighting function needs to be constructed in advance. Optionally, in an embodiment of the present invention, constructing an improved weighting function based on the sound source signal includes:

[0092] Performing Fourier transform on the four sound source signals and their corresponding noise signals respectively to obtain four frequency domain sound source signals and their corresponding frequency domain noise signals;

[0093] An improved weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal; wherein, one improved weighting function corresponds to any two sensors.

[0094] Specifically, since the generalized cross-correlation algorithm introduces a weighting function in the frequency domain to suppress the influence of reverberation and ambient noise, the sound source signal in the time domain and its corresponding noise signal need to be Fourier transformed first to complete the construction of the improved weighting function.

[0095] The embodiment of the present invention provides a data basis for the subsequent construction of an improved weighting function by performing Fourier transform on a sound source signal and its corresponding noise signal.

[0096] In order to suppress the influence of reverberation and ambient noise at the same time, it is necessary to combine the phase transformation weighting function and the maximum likelihood weighting function. Optionally, in an embodiment of the present invention, constructing an improved weighting function based on the frequency domain sound source signal and the frequency domain noise signal includes:

[0097] A phase transformation weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal, specifically:

[0098]

[0099] in, is the phase transformation weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor; is the cross-power spectrum function between the frequency domain noise signal of the i-th sensor and the frequency domain noise signal of the j-th sensor; ρ is the noise parameter factor; is the signal coherence function between the i-th sensor and the j-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the i-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the jth sensor;

[0100] A maximum likelihood weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal, specifically:

[0101]

[0102] in, is the maximum likelihood weighted function corresponding to the i-th sensor and the j-th sensor; X i (ω) is the frequency domain sound source signal of the i-th sensor; X j (ω) is the frequency domain sound source signal of the jth sensor; N i (ω) is the frequency domain noise signal of the i-th sensor; N j (ω) is the frequency domain noise signal of the jth sensor;

[0103] The phase transformation weighting function and the maximum likelihood weighting function are weighted and summed to obtain an improved weighting function, specifically:

[0104]

[0105] in, is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the weight factor, Q is the directivity factor, R is the space constant, and D is the prior distance.

[0106] Specifically, in a real environment, due to the presence of wall reflections, the two noise signals received by the two sensors also have correlation. Therefore, the phase transformation weighting function described in the embodiment of the present invention is the phase transformation weighting function after subtracting the correlated noise portion. The robustness of the phase transformation weighting function to reverberation and noise can be further optimized by using the maximum likelihood weighting function. The total noise energy formula |N T (ω)| 2 =q|X(ω)| 2 +(1-q)|N(ω)| 2 Substituting the maximum likelihood weighting function, we can obtain the weighting function when noise and reverberation exist at the same time, which is:

[0107]

[0108] Since the sensors are identical and very close to each other in the same space, we can assume that q = q i =q j , simplifying the above formula, we can get the improved weighting function The weight factor q is used to balance the influence between the two weighting functions. When the ambient noise is large, the improved weighting function is close to the maximum likelihood weighting function. When the reverberation noise is large, the improved weighting function is close to the phase shift weighting function.

[0109] The embodiment of the present invention obtains an improved weighting function by weighting the phase transform weighting function and the maximum likelihood weighting function, so that the improved weighting function can combine the good robustness of the phase transform weighting function in a strong reverberation environment and the good robustness of the maximum likelihood weighting function in a low signal-to-noise ratio environment.

[0110] In order to obtain the time delay estimate, it is necessary to construct a generalized cross-correlation function. Optionally, in an embodiment of the present invention, performing a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain the time delay includes:

[0111] Constructing a generalized cross-correlation function based on the sound source signal and the improved weighting function; wherein, there is one generalized cross-correlation function corresponding to any two sensors;

[0112] The absolute value operation and peak detection are performed on the generalized cross-correlation function to obtain the time delay, which is specifically:

[0113]

[0114] Among them, τ ij is the time delay of collecting the sound source signal between the i-th sensor and the j-th sensor; To find the operation of τ corresponding to the maximum value of the objective function; R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor.

[0115] The embodiment of the present invention can suppress the influence of reverberation and environmental noise on the accuracy of time delay estimation by performing generalized cross-correlation calculation through an improved weighting function.

[0116] In order to construct a generalized cross-correlation function, it is necessary to weight the cross-power spectrum functions of the two sound source signals in the frequency domain. Optionally, in an embodiment of the present invention, constructing the generalized cross-correlation function based on the sound source signals and the improved weighting function includes:

[0117] In the frequency domain, weighting processing is performed on the sound source signal by using the improved weighting function;

[0118] Perform inverse Fourier transform on the weighted result to obtain the generalized cross-correlation function, which is:

[0119]

[0120] Among them, R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor; is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor.

[0121] The embodiment of the present invention provides a data basis for the subsequent solution of time delay by constructing a generalized cross-correlation function.

[0122] In order to obtain the sound source position, it is necessary to perform a geometric operation based on the time delay. Optionally, in an embodiment of the present invention, performing a geometric operation based on the time delay in the three-dimensional rectangular coordinate system to obtain the sound source position includes:

[0123] Based on the time delay, a set of equations is constructed in the three-dimensional rectangular coordinate system, specifically:

[0124]

[0125] Where (x, y, z) are the coordinates of the sound source; R is the distance from the sound source to the origin of the three-dimensional rectangular coordinate system; r1, r2, r3, and r4 are the distances from the sound source to the four sensors respectively; d is the distance from any sensor to the origin; Δτ 12 ,Δτ 13 ,Δτ 14 are the time delays between any sensor and the other three sensors in collecting the sound source signal; c is the speed of sound propagation in the air;

[0126] Solve the equations to get the sound source position, specifically:

[0127]

[0128] The embodiment of the present invention constructs a set of equations by using a certain number of time delays and the geometric relationship between the four-element cross sensor array and the sound source, and can solve the problem to obtain the accurate sound source position.

[0129] As a preferred solution, the embodiment of the present invention can be used to locate the location of hydrogen leakage. After obtaining the hydrogen leakage location data, the hydrogen leakage location data can be uploaded to the cloud through the Internet of Things technology to analyze the long-term trend. An early warning can be issued based on the distance, location area and leakage trend of the leakage point, and combined with the set safety radius R safe Different levels of alarms are divided according to the critical thresholds, as shown in Table 1.

[0130] Table 1-Hydrogen Leakage Warning Level Table

[0131]

[0132] like Figure 4 As shown, based on the above method embodiment, a system embodiment for locating a hydrogen leak position is provided, including steps S1 to S4:

[0133] S1, collecting a sound source analog signal from the hydrogen leakage sound source area through a sensor array; this is equivalent to executing the action of collecting a first sound source analog signal from each of the four sensors of the four-element cross sensor array in step S101;

[0134] S2, converting the collected sound source analog signal into a sound source digital signal through signal amplification and analog-to-digital conversion; equivalent to performing signal amplification processing on the four first sound source analog signals to obtain four second sound source analog signals in step S101; and performing analog-to-digital conversion processing on the four second sound source analog signals to obtain four sound source signals;

[0135] S3, performing improved generalized cross-correlation delay calculation based on the sound source digital signal to obtain the delay; equivalent to executing steps S102 and S103;

[0136] S4, performing geometric calculations based on the time delay to locate the hydrogen leak position; equivalent to executing step S104;

[0137] S5, setting a multi-level monitoring and alarm system based on the hydrogen leakage location; equivalent to using the sound source location obtained in step S104 to set a multi-level monitoring and alarm system.

[0138] The embodiments of the present invention collect sound source analog signals through a sensor array. The position and layout of the sensors ensure that the location of the sound source can be calculated using a certain number of time delays. By amplifying and performing analog-to-digital conversion on the sound source analog signals, the sound source signal quality can be enhanced and computational efficiency can be improved. By improving the delay estimation method using generalized cross-correlation delay calculation, the effects of reverberation and environmental noise on the accuracy of delay estimation can be suppressed. A system of equations is constructed based on a certain number of time delays and the geometric relationship between the sensor array and the sound source to accurately solve the hydrogen leak location. A multi-level monitoring and alarm system is established based on the hydrogen leak location, thereby reducing the threat posed by hydrogen leaks to human safety and the environment.

[0139] like Figure 5 As shown, based on the above method embodiment, a corresponding device embodiment is provided;

[0140] An embodiment of the present invention provides a sound source localization device based on an improved generalized cross-correlation algorithm, comprising: a signal acquisition module 501, a weighting function module 502, a generalized cross-correlation module 503, and a geometric operation module 504;

[0141] The signal acquisition module 501 is configured to acquire sound source signals using a four-element cross sensor array; wherein the four-element cross sensor array is composed of four sensors located in the same coordinate axis plane of a three-dimensional rectangular coordinate system, wherein two sensors are included on each of the two coordinate axes of the coordinate axis plane, and the two sensors are located on either side of the origin of the three-dimensional rectangular coordinate system, and the four sensors are equidistant from the origin;

[0142] The weighting function module 502 is used to construct an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function;

[0143] The generalized cross-correlation module 503 is used to perform a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay;

[0144] The geometric operation module 504 is configured to perform geometric operations in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position.

[0145] In the embodiment of the present invention, the signal acquisition module 501 includes: a signal acquisition submodule, a signal amplification submodule and an analog-to-digital conversion submodule;

[0146] The signal acquisition submodule is configured to acquire a first sound source analog signal through each of the four sensors of the four-element cross sensor array; wherein the first sound source analog signals are emitted by the same sound source;

[0147] The signal amplification submodule is used to perform signal amplification processing on the four first sound source analog signals respectively to obtain four second sound source analog signals;

[0148] The analog-to-digital conversion submodule is used to perform analog-to-digital conversion processing on the four second sound source analog signals respectively to obtain four sound source signals; wherein each sound source signal corresponds to a noise signal.

[0149] The embodiment of the present invention can enhance the quality of the sound source signal and improve the calculation efficiency by performing signal amplification and analog-to-digital conversion processing on the sound source analog signal.

[0150] In the embodiment of the present invention, the weighting function module 502 includes: a frequency domain transformation submodule and a weighting function submodule;

[0151] The frequency domain transformation submodule is used to perform Fourier transformation on the four sound source signals and their corresponding noise signals respectively to obtain four frequency domain sound source signals and their corresponding frequency domain noise signals;

[0152] The weighting function submodule is used to construct an improved weighting function according to the frequency domain sound source signal and the frequency domain noise signal; wherein, there is one improved weighting function corresponding to any two sensors.

[0153] The embodiment of the present invention provides a data basis for the subsequent construction of an improved weighting function by performing Fourier transform on a sound source signal and its corresponding noise signal.

[0154] In an embodiment of the present invention, the weighted function submodule includes: a phase transformation weighted function unit, a maximum likelihood weighted function unit and a weighted summation unit;

[0155] The phase transformation weighting function unit is used to construct a phase transformation weighting function according to the frequency domain sound source signal and the frequency domain noise signal, specifically:

[0156]

[0157] in, is the phase transformation weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor; is the cross-power spectrum function between the frequency domain noise signal of the i-th sensor and the frequency domain noise signal of the j-th sensor; ρ is the noise parameter factor; is the signal coherence function between the i-th sensor and the j-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the i-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the jth sensor;

[0158] The maximum likelihood weighted function unit is used to construct a maximum likelihood weighted function according to the frequency domain sound source signal and the frequency domain noise signal, specifically:

[0159]

[0160] in, is the maximum likelihood weighted function corresponding to the i-th sensor and the j-th sensor; X i (ω) is the frequency domain sound source signal of the i-th sensor; X j (ω) is the frequency domain sound source signal of the jth sensor; N i (ω) is the frequency domain noise signal of the i-th sensor; N j (ω) is the frequency domain noise signal of the jth sensor;

[0161] The weighted summation unit is used to perform weighted summation on the phase transformation weighting function and the maximum likelihood weighting function to obtain an improved weighting function, which is specifically:

[0162]

[0163] in, is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the weight factor, Q is the directivity factor, R is the space constant, and D is the prior distance.

[0164] The embodiment of the present invention obtains an improved weighting function by weighting the phase transform weighting function and the maximum likelihood weighting function, so that the improved weighting function can combine the good robustness of the phase transform weighting function in a strong reverberation environment and the good robustness of the maximum likelihood weighting function in a low signal-to-noise ratio environment.

[0165] In the embodiment of the present invention, the generalized cross-correlation module 503 includes: a generalized cross-correlation submodule and a time delay estimation submodule;

[0166] The generalized cross-correlation submodule is used to construct a generalized cross-correlation function based on the sound source signal and the improved weighting function; wherein, there is one generalized cross-correlation function between any two sensors;

[0167] The time delay estimation submodule is used to perform absolute value calculation and peak detection on the generalized cross-correlation function to obtain the time delay, specifically:

[0168]

[0169] Among them, τ ij is the time delay of collecting the sound source signal between the i-th sensor and the j-th sensor; To find the operation of τ corresponding to the maximum value of the objective function; R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor.

[0170] The embodiment of the present invention can suppress the influence of reverberation and environmental noise on the accuracy of time delay estimation by performing generalized cross-correlation calculation through an improved weighting function.

[0171] In an embodiment of the present invention, the generalized cross-correlation submodule includes: a weighted processing unit and a generalized cross-correlation unit;

[0172] The weighted processing unit is used to perform weighted processing on the sound source signal in the frequency domain by using the improved weighting function;

[0173] The generalized cross-correlation unit is used to perform inverse Fourier transform on the weighted result to obtain a generalized cross-correlation function, which is specifically:

[0174]

[0175] Among them, R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor; is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor.

[0176] The embodiment of the present invention provides a data basis for the subsequent solution of time delay by constructing a generalized cross-correlation function.

[0177] In the embodiment of the present invention, the geometric operation module 504 includes: a constructing system of equations submodule and a solving system of equations submodule;

[0178] The constructing equation group submodule is used to construct an equation group in the three-dimensional rectangular coordinate system based on the time delay, specifically:

[0179]

[0180] Where (x, y, z) are the coordinates of the sound source; R is the distance from the sound source to the origin of the three-dimensional rectangular coordinate system; r1, r2, r3, and r4 are the distances from the sound source to the four sensors respectively; d is the distance from any sensor to the origin; Δτ 12 ,Δτ 13 ,Δτ 14 are the time delays between any sensor and the other three sensors in collecting the sound source signal; c is the speed of sound propagation in the air;

[0181] The equation solving submodule is used to solve the equations to obtain the sound source position, specifically:

[0182]

[0183] The embodiment of the present invention constructs a set of equations by using a certain number of time delays and the geometric relationship between the four-element cross sensor array and the sound source, and can solve the problem to obtain the accurate sound source position.

[0184] It can be understood that the above-mentioned device embodiment corresponds to the method embodiment of the present invention, and can implement a sound source localization method based on an improved generalized cross-correlation algorithm provided by any of the above-mentioned method embodiments of the present invention.

[0185] The embodiment of the present invention collects sound source signals through a signal acquisition module. The position and layout of the sensors ensure that the position of the sound source can be calculated through a certain number of time delays. An improved weighting function is constructed through a weighting function module, so that the improved weighting function can combine the good robustness of the phase transformation weighting function in a strong reverberation environment and the good robustness of the maximum likelihood weighting function in a low signal-to-noise ratio environment. The generalized cross-correlation module performs a generalized cross-correlation operation, which can suppress the influence of reverberation and environmental noise on the accuracy of time delay estimation. The geometric operation module constructs a set of equations, which can solve and obtain the accurate sound source position. Compared with the existing technology that is easily affected in low signal-to-noise ratio environments and strong reverberation environments, the present application can improve the accuracy and robustness of sound source positioning.

[0186] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Furthermore, in the drawings of the device embodiments provided by the present invention, the connection relationship between modules indicates that they have a communication connection, which may be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement the present invention without inventive effort.

[0187] Based on the above embodiment of a sound source localization method based on an improved generalized cross-correlation algorithm, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a sound source localization method based on an improved generalized cross-correlation algorithm according to any embodiment of the present invention.

[0188] For example, in this embodiment, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to implement the present invention. The one or more module elements may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0189] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0190] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0191] Based on the above method embodiments, another embodiment of the present invention provides a computer-readable storage medium, including a stored computer program, wherein, when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the sound source localization method based on the improved generalized cross-correlation algorithm described in any one of the above method embodiments of the present invention.

[0192] Wherein, the module / unit integrated in the device / terminal equipment, if implemented in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0193] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A sound source localization method based on an improved generalized cross-correlation algorithm, characterized in that: include: Acquiring sound source signals through a four-element cross sensor array; wherein the four-element cross sensor array is composed of four sensors located in the same coordinate axis plane of a three-dimensional rectangular coordinate system, wherein two sensors are included on each of the two coordinate axes of the coordinate axis plane, and the two sensors are respectively located on either side of the origin of the three-dimensional rectangular coordinate system, and the four sensors are equidistant from the origin; Constructing an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function; Performing a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay; A geometric operation is performed in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position.

2. The sound source localization method based on the improved generalized cross-correlation algorithm according to claim 1, wherein: The collecting of sound source signals by using a four-element cross sensor array includes: The four sensors of the four-element cross sensor array respectively collect a first sound source analog signal; wherein the first sound source analog signal is emitted by the same sound source; performing signal amplification processing on the four first sound source analog signals respectively to obtain four second sound source analog signals; Analog-to-digital conversion is performed on the four second sound source analog signals respectively to obtain four sound source signals; wherein each sound source signal corresponds to a noise signal.

3. A sound source localization method based on an improved generalized cross-correlation algorithm as claimed in claim 2, characterized in that: The step of constructing an improved weighting function according to the sound source signal comprises: Performing Fourier transform on the four sound source signals and their corresponding noise signals respectively to obtain four frequency domain sound source signals and their corresponding frequency domain noise signals; An improved weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal; wherein, one improved weighting function corresponds to any two sensors.

4. A sound source localization method based on an improved generalized cross-correlation algorithm as claimed in claim 3, characterized in that: The constructing of an improved weighting function according to the frequency domain sound source signal and the frequency domain noise signal comprises: A phase transformation weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal, specifically: in, is the phase transformation weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor; is the cross-power spectrum function between the frequency domain noise signal of the i-th sensor and the frequency domain noise signal of the j-th sensor; ρ is the noise parameter factor; is the signal coherence function between the i-th sensor and the j-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the i-th sensor, is the autopower spectrum function of the frequency domain sound source signal of the jth sensor; A maximum likelihood weighting function is constructed according to the frequency domain sound source signal and the frequency domain noise signal, specifically: in, is the maximum likelihood weighted function corresponding to the i-th sensor and the j-th sensor; X i (v) is the frequency domain sound source signal of the i-th sensor; X j (ω) is the frequency domain sound source signal of the jth sensor; N i (ω) is the frequency domain noise signal of the i-th sensor; N j (ω) is the frequency domain noise signal of the jth sensor; The phase transformation weighting function and the maximum likelihood weighting function are weighted and summed to obtain an improved weighting function, specifically: in, is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the weight factor, Q is the directivity factor, R is the space constant, and D is the prior distance.

5. The sound source localization method based on the improved generalized cross-correlation algorithm according to claim 4, characterized in that: The performing of a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay includes: Constructing a generalized cross-correlation function based on the sound source signal and the improved weighting function; wherein, there is one generalized cross-correlation function corresponding to any two sensors; The absolute value operation and peak detection are performed on the generalized cross-correlation function to obtain the time delay, which is specifically: Among them, τ ij is the time delay of collecting the sound source signal between the i-th sensor and the j-th sensor; To find the operation of τ corresponding to the maximum value of the objective function; R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor.

6. A sound source localization method based on an improved generalized cross-correlation algorithm as claimed in claim 5, characterized in that: The constructing of a generalized cross-correlation function according to the sound source signal and the improved weighting function comprises: In the frequency domain, weighting processing is performed on the sound source signal by using the improved weighting function; Perform inverse Fourier transform on the weighted result to obtain the generalized cross-correlation function, which is: Among them, R ij (τ) is the generalized cross-correlation function between the i-th sensor and the j-th sensor; is the improved weighting function corresponding to the i-th sensor and the j-th sensor; is the cross-power spectrum function between the frequency domain sound source signal of the i-th sensor and the frequency domain sound source signal of the j-th sensor.

7. The sound source localization method based on the improved generalized cross-correlation algorithm according to claim 1, wherein: The performing geometric operations in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position includes: Based on the time delay, a set of equations is constructed in the three-dimensional rectangular coordinate system, specifically: Where (x, y, z) are the coordinates of the sound source; R is the distance from the sound source to the origin of the three-dimensional rectangular coordinate system; r1, r2, r3, and r4 are the distances from the sound source to the four sensors respectively; d is the distance from any sensor to the origin; Δτ 12 ,Δτ 13 ,Δτ 14 are the time delays between any sensor and the other three sensors in collecting the sound source signal; c is the speed of sound propagation in the air; Solve the equations to get the sound source position, specifically:

8. A sound source localization device based on an improved generalized cross-correlation algorithm, characterized in that: include: Signal acquisition module, weighting function module, generalized cross-correlation module and geometric operation module; The signal acquisition module is configured to acquire sound source signals through a four-element cross sensor array; wherein the four-element cross sensor array is composed of four sensors located in the same coordinate axis plane of a three-dimensional rectangular coordinate system, wherein two sensors are included on each of the two coordinate axes of the coordinate axis plane, and the two sensors are respectively located on either side of the origin of the three-dimensional rectangular coordinate system, and the four sensors are equidistant from the origin; The weighting function module is used to construct an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function; The generalized cross-correlation module is used to perform a generalized cross-correlation operation based on the sound source signal and the improved weighting function to obtain a time delay; The geometric operation module is used to perform geometric operations in the three-dimensional rectangular coordinate system based on the time delay to obtain the sound source position.

9. A terminal device, characterized in that: The invention comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the sound source localization method based on the improved generalized cross-correlation algorithm according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that include: A stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the sound source localization method based on the improved generalized cross-correlation algorithm according to any one of claims 1 to 7.

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