A method, device, and computer equipment for realizing acoustic wave imaging based on a single FPGA

Abstract

The present invention relates to the field of acoustic wave imaging technology, and particularly discloses a method, apparatus, and computer equipment for implementing acoustic wave imaging based on a single FPGA, comprising collecting acoustic wave signals from a sound source using a microphone array board; processing the acoustic wave signals based on a time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution; processing the acoustic wave image of the first resolution based on a bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution; the second resolution being greater than the first resolution. The above-mentioned method for implementing acoustic wave imaging based on a single FPGA can reduce the computational complexity of acoustic wave imaging by combining a time-delay acoustic wave imaging algorithm with a bilinear interpolation algorithm, thereby achieving the complete function of acoustic wave imaging using a single FPGA, while ensuring the imaging positioning accuracy of the sound.

Description

Technical Field

[0001] The present invention relates to the technical field of acoustic wave imaging, and in particular to a method, device, and computer equipment for implementing acoustic wave imaging based on a single FPGA. Background Art

[0002] Traditional acoustic imaging techniques typically use FPGA (Field Programmable Gate Array) chips to collect and filter acoustic waves, then transmit the data to a dedicated ARM-based processing chip for conversion and calculation, ultimately outputting an acoustic image. However, current acoustic imaging methods suffer from low efficiency, complex hardware connections, high power consumption, and high costs. Summary of the Invention

[0003] Based on this, it is necessary to provide a method, device, and computer equipment for implementing acoustic wave imaging based on a single FPGA to address the problems existing in current acoustic wave imaging methods.

[0004] A method for implementing acoustic wave imaging based on a single FPGA includes collecting acoustic wave signals from a sound source using a microphone array board; processing the acoustic wave signals based on a time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution; and processing the acoustic wave image of the first resolution based on a bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution, wherein the second resolution is greater than the first resolution.

[0005] In one embodiment, before processing the acoustic wave signal based on a time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution, the method further includes preprocessing the acoustic wave signal; the preprocessing includes data integration and filtering conversion.

[0006] In one embodiment, the microphone array board includes multiple microphones, and the processing of the sound wave signal based on the time-delay sound wave imaging algorithm to obtain the sound wave image of the first resolution includes calculating the sound wave delay of the sound wave signal to determine the time delay correction parameters of each of the microphones; performing time delay correction on the sound wave signal based on the time delay correction parameters of each of the microphones; calculating the sound intensity of the sound wave signal to determine the sound intensity of each of the microphones; and arranging and combining the pixel sound intensities of the sound wave signal to form the sound wave image of the first resolution.

[0007] In one embodiment, calculating the acoustic wave delay of the acoustic wave signal and determining the delay correction parameters of each microphone includes:

[0008] t=(x*sin(θ)*cos(φ)+y*cos(θ)*sin(φ)) / c;

[0009] In the formula, t represents the time delay correction parameter of each microphone, x represents the horizontal coordinate of each microphone in the sound wave area to be detected, y represents the vertical coordinate of each microphone in the sound wave area to be detected, θ represents the azimuth angle between the sound source and each microphone, φ represents the pitch angle between the sound source and each microphone, and c represents the speed of sound.

[0010] In one embodiment, after calculating the acoustic wave delay of the acoustic wave signal and determining the delay correction parameters of each microphone, the method further includes converting the delay correction parameters of each microphone into a system clock number of the FPGA.

[0011] In one embodiment, converting the delay correction parameters of each microphone into the system clock number of the FPGA includes:

[0012] t clk =t*fs;

[0013] Where, t clk represents the system clock number of FPGA, t represents the delay correction parameter of each microphone, and fs represents the sampling rate of FPGA.

[0014] In one embodiment, the acoustic wave image of the first resolution is processed based on the bilinear interpolation algorithm to obtain the acoustic wave image of the second resolution, including allocating any target floating-point coordinate in the acoustic wave image of the first resolution to the four integer coordinates closest to the target floating-point coordinate according to a weight; and determining the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate.

[0015] In one embodiment, determining the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate comprises:

[0016] f(i+u,j+v)=(1-u)(1-v)f(i,j)+(1-u)vf(i,j+1)+u(1-v)f(i+1,j)+uvf(i+1,j+1);

[0017] Wherein, (i+u, j+v) represents the coordinates of the floating-point number, f() represents the pixel value, i and j represent the integer part of the floating-point number, u and v represent the decimal part of the floating-point number, (i, j), (i, j+1), (i+1, j), and (i+1, j+1) respectively represent the four integer coordinates closest to the target floating-point coordinate.

[0018] A device for implementing acoustic wave imaging based on a single FPGA includes a microphone array board for collecting acoustic wave signals from a sound source; an FPGA processing module connected to the microphone array board and configured to process the acoustic wave signals based on a time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution, and then process the acoustic wave image of the first resolution based on a bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution.

[0019] In one embodiment, the FPGA processing module includes a data integration unit for performing data integration on the acoustic wave signal; a low-pass filtering unit connected to the data integration unit for performing low-pass filtering on the acoustic wave signal; and a band-pass filtering unit connected to the low-pass filtering unit for performing band-pass filtering on the acoustic wave signal.

[0020] In one embodiment, the FPGA processing module also includes a delay calculation unit, which is connected to the bandpass filtering unit, and is used to perform sound wave delay calculation on the sound wave signal, determine the delay correction parameters of each microphone, and perform delay correction on the sound wave signal based on the delay correction parameters of each microphone; a sound intensity calculation unit, which is connected to the delay calculation unit, and is used to perform sound intensity calculation on the sound wave signal, and determine the sound intensity of each microphone; a pixel point sound intensity arrangement unit, which is connected to the sound intensity calculation unit, and is used to arrange and combine pixel point sound intensities of the sound wave signal to form the sound wave image of the first resolution.

[0021] In one embodiment, the FPGA processing module also includes a bilinear interpolation calculation unit, which is connected to the pixel point sound intensity arrangement unit, and is used to assign any target floating-point coordinate in the sound wave image of the first resolution to the four integer coordinates closest to the target floating-point coordinate according to the weight, and determine the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate.

[0022] In one embodiment, the device further includes a DC-DC power supply integrated module connected to the FPGA processing module for providing working power to the FPGA processing module.

[0023] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for implementing acoustic wave imaging using a single FPGA as described in any of the above embodiments.

[0024] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for implementing acoustic wave imaging using a single FPGA as described in any one of the above embodiments.

[0025] The above-mentioned method for implementing acoustic imaging using a single FPGA uses a microphone array board to collect acoustic signals from a sound source. It then processes these signals using a time-delay acoustic imaging algorithm to form an acoustic image at a first resolution. This image is then processed using a bilinear interpolation algorithm to form an acoustic signal at a second resolution. By combining the time-delay acoustic imaging algorithm with the bilinear interpolation algorithm, the computational complexity of acoustic imaging can be reduced, enabling the full functionality of acoustic imaging to be realized using a single FPGA while ensuring accurate sound imaging and positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the implementation methods of this specification or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the implementation methods or the description of the prior art. Obviously, the drawings described below are only some implementation methods recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0027] Figure 1 It is a structural diagram of an existing acoustic imaging device;

[0028] Figure 2 This is a flow chart of a method for implementing acoustic wave imaging based on a single FPGA in one embodiment of the present application;

[0029] Figure 3 This is a comparison diagram of FPGA resource usage between the time-delay acoustic imaging algorithm and the frequency-domain Fourier transform calculation algorithm. Figure 3 a is a statistical diagram of FPGA resource usage based on the time-delay acoustic imaging algorithm. Figure 3 b is a statistical diagram of FPGA resource usage for Fourier transform calculation based on the frequency domain method;

[0030] Figure 4 This is a schematic diagram comparing an acoustic wave image of a first resolution and an acoustic wave image of a second resolution in one embodiment of the present application, wherein: Figure 4 a is a schematic diagram of an acoustic wave image of the first resolution in one embodiment of the present application, Figure 4 b is a schematic diagram of an acoustic wave image at a second resolution in one embodiment of the present application;

[0031] Figure 5This is a flowchart of a method for obtaining an acoustic wave image of a first resolution based on a time-delay acoustic wave imaging algorithm in one embodiment of the present application;

[0032] Figure 6 This is a schematic diagram of the positions of the area to be detected and the microphone array board in one embodiment of the present application;

[0033] Figure 7 This is a flowchart of a method for obtaining an acoustic wave image of a second resolution based on a bilinear interpolation algorithm in one embodiment of the present application;

[0034] Figure 8 This is a schematic diagram of the structure of a device for implementing acoustic wave imaging based on a single FPGA in one embodiment of the present application;

[0035] Figure 9 This is a schematic diagram of the performance parameters of a device for implementing acoustic wave imaging based on a single FPGA in an aging test in one embodiment of this application, wherein: Figure 9 a is a statistical diagram of current changes in a whole-machine aging test of a device for implementing acoustic wave imaging based on a single FPGA in one embodiment of the present application, Figure 9 b is a statistical diagram of temperature changes during the aging test of a device for implementing acoustic wave imaging based on a single FPGA in one embodiment of the present application;

[0036] Figure 10 This is a structural diagram of the FPGA processing module in one embodiment of the present application;

[0037] Figure 11 This is a schematic structural diagram of a device for implementing acoustic wave imaging based on a single FPGA in another embodiment of the present application;

[0038] Figure 12 This is a schematic diagram of the circuit principle of a DC-DC power supply integrated module in one embodiment of the present application;

[0039] Figure 13 This is a schematic diagram of the system structure for implementing a method for acoustic wave imaging based on a single FPGA in one embodiment of the present application;

[0040] Figure 14 This is a diagram of the internal structure of a computer device in one of the embodiments of this application. DETAILED DESCRIPTION

[0041] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the accompanying drawings. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present disclosure.

[0042] 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 invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0043] Figure 1 This is a schematic diagram of the structure of an existing acoustic imaging device, which includes a microphone array board, a DC-DC power supply, an FPGA chip, a 5SPI Nor flash memory chip, an ARM architecture data processing chip, and a DDR memory chip (Double Data Rate SDRAM). Existing acoustic imaging devices require an FPGA chip and an ARM architecture processing chip to jointly implement the acoustic imaging function. The FPGA chip performs data acquisition or filtering, and then transmits the data to a dedicated processing chip of the ARM architecture for conversion and calculation. The ARM chip is mainly used to perform beamforming and interpolation calculations on the data. This process is relatively cumbersome and inefficient. At the same time, because existing acoustic imaging devices require the use of multiple chips and hardware components, the connection of the entire device becomes complicated, the overall power consumption is high, and the production cost is also high. In addition, in existing acoustic imaging devices, if the functions of the ARM chip are directly transplanted to the FPGA chip, the FPGA resources will be seriously insufficient, and the problem of being unable to implement the complete function of acoustic imaging will occur.

[0044] This application provides a method for realizing acoustic wave imaging based on a single FPGA, which can realize complete acoustic wave imaging function using a single FPGA chip while ensuring the imaging positioning accuracy of sound. Figure 2 This is a flow chart of a method for implementing acoustic wave imaging based on a single FPGA in one embodiment of the present application. In one embodiment, the method for implementing acoustic wave imaging based on a single FPGA may include the following steps S100 to S300.

[0045] Step S100: using a microphone array board to collect sound wave signals from a sound source.

[0046] A microphone array board can be equipped with multiple microphones, which can be arranged regularly or irregularly to form a microphone array. When sound waves generated by a sound source propagate to the microphone array board, each microphone on the microphone array board can collect the sound waves within its pickup range, thereby enabling the microphone array board to collect the sound wave signal from the sound source. In this embodiment, the sound wave signal can include data collected by all microphones on the microphone array board.

[0047] Step S200: Processing the acoustic wave signal based on a time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution.

[0048] There are two commonly used acoustic imaging algorithms: the time-delay acoustic imaging algorithm based on time-domain calculations and the frequency-domain acoustic imaging algorithm based on frequency calculations. Both algorithms essentially aim to compensate for phase differences caused by the different arrival times of acoustic signals at different microphones; the difference lies in the methods used to compensate for these phase differences. The time-delay acoustic imaging algorithm adjusts phase through delay, applying different delays to the signals received by each microphone to achieve phase alignment. This process involves only delay calculations and shift registers, and consumes relatively few FPGA resources. In the frequency domain, the Fourier transform of the signal is performed, applying phase compensation to the signals of the same frequency received by the microphones. This involves complex Fourier transforms and phase compensation multiplications, which consumes significant FPGA resources.

[0049] Figure 3 This is a comparison diagram of FPGA resource usage between the time-delay acoustic imaging algorithm and the frequency-domain Fourier transform calculation algorithm. Figure 3 a is a statistical diagram of FPGA resource usage based on the time-delay acoustic imaging algorithm. Figure 3 b is a statistical diagram of FPGA resource usage based on the frequency domain method for Fourier transform calculation. A targeted comparison of the resource usage of the time-delay acoustic imaging algorithm based on time domain calculation and the frequency domain acoustic imaging algorithm based on frequency calculation in FPGA can be obtained. Figure 3 a and Figure 3 Statistical diagram of b. Comparison Figure 3 a and Figure 3 The utilization rate of FPGA resources (BRAM, DSP) in b is obvious. Figure 3 a is used less frequently.

[0050] Figure 3 a shows the resource occupancy statistics of the FPGA chip that realizes the acoustic imaging function by using the method of realizing acoustic imaging based on a single FPGA provided by this application. Figure 3 b shows the resource usage of the FPGA chip based only on the Fourier transform calculation based on the frequency domain algorithm (no acoustic imaging calculation has been performed, that is, the acoustic imaging function has not been realized). Its FPGA resource utilization rate has obviously exceeded Figure 3 a, if Figure 3 If acoustic imaging is added to the algorithm in step b, the FPGA resources will be severely insufficient. Therefore, the traditional frequency-domain acoustic imaging algorithm cannot fully implement acoustic imaging functions on a single FPGA. The time-delay acoustic imaging algorithm is more suitable for running on FPGA chips.

[0051] In the method for implementing acoustic wave imaging based on a single FPGA provided in the present application, a time-delay acoustic wave imaging algorithm is used to perform time-delay compensation on the phases of different microphones in the acoustic wave signal, and an acoustic wave image of the first resolution is formed based on the data processed by the time-delay acoustic wave imaging algorithm.

[0052] Step S300: Processing the acoustic wave image of the first resolution based on a bilinear interpolation algorithm to obtain an acoustic wave image of the second resolution; the second resolution is greater than the first resolution.

[0053] After forming an acoustic wave image of a first resolution based on the data processed by the time-delay acoustic wave imaging algorithm, the acoustic wave image of the first resolution can be amplified using a bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution. Figure 4 This is a schematic diagram comparing an acoustic wave image of a first resolution and an acoustic wave image of a second resolution in one embodiment of the present application, wherein: Figure 4 a is a schematic diagram of an acoustic wave image of the first resolution in one embodiment of the present application, Figure 4 b is a schematic diagram of a second resolution acoustic wave image in one embodiment of the present application. Using the time-delay acoustic wave imaging algorithm, the collected acoustic wave signal can be processed to form the following Figure 4 The first resolution sound wave image shown in a has a low image resolution. After the first resolution sound wave image is amplified using a bilinear interpolation algorithm, the following can be generated: Figure 4 b shows an acoustic wave image of the second resolution. It can be seen that the bilinear interpolation algorithm can improve the resolution of the acoustic wave image to ensure the image accuracy when acoustic wave imaging is implemented based on a single FPGA.

[0054] The method for implementing acoustic wave imaging based on a single FPGA provided in this application combines a time-delay acoustic wave imaging algorithm and a bilinear interpolation algorithm, which can significantly reduce the amount of calculation in the FPGA chip to ensure that the complete acoustic wave imaging function can be achieved using a single FPGA chip, while also ensuring the image accuracy of the output acoustic wave image.

[0055] In one embodiment, before processing the acoustic wave signal based on the time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of the first resolution, the method may further include the following steps:

[0056] Preprocess the acoustic wave signal; preprocessing includes data integration and filtering conversion.

[0057] Before processing the acoustic signal using the time-delay acoustic imaging algorithm, the acoustic signal can be pre-processed to improve signal quality, extract useful information, and prepare for subsequent analysis or processing. Specifically, data integration of the acoustic signal can be to convert the acoustic signals collected from different microphones into the same sampling rate, quantization accuracy, etc. to ensure consistency of processing. It can also combine the acoustic signals from multiple microphones to improve signal quality or extract spatial information through weighted averaging, maximum value selection, etc. After the data integration of the acoustic signal is completed, the acoustic signal is filtered and converted. Low-pass filtering is used to remove high-frequency noise and reduce random noise and pulse interference. Band-pass filtering is used to selectively allow acoustic signals in a specific frequency range to pass through, so as to eliminate interference from irrelevant frequency bands and reduce the impact of noise.

[0058] By preprocessing the acoustic wave signal, the acoustic wave signal can be converted into a representation suitable for further analysis or application, unnecessary noise can be removed, the quality of the acoustic wave signal can be improved, and more accurate and effective data can be provided for acoustic imaging.

[0059] Figure 5 This is a flow chart of a method for obtaining an acoustic wave image of a first resolution based on a time-delay acoustic wave imaging algorithm in one of the embodiments of the present application. In one embodiment, processing the acoustic wave signal based on the time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution may include the following steps S210 to S240.

[0060] Step S210: Calculate the acoustic wave delay of the acoustic wave signal to determine the delay correction parameters of each microphone.

[0061] The time-delay acoustic imaging algorithm can be used to calculate the time delay of the acoustic wave signal of each microphone to correct the time delay of each microphone. For a sound wave area to be detected, it can be divided into different grid points. The distance between each grid point and each microphone is different, resulting in different times for the sound wave signal to arrive at the microphone. The core of the time-delay acoustic wave imaging algorithm is to accurately time-align the signals received by each microphone, that is, to correct the time domain offset of the signal by introducing an appropriate time delay. In this embodiment, the time domain offset of the signal received by each microphone is corrected using the time delay correction parameter. Through the time delay correction process, the sound wave signals that are misaligned in the time domain can be aligned, thereby achieving phase synchronization. This process can ensure that the sound wave signals from the sound source can be superimposed in phase at each microphone, significantly enhancing the coherence of the signal. Ultimately, based on this coherence enhancement effect, it can be ensured that the spatial distribution of the sound source can be accurately reconstructed in subsequent processing.

[0062] To achieve precise alignment of acoustic signals, a specific set of delay correction parameters can be assigned to each point within the target area. When the sound source is located at a certain point, the acoustic signal received by the microphone is corrected according to the delay parameters corresponding to that point. This effectively achieves in-phase superposition of the acoustic signals, resulting in the strongest acoustic energy concentration at that point.

[0063] For example, Figure 6 This is a schematic diagram of the position of the area to be detected and the microphone array board in one embodiment of the present application. A sound source is located at point A in the area to be detected. At the same time, the area to be detected includes an array formed by multiple microphone array boards, and the array includes array element 1, array element 2, ..., array element M. Figure 6 As shown, the azimuth angle between point A and the microphone in array element 1 may be θ, and the elevation angle between point A and the microphone in array element 1 may be φ. In this embodiment, the azimuth angle θ may range from -37.8° to 37.8°, and the elevation angle φ may range from -21° to 21°.

[0064] In one embodiment, calculating the acoustic wave delay of the acoustic wave signal and determining the delay correction parameters of each microphone may include the following calculation method:

[0065] t=(x*sin(θ)*cos(φ)+y*cos(θ)*sin(φ)) / c;

[0066] In the formula, t represents the delay correction parameter for each microphone, x represents the horizontal coordinate of each microphone in the sound wave area to be detected, y represents the vertical coordinate of each microphone in the sound wave area to be detected, θ represents the azimuth angle between the sound source and each microphone, φ represents the pitch angle between the sound source and each microphone, and c represents the speed of sound. In the above formula, t is in seconds, and the speed of sound c = 345 m / s.

[0067] Step S220: performing time delay correction on the sound wave signal based on the time delay correction parameters of each microphone.

[0068] By using the above steps to calculate the time delay of the sound wave signal collected by the microphone in each array element from the sound source at point A, the time delay correction parameters corresponding to each microphone can be determined. Then, the time delay correction parameters corresponding to each microphone can be used to perform time delay correction on the sound wave signal, so that the sound wave signals collected by the microphone in each array element are accurately aligned in phase.

[0069] Step S230: Calculate the sound intensity of the sound wave signal to determine the sound intensity of each microphone.

[0070] Step S240: performing pixel-wise sound intensity permutations on the acoustic wave signal to form an acoustic wave image of a first resolution.

[0071] After the delay correction of the sound wave signal is realized, the corresponding sound intensity value of each microphone can be calculated according to the in-phase superposition sound wave signal received by each microphone for its position. The pixel point sound intensity permutation and combination calculation is performed based on the corresponding sound intensity value of each microphone. Specifically, the sound intensity value can be assigned to the virtual pixel point in the two-dimensional or three-dimensional space. This process can reversely determine the direction of the sound source based on the geometric layout of the microphone array board and the time difference of the sound wave reaching each microphone (wherein, the time difference can be determined based on the time delay calculation in the above steps). The sound intensity value of each pixel point is mapped to a grayscale or color intensity to form a sound wave image of the first resolution. Among them, the area with higher sound intensity value in the sound wave image can appear as a brighter or darker area in the image, and the area with lower sound intensity value in the sound wave image appears as a darker or lighter area in the image. As Figure 3 a and Figure 3 As shown in b, the area with higher sound intensity values ​​in the acoustic wave image is darker in color, and the area with lower sound intensity values ​​in the acoustic wave image is brighter in color.

[0072] In one embodiment, after calculating the acoustic wave delay of the acoustic wave signal and determining the delay correction parameters of each microphone, the method may further include the following steps:

[0073] Convert the delay correction parameters of each microphone into the system clock number of the FPGA.

[0074] By converting the delay correction parameters of each microphone into the system clock number of the FPGA, the delay correction parameters can be kept consistent with the system clock, ensuring that subsequent processing steps can work correctly and synchronously.

[0075] In one embodiment, a method for converting the delay correction parameters of each microphone into the number of system clocks of the FPGA may be:

[0076] t clk =t*fs;

[0077] Where, t clk Where fs = 192000, it represents the FPGA system clock rate, t represents the delay correction parameter of each microphone, and fs represents the FPGA sampling rate.

[0078] Figure 7 This is a flow chart of a method for obtaining an acoustic wave image of a second resolution based on a bilinear interpolation algorithm in one embodiment of the present application. In one embodiment, the acoustic wave image of a first resolution is processed based on the bilinear interpolation algorithm, and obtaining the acoustic wave image of the second resolution may include the following steps S310 to S320.

[0079] Step S310: for any target floating-point coordinate in the acoustic wave image of the first resolution, the target floating-point coordinate is allocated to four integer coordinates closest to the target floating-point coordinate according to a weight.

[0080] Step S320: Determine the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate.

[0081] A bilinear interpolation algorithm can be used to smoothly magnify an acoustic image at a first resolution to obtain an acoustic image at a second resolution. The bilinear interpolation algorithm can be used to estimate the value of any point between two known data points in the acoustic image at the first resolution, thereby estimating the color value of non-integer pixel positions in the acoustic image at the first resolution.

[0082] Specifically, a floating-point coordinate (i+u, j+v) in the acoustic wave image of the first resolution can be distributed to the four integer coordinates closest to it according to the weight, and then the pixel value of the floating-point coordinate can be obtained by the pixel values ​​of these four integer coordinates. Among them, a floating-point number can refer to a non-integer point between two known data points. Floating-point numbers are a format of data, which represents the composition of the data and contains two parts, an integer and a decimal. The core of smoothly amplifying the acoustic wave image of the first resolution based on the bilinear interpolation algorithm is to perform an interpolation calculation in the x and y directions respectively, so as to obtain the value of the floating-point coordinate. In this embodiment, the farther the distance, the smaller the integer coordinate weight of the floating-point coordinate (i+u, j+v).

[0083] In one embodiment, determining the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate may include the following calculation method:

[0084] f(i+u,j+v)=(1-u)(1-v)f(i,j)+(1-u)vf(i,j+1)+u(1-v)f(i+1,j)+uvf(i+1,j+1);

[0085] Wherein, (i+u,j+v) can represent the coordinates of a floating-point number, f() can represent a pixel value, i and j can represent the integer part of the floating-point number, u and v can represent the decimal part of the floating-point number, and (i,j), (i,j+1), (i+1,j), and (i+1,j+1) can respectively represent the four integer coordinates closest to the target floating-point coordinates.

[0086] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times. The order of execution of these steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

[0087] Based on the description of the above-mentioned method embodiment for realizing acoustic wave imaging based on a single FPGA, the present disclosure also provides a device for realizing acoustic wave imaging based on a single FPGA. The device may include a device (including a distributed system), software (application), modules, components, servers, clients, etc. using the method described in the embodiments of this specification and a device combined with necessary implementation hardware. Based on the same innovative concept, the device in one or more embodiments provided in the embodiments of the present disclosure is as described in the following embodiments. Since the implementation scheme and method for solving the problem of the device are similar, the implementation of the specific device in the embodiments of this specification can refer to the implementation of the aforementioned method, and the repetitions will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0088] This application also provides a device for realizing acoustic wave imaging based on a single FPGA. Figure 8 This is a structural diagram of an apparatus for implementing acoustic wave imaging based on a single FPGA in one of the embodiments of the present application. In one embodiment, the apparatus for implementing acoustic wave imaging based on a single FPGA may include a microphone array board 100 and an FPGA processing module 200.

[0089] The microphone array board 100 can be used to collect sound wave signals from a sound source. The FPGA processing module 200 can be connected to the microphone array board 100. Specifically, the FPGA processing module 200 and the microphone array board 100 can be connected via a data connection cable. The microphone array board 100 can be provided with multiple microphones. The microphone array board can collect sound wave signals from a sound source. In this embodiment, the sound wave signals may include data collected by all microphones on the microphone array board.

[0090] The FPGA processing module 200 can be used to process the acoustic wave signal based on the time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution, and to process the acoustic wave image of the first resolution based on the bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution. The FPGA processing module 200 uses the time-delay acoustic wave imaging algorithm to perform time delay compensation on the phases of different microphones in the acoustic wave signal, and forms an acoustic wave image of a first resolution based on the data processed by the time-delay acoustic wave imaging algorithm. After forming the acoustic wave image of the first resolution based on the data processed by the time-delay acoustic wave imaging algorithm, the bilinear interpolation algorithm can be used to amplify the acoustic wave image of the first resolution to obtain an acoustic wave image of a second resolution.

[0091] In some embodiments, the FPGA processing module 200 may transmit the sound wave pattern at the second resolution to an external device via a sound wave output interface data connection line.

[0092] The device for implementing acoustic wave imaging based on a single FPGA provided by the present application greatly reduces the amount of calculation in the FPGA chip by combining the time-delay acoustic wave imaging algorithm and the bilinear interpolation algorithm. In addition, compared with the traditional frequency-domain acoustic wave imaging algorithm, the improved time-delay acoustic wave imaging algorithm used in the present application greatly reduces the resources occupied by the FPGA, making it more suitable for running on the FPGA chip without losing the imaging positioning accuracy of the sound, so that the acoustic wave imaging algorithm can be implemented in a single FPGA chip. The above-mentioned device for implementing acoustic wave imaging based on a single FPGA can ensure that the acoustic wave imaging function can run efficiently on a single FPGA chip through the coordinated optimization design of the software algorithm and the hardware architecture, and can also improve the quality of acoustic wave imaging. In addition, the integrated single-chip device can improve the processing speed and efficiency of acoustic wave imaging and reduce the time for data processing and conversion.

[0093] refer to Figure 1 and Figure 8 It can be seen that compared Figure 1 Compared with existing acoustic wave shaping devices, the device for implementing acoustic wave imaging based on a single FPGA provided by this application reduces one ARM chip, and a single FPGA chip can realize the complete acoustic wave imaging function. By integrating the functions that originally required the FPGA chip and the ARM architecture processing chip to be completed together into a single FPGA chip for operation, the number of hardware components and the complexity of the connection can be reduced, and the number of required hardware components can be reduced, thereby simplifying the hardware structure of the entire device. Simpler hardware connections and the number of components can also make the device for implementing acoustic wave imaging based on a single FPGA provided by this application easier to integrate into a larger system and more convenient to maintain. In addition, the device provided by this application uses a single-chip design, which requires fewer chips and a simpler assembly process, thereby also reducing material and production costs.

[0094] Figure 9 This is a schematic diagram of the performance parameters of a device for implementing acoustic wave imaging based on a single FPGA in an aging test in one embodiment of this application, wherein: Figure 9 a is a statistical diagram of current changes in a whole-machine aging test of a device for implementing acoustic wave imaging based on a single FPGA in one embodiment of the present application, Figure 9 b is a statistical diagram of temperature changes during the aging test of the entire device for implementing acoustic wave imaging based on a single FPGA in one of the embodiments of the present application. Figure 9 a shows the current change of the whole device based on a single FPGA for acoustic imaging provided by this application after aging for 2 hours at a power supply voltage of 5V. Figure 9 It can be seen from a that after 2 hours of aging, the current of the whole machine is stabilized at 0.6 amperes. According to the power calculation formula P=UI, it can be calculated that the whole machine power consumption of the device for realizing acoustic wave imaging based on a single FPGA provided by this application is 3 watts, which is significantly lower than the whole machine power consumption of 7 watts of similar products in the industry.

[0095] Figure 9 b shows the temperature change of the whole device for acoustic imaging based on a single FPGA provided by this application after aging for 2 hours at a power supply voltage of 5V. Figure 9 As shown in Figure b, after 2 hours of aging, the entire device temperature stabilized at 70 degrees Celsius, with no significant fluctuations. The device temperature rise was within a reasonable range and relatively stable, indicating that the entire device was operating relatively stably. This indicates that the single-FPGA-based acoustic imaging device provided in this application can achieve reliable acoustic imaging after 2 hours of aging.

[0096] Combine Figure 9 a and Figure 9 As can be seen, compared to traditional acoustic imaging devices, the single-FPGA acoustic imaging device provided in this application can reduce overall system power consumption due to its simplified hardware configuration and low-power design. Compared to traditional multi-chip solutions, it is more energy-efficient and operates more stably and reliably. Lower power consumption also reduces energy consumption and heat generation, contributing to a more environmentally friendly system.

[0097] Figure 10 This is a structural diagram of the FPGA processing module in one embodiment of the present application. In one embodiment, the FPGA processing module 200 may include a data integration unit 210, a low-pass filtering unit 220 and a band-pass filtering unit 230.

[0098] The data integration unit 210 can be used to integrate the sound wave signals. The microphone array board 100 can transmit the sound wave signals collected from the sound source to the data integration unit 210, and the data integration unit 210 can integrate the sound wave signals. The data integration operation can convert the sound wave signals collected from different microphones to the same sampling rate and quantization accuracy to ensure processing consistency. It can also combine the sound wave signals from multiple microphones to improve signal quality or extract spatial information through weighted averaging, maximum value selection, etc.

[0099] The low-pass filter unit 220 can be connected to the data integration unit 210 and can be used to perform low-pass filtering on the acoustic signal. The data integration unit 210 can transmit the acoustic signal after data integration to the low-pass filter unit 220, which performs low-pass filtering on the acoustic signal. Low-pass filtering can remove high-frequency noise in the acoustic signal, thereby reducing random noise and pulse interference in the acoustic signal.

[0100] The bandpass filter unit 230 can be connected to the low-pass filter unit 220 and can be used to perform bandpass filtering on the acoustic signal. The low-pass filter unit 220 can transmit the acoustic signal that has completed the low-pass filtering to the bandpass filter unit 230, which then performs bandpass filtering on the acoustic signal. Bandpass filtering can selectively allow acoustic signals within a specific frequency range to pass through, thereby eliminating interference from irrelevant frequency bands on the acoustic signal and reducing the impact of noise.

[0101] Before using the time-delay acoustic imaging algorithm to process the acoustic wave signal, the above-mentioned device first uses the data integration unit 210, the low-pass filtering unit 220 and the band-pass filtering unit 230 to pre-process the acoustic wave signal. This can convert the acoustic wave signal into a representation suitable for further analysis or application, remove unnecessary noise, improve the quality of the acoustic wave signal, extract useful information, and provide more accurate and effective data for realizing acoustic wave imaging.

[0102] In one embodiment, see Figure 10 The FPGA processing module 200 may further include a time delay calculation unit 240 , a sound intensity calculation unit 250 , and a pixel point sound intensity arrangement unit 260 .

[0103] The delay calculation unit 240 can be connected to the bandpass filtering unit 230. The delay calculation unit 240 can be used to calculate the sound wave delay of the sound wave signal, determine the delay correction parameters of each microphone, and perform delay correction on the sound wave signal based on the delay correction parameters of each microphone.

[0104] In one embodiment, the delay calculation unit 240 performs sound wave delay calculation on the sound wave signal and may perform the following calculation method when determining the delay correction parameters of each microphone:

[0105] t=(x*sin(θ)*cos(φ)+y*cos(θ)*sin(φ)) / c;

[0106] In the formula, t represents the delay correction parameter for each microphone, x represents the horizontal coordinate of each microphone in the sound wave area to be detected, y represents the vertical coordinate of each microphone in the sound wave area to be detected, θ represents the azimuth angle between the sound source and each microphone, φ represents the pitch angle between the sound source and each microphone, and c represents the speed of sound. In the above formula, t is in seconds, and the speed of sound c = 345 m / s.

[0107] The delay calculation unit 240 uses the above-mentioned calculation method to perform delay calculation on the sound wave signals of the sound source collected by each microphone, and can determine the delay correction parameters corresponding to each microphone, so that the delay correction parameters corresponding to each microphone can be used to perform delay correction on the sound wave signals, so that the sound wave signals collected by each microphone can be accurately aligned in phase.

[0108] Sound intensity calculation unit 250 can be connected to delay calculation unit 240 and is used to calculate the sound intensity of the sound wave signal and determine the sound intensity of each microphone. After correcting the delay of the sound wave signal, sound intensity calculation unit 250 can calculate the sound intensity value corresponding to each microphone based on the in-phase superposition of the received sound wave signals at each microphone position.

[0109] The pixel point sound intensity arrangement unit 260 can be connected to the sound intensity calculation unit 250, and the pixel point sound intensity arrangement unit 260 can be used to arrange and combine the sound wave signals by pixel point sound intensity to form a sound wave image of the first resolution. The pixel point sound intensity arrangement unit 260 can perform pixel point sound intensity arrangement and combination calculation based on the sound intensity value corresponding to each microphone. Specifically, the pixel point sound intensity arrangement unit 260 can assign the sound intensity value to the virtual pixel points in the two-dimensional or three-dimensional space. This process can reversely determine the direction of the sound source based on the geometric layout of the microphone array board and the time difference between the sound waves reaching each microphone (wherein, the time difference can be determined based on the time delay calculation in the above steps). The sound intensity value of each pixel point is mapped to a grayscale or color intensity to form a sound wave image of the first resolution.

[0110] In one embodiment, see Figure 10 , the FPGA processing module 200 may further include a bilinear interpolation calculation unit 270 .

[0111] The bilinear interpolation calculation unit 270 can be connected to the pixel point sound intensity arrangement unit 260. The bilinear interpolation calculation unit 270 can be used to assign the target floating-point coordinate to the four integer coordinates closest to the target floating-point coordinate according to the weight for any target floating-point coordinate in the sound wave image of the first resolution, and determine the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate.

[0112] The bilinear interpolation calculation unit 270 can smoothly amplify the acoustic wave image of the first resolution based on the bilinear interpolation algorithm to obtain the acoustic wave image of the second resolution. Specifically, the bilinear interpolation calculation unit 270 can distribute a floating-point coordinate (i+u, j+v) in the acoustic wave image of the first resolution to the four integer coordinates closest to it according to the weight, and then obtain the pixel value of the floating-point coordinate through the pixel values ​​of these four integer coordinates. Among them, a floating-point number can refer to a non-integer point between two known data points. A floating-point number is a format of data that represents the composition of the data and contains two parts: an integer and a decimal.

[0113] In one embodiment, the bilinear interpolation calculation unit 270 may perform the following calculation method when determining the pixel value of the target floating-point coordinate based on the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate:

[0114] f(i+u,j+v)=(1-u)(1-v)f(i,j)+(1-u)vf(i,j+1)+u(1-v)f(i+1,j)+uvf(i+1,j+1);

[0115] Wherein, (i+u,j+v) can represent the coordinates of a floating-point number, f() can represent a pixel value, i and j can represent the integer part of the floating-point number, u and v can represent the decimal part of the floating-point number, and (i,j), (i,j+1), (i+1,j), and (i+1,j+1) can respectively represent the four integer coordinates closest to the target floating-point coordinates.

[0116] The device for implementing acoustic wave imaging based on a single FPGA provided in this application also has the advantage of high integration. By designing a highly integrated chip for the FPGA processing module 200 and integrating multiple functional units into a single FPGA chip, dependence on external components can be reduced.

[0117] Figure 11 This is a structural diagram of an apparatus for implementing acoustic wave imaging based on a single FPGA in another embodiment of the present application. In one embodiment, the apparatus for implementing acoustic wave imaging based on a single FPGA may further include a DC-DC power supply integrated module 300.

[0118] The DC-DC power supply integrated module 300 may be connected to the FPGA processing module 200 , and the DC-DC power supply integrated module 300 may be used to provide operating power to the FPGA processing module 200 . Figure 12 This is a schematic diagram of the circuit principle of a DC-DC power supply integrated module in one embodiment of the present application. In this embodiment, the DC-DC power supply integrated module 300 is designed as follows Figure 12 The circuit shown can integrate the power inductor in a traditional DC-DC power supply circuit into the DC-DC chip, thereby greatly reducing the PCB area used in the circuit design, reducing the complexity of the PCB design, and also reducing the electromagnetic radiation problem caused by the external power inductor.

[0119] In one embodiment, Figure 11 As shown, the device for implementing acoustic wave imaging based on a single FPGA may further include a DDR memory chip 400 , which may be used to store and transmit data processed in the device for implementing acoustic wave imaging based on a single FPGA.

[0120] It should be understood that the various embodiments of the above-mentioned methods, systems, etc. in this specification are described in a progressive manner. The same / similar parts between the various embodiments can be referred to in detail. Each embodiment focuses on the differences from other embodiments. For related parts, please refer to the descriptions of other method embodiments.

[0121] Figure 13 This is a schematic diagram of the system structure for implementing a method for acoustic imaging based on a single FPGA in one embodiment of this application. Figure 13 System S00 for implementing acoustic imaging based on a single FPGA may include a processing component S20, which further includes one or more processors, and a memory resource represented by memory S22 for storing instructions executable by processing component S20, such as application programs. The application programs stored in memory S22 may include one or more instructions, with each module corresponding to a set of instructions. Furthermore, processing component S20 is configured to execute the instructions to perform the above-described method for implementing acoustic imaging based on a single FPGA.

[0122] The system S00 for implementing acoustic imaging based on a single FPGA may further include a power supply assembly S24 configured to perform power management for the system S00, a wired or wireless network interface S26 configured to connect the system S00 to a network, and an input / output (I / O) interface S28. The system S00 may be operated based on an operating system stored in the memory S22, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, or the like.

[0123] In an exemplary embodiment, a computer-readable storage medium including instructions is further provided, such as a memory S22 including instructions. The instructions can be executed by a processor of a system S00 for implementing acoustic imaging based on a single FPGA to perform the above method. The storage medium can be a computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0124] In an exemplary embodiment, a computer program product is further provided. The computer program product includes instructions. The instructions can be executed by a processor of the system S00 for implementing acoustic wave imaging based on a single FPGA to implement the above method.

[0125] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 14 As shown, Figure 14 This is a diagram of the internal structure of a computer device in one of the embodiments of the present application. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store user- and task-related data used in the above-mentioned method for implementing acoustic wave imaging based on a single FPGA. The network interface of the computer device is used to communicate with an external terminal via a network connection. The computer program is executed by the processor to implement a method for implementing acoustic wave imaging based on a single FPGA.

[0126] Those skilled in the art will understand that Figure 14The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0127] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0128] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences between the other embodiments. In particular, the hardware + program embodiments are described briefly because they are generally similar to the method embodiments. For relevant portions, refer to the description of the method embodiments.

[0129] It should be noted that the aforementioned devices, electronic devices, servers, etc., according to the description of the method embodiments, may also include other implementation methods. For specific implementation methods, reference can be made to the description of the relevant method embodiments. At the same time, new embodiments formed by combining the features of various method, device, equipment, and server embodiments still fall within the scope of implementation covered by this disclosure and are not described in detail here.

[0130] Throughout this specification, references to terms such as "some embodiments," "other embodiments," and "desired embodiments" indicate that a particular feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. Although these terms are used interchangeably throughout this specification, they do not necessarily refer to the same embodiment or example.

[0131] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] The above-described embodiments merely represent several implementations of the present invention. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. A method for realizing acoustic wave imaging based on a single FPGA, characterized in that: include: Use the microphone array board to collect the sound wave signal of the sound source; Processing the acoustic wave signal based on a time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution; Processing the acoustic wave image of the first resolution based on a bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution; the second resolution is greater than the first resolution; The microphone array board includes a plurality of microphones, and the processing of the acoustic wave signal based on the time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution includes: Performing sound wave delay calculation on the sound wave signal to determine the delay correction parameters of each microphone; Performing time delay correction on the sound wave signal based on the time delay correction parameters of each of the microphones; Calculating the sound intensity of the sound wave signal to determine the sound intensity of each microphone; The acoustic wave signal is subjected to pixel point sound intensity arrangement and combination to form the acoustic wave image of the first resolution.

2. The method for realizing acoustic wave imaging based on a single FPGA according to claim 1, characterized in that: Before processing the acoustic wave signal based on the time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of the first resolution, the method further includes: The acoustic wave signal is preprocessed; the preprocessing includes data integration and filtering conversion.

3. The method for realizing acoustic wave imaging based on a single FPGA according to claim 1, wherein: Calculating the acoustic wave delay of the acoustic wave signal to determine the delay correction parameters of each microphone includes: t=(x*sin(θ)*cos(φ)+y*cos(θ)*sin(φ)) / c; In the formula, t represents the time delay correction parameter of each microphone, x represents the horizontal coordinate of each microphone in the sound wave area to be detected, y represents the vertical coordinate of each microphone in the sound wave area to be detected, θ represents the azimuth angle between the sound source and each microphone, φ represents the pitch angle between the sound source and each microphone, and c represents the speed of sound.

4. The method for realizing acoustic wave imaging based on a single FPGA according to claim 1, wherein: After calculating the acoustic wave delay of the acoustic wave signal and determining the delay correction parameters of each microphone, the method further includes: The time delay correction parameters of each microphone are converted into the system clock number of the FPGA.

5. The method for realizing acoustic wave imaging based on a single FPGA according to claim 1, wherein: Converting the delay correction parameters of each microphone into the system clock number of the FPGA includes: t clk =t*fs; Where, t clk represents the system clock number of FPGA, t represents the delay correction parameter of each microphone, and fs represents the sampling rate of FPGA.

6. The method for realizing acoustic wave imaging based on a single FPGA according to claim 1, wherein: Processing the acoustic wave image of the first resolution based on a bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution includes: For any target floating-point coordinate in the acoustic wave image of the first resolution, assigning the target floating-point coordinate to four integer coordinates closest to the target floating-point coordinate according to a weight; The pixel value of the target floating-point coordinate is determined according to the pixel values ​​respectively corresponding to the four integer coordinates closest to the target floating-point coordinate.

7. The method for realizing acoustic wave imaging based on a single FPGA according to claim 6, characterized in that: Determining the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate includes: f(i+u,j+v)=(1-u)(1-v)f(i,j)+(1-u)vf(i,j+1)+u(1-v)f(i+1,j)+uvf(i+1,j+1); Wherein, (i+u, j+v) represents the coordinates of the floating-point number, f( ) represents the pixel value, i and j represent the integer part of the floating-point number, u and v represent the decimal part of the floating-point number, (i, j), (i, j+1), (i+1, j), and (i+1, j+1) respectively represent the four integer coordinates closest to the target floating-point coordinate.

8. A device for realizing acoustic wave imaging based on a single FPGA, characterized in that: include: Microphone array board, used to collect sound wave signals from sound sources; an FPGA processing module, connected to the microphone array board, and configured to process the acoustic wave signal based on a time-delay acoustic wave imaging algorithm to obtain an acoustic wave image of a first resolution, and process the acoustic wave image of the first resolution based on a bilinear interpolation algorithm to obtain an acoustic wave image of a second resolution; The FPGA processing module includes: a time delay calculation unit, configured to calculate the time delay of the sound wave signal, determine the time delay correction parameters of each of the microphones, and perform time delay correction on the sound wave signal based on the time delay correction parameters of each of the microphones; a sound intensity calculation unit, connected to the time delay calculation unit, for performing sound intensity calculation on the sound wave signal to determine the sound intensity of each microphone; The pixel point sound intensity arrangement unit is connected to the sound intensity calculation unit and is used to arrange and combine the pixel point sound intensities of the sound wave signal to form the sound wave image of the first resolution.

9. The device for realizing acoustic wave imaging based on a single FPGA according to claim 8, characterized in that: The FPGA processing module includes: a data integration unit, configured to perform data integration on the acoustic wave signal; a low-pass filtering unit, connected to the data integration unit, and configured to perform low-pass filtering on the sound wave signal; The bandpass filter unit is connected to the low-pass filter unit and is used to perform bandpass filtering on the sound wave signal.

10. The device for realizing acoustic wave imaging based on a single FPGA according to claim 9, characterized in that: The FPGA processing module also includes: A bilinear interpolation calculation unit is connected to the pixel point sound intensity arrangement unit, and is used to assign any target floating-point coordinate in the acoustic wave image of the first resolution to the four integer coordinates closest to the target floating-point coordinate according to a weight, and determine the pixel value of the target floating-point coordinate according to the pixel values ​​corresponding to the four integer coordinates closest to the target floating-point coordinate.

11. The device for implementing acoustic wave imaging based on a single FPGA according to claim 8, characterized in that: The device further comprises: A DC-DC power supply integrated module is connected to the FPGA processing module and is used to provide working power to the FPGA processing module.

12. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for implementing acoustic wave imaging using a single FPGA as described in any one of claims 1 to 7 are implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for implementing acoustic wave imaging using a single FPGA as described in any one of claims 1 to 7 are implemented.

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