Wavefield reconstruction method and apparatus for wave signal, and program product and storage medium

Abstract

Disclosed are a wavefield reconstruction method and apparatus for a wave signal, and a program product and a storage medium, which relate to the technical field of scientific computing. During the process of wavefield reconstruction of a wave signal, on the basis of a first wavefield corresponding to frequency point information of a batch for which a wavefield has been solved, the input of a wave equation is set, so as to solve a second wavefield corresponding to frequency points of any second batch other than the first batch. The flexible setting of an initial wavefield value during a wave-equation solving process is implemented, and the rationality of setting the initial wavefield value is ensured, such that the input of the wave equation is closer to a second wavefield corresponding to frequency point information of a second batch, and thus the number of iterations during a wavefield solving process can be reduced, thereby improving the reconstruction efficiency, and reducing the consumption of computing resources. In addition, during a wavefield reconstruction process, a plurality of pieces of frequency point information corresponding to a target object are further divided into batches, so as to implement parallel solution of all frequency point information in the same batch, such that the reconstruction efficiency can be improved, and the consumption of computing resources can be reduced.

Description

Wavefield reconstruction methods, devices, program products, and storage media for wave signals

[0001] This application claims priority to Chinese Patent Application No. 202510153721.4, filed on February 10, 2025, entitled “Method, Apparatus, Program Product and Storage Medium for Wave Field Reconstruction of Wave Signal”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of scientific computing technology, and in particular to a method, apparatus, program product, and storage medium for wave field reconstruction of wave signals. Background Technology

[0003] The wave equation describes the wave phenomenon of wave signals (which can be called the wave field). Solving the wave equation involves using frequency domain or time domain algorithms to predict the wave field after the wave signal is reflected by a scene or object. Based on this reflected wave field, the internal structure of the scene or object, or the surface texture of the object, can be reconstructed.

[0004] Solving the wave equation typically involves multiple iterations to obtain the reflected wave field. During these iterations, fixed initial values ​​are usually used. However, improper initial value settings will increase the number of iterations, reduce the efficiency of reconstructing internal structures or surface textures, and increase the computational resources consumed in solving the wave equation. Summary of the Invention

[0005] This application provides a wave field reconstruction method, apparatus, program product, and storage medium for wave signals, so as to reduce the number of iterations in the wave field solving process, improve reconstruction efficiency, and reduce the consumption of computing resources.

[0006] Firstly, this application provides a wavefield reconstruction method for wave signals. During the wavefield reconstruction process, information about the wave signal used to detect the structure of a target object is acquired. Multiple frequency points corresponding to the target object are determined based on the wave signal information. These multiple frequency points are decomposed into multiple batches of frequency points. For the first batch of frequency points solved in the multiple batches, a preset wavefield is used as the input and output of the wave equation to solve for the wavefield corresponding to the first batch of frequency points. For any other second batch of frequency points besides the first batch, the first wavefield corresponding to the batch whose wavefield has been solved according to the wave equation is acquired, and the first wavefield is used as the input of the wave equation to solve for the second batch of frequency points. The wavefield of the reflected wave of the wave signal is obtained through the wavefield corresponding to the frequency points of each batch in the multiple batches, and the structure of the target object is determined based on the wavefield of the reflected wave.

[0007] Based on the first aspect, when solving the wave equation using multiple batches of frequency points, the first wave field corresponding to the frequency points of the batches whose wave fields have been solved is used as the input for solving the wave equations corresponding to the frequency points of other batches. This allows the second wave field corresponding to the frequency points of other batches to be solved. In this way, the initial wave field value can be set based on the wave field corresponding to the frequency points of the solved batches, instead of starting the iteration from a preset wave field, such as the zero wave field, for each batch. This reduces the number of iterations in the wave field solving process, improves reconstruction efficiency, and reduces the computational resources consumed.

[0008] In one alternative implementation, the wave equation is solved using a convergent Born series (CBS).

[0009] Thus, by using CBS iterative solution to the wave equation, dispersion error is reduced, thereby improving the reliability of the reconstructed wave field and ensuring the accuracy of the final target object's structure.

[0010] In one optional implementation, adjacent frequency information in each batch of multiple batches is spaced m times apart, where m is the total number of batches and m is an integer greater than or equal to 2.

[0011] Based on this optional implementation method, in the process of decomposing multiple frequency points into multiple batches of frequency points, according to the number of batches, the frequency points in the multiple frequency point information that are separated by a number of batches are divided into the same batch. Since the frequencies between adjacent frequency points in the multiple frequency point information are similar, the frequency point information with similar frequency values ​​can be decomposed into different batches by means of interval sampling, so that subsequent batches can use the wavefield corresponding to the frequency point information with similar frequency values ​​in the previous batch, ensuring the rationality of the initial wavefield value setting.

[0012] In one alternative implementation, for each of multiple batches, the wavefield similarity between different frequency points in each batch is less than a similarity threshold.

[0013] Based on this optional implementation method, during the batch division process, frequency information in the current batch can be selected from multiple unsolved frequency information based on the wave field corresponding to each frequency information in the previous batch, ensuring that the wave field similarity between different frequency points in each batch is less than the similarity threshold, thereby ensuring the rationality of the initial wave field value setting.

[0014] In one optional implementation, after decomposing multiple frequency point information into multiple batches of frequency point information, for the first batch of frequency point information solved in the multiple batches, a preset wave field is used as the input to the wave equation, and the wave equation is solved iteratively. During the iteration process, if the intermediate value corresponding to the first batch of frequency points meets the preset wave field requirements, the frequency point information of any second batch other than the first batch in the multiple batches is obtained, and the step of obtaining the first wave field corresponding to the frequency point information of the batch whose wave field has been solved according to the wave equation is executed. The preset wave field requirements include: the iteration residual is less than or equal to a residual threshold, or the number of iterations is greater than or equal to a threshold.

[0015] Based on this optional implementation, given the intermediate wavefield corresponding to the frequency information of the current batch, the wavefield solution for the next batch can begin ahead of time. This increases the parallelism of the computation, thereby reducing the wavefield solution time and improving its efficiency.

[0016] In one alternative implementation, after decomposing multiple frequency point information into multiple batches of frequency point information, for the first batch of frequency point information solved in the multiple batches, a preset wave field is used as the input of the wave equation to iteratively solve the wave equation; during the iteration process, if the iteration process converges, the frequency point information of any second batch other than the first batch in the multiple batches is obtained, and the step of obtaining the first wave field corresponding to the frequency point information of the batch whose wave field has been solved according to the wave equation is executed.

[0017] Based on this optional implementation, for all batches except the first batch, the wavefield corresponding to the frequency information of the previously solved batch is used as the initial wavefield for the current batch. This allows for flexible setting of the initial wavefield during the wave equation solution process and ensures its appropriateness, making the wave equation input closer to the second wavefield corresponding to the frequency information of the second batch. This reduces the number of iterations in the wavefield solution process, improves reconstruction efficiency, and reduces computational resource consumption.

[0018] In one alternative implementation, the first wave field includes: the wave field corresponding to the frequency information of the batch of wave fields that have been solved according to the wave equation.

[0019] In this way, the first wave field can be obtained quickly, reducing the wave field solution time and improving the wave field solution efficiency.

[0020] In one alternative implementation, the first wave field includes: the interpolation result of the wave field corresponding to the frequency information of the batch of wave fields that have been solved according to the wave equation.

[0021] In this optional implementation, the first wavefield is determined based on the interpolation results of the wavefield corresponding to the frequency information of the batches whose wavefields have been solved. This can improve the matching degree between the first wavefield and the mid-frequency information of the second batch, thereby ensuring the rationality of the initial wavefield value setting.

[0022] In one optional implementation, the first wavefield includes: an intermediate wavefield corresponding to the frequency information of the batch of wavefields solved according to the wave equation. The intermediate wavefield indicates an intermediate value during the iterative solution process of the wave equation; the intermediate value satisfies preset wavefield requirements; the preset wavefield requirements include: the iteration residual is less than or equal to a residual threshold, or the number of iterations is greater than or equal to a threshold.

[0023] In this way, given the intermediate wavefield corresponding to the frequency information of the current batch, the wavefield solution for the next batch can begin ahead of schedule. This increases the parallelism of the computation, thereby reducing the wavefield solution time and improving the efficiency of wavefield solution.

[0024] In one optional implementation, the first wave field includes: the interpolation result of the intermediate wave field corresponding to the frequency information of the batch of wave fields solved by the wave equation; the intermediate wave field indicates the intermediate value in the iterative solution process of the wave equation; the intermediate value meets the preset wave field requirements; the preset wave field requirements include: the iteration residual is less than or equal to the residual threshold, or the number of iterations is greater than or equal to the threshold.

[0025] Based on this optional implementation method, using the interpolation result of the intermediate wavefield to set the first wavefield can improve the matching degree between the first wavefield and the mid-frequency information of the second batch, thereby ensuring the rationality of the initial wavefield value setting. Furthermore, by using the intermediate wavefield to set the first wavefield, after obtaining the intermediate wavefield corresponding to the frequency information of the current batch, the wavefield solution for the next batch can begin in advance. This increases the parallelism of computation, thereby reducing the wavefield solution time and improving the wavefield solution efficiency.

[0026] In one optional implementation, a preset wave field is used as input to the wave equation to solve for the wave field corresponding to the first batch of frequency points. This includes: obtaining the wave velocity field corresponding to the target object, where the wave velocity field includes the wave velocity of the wave signal at each spatial location of the target object; using the preset wave field, wave velocity field, information of the wave signal, and the first batch of frequency points as input to the wave equation, iteratively solving the wave equation to obtain the wave field corresponding to the first batch of frequency point information.

[0027] In this optional implementation, information about the preset wave field, wave velocity field, and wave signal, along with the first batch of frequency points, is used as input to the wave equation. The wave equation is then iteratively solved to obtain the wave field corresponding to the first batch of frequency point information. This reduces dispersion error, thereby improving the reliability of the reconstructed wave field and ensuring the accuracy of the final target object's structure.

[0028] In one alternative implementation, the structure of the target object is determined based on the wave field of the reflected wave, including:

[0029] Obtain the predicted structure corresponding to the wave field of the reflected wave. Acquire the wave field observation data corresponding to the target object; the wave field observation data includes the actual wave field after the wave signal is reflected by the target object. If the fitting error between the wave field of the reflected wave and the wave field observation data is less than or equal to a preset error threshold, the predicted structure is determined as the structure of the target object. If the fitting error between the wave field of the reflected wave and the wave field observation data is greater than the preset error threshold, the predicted structure is corrected based on the fitting error until the fitting error is less than or equal to the preset error threshold, at which point the structure of the target object is obtained.

[0030] Based on this optional implementation method, the fitting error between the wavefield of the reflected wave and the wavefield observation data is used to correct the predicted structure, thereby improving the accuracy of the target object's structure.

[0031] Secondly, this application provides a wavefield reconstruction apparatus. This apparatus can be a computing device executing a wavefield reconstruction method for wave signals, or a chip or system-on-a-chip within the computing device. It can also be a functional module within the computing device executing the wavefield reconstruction method for wave signals, used to implement the method in the first aspect or any of the optional implementations of the first aspect. This wavefield reconstruction apparatus can implement the functions performed by the computing device in any possible implementation of the first aspect or the first method. The functional module can be implemented by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the aforementioned functions, such as: a signal acquisition module, a frequency acquisition module, a frequency batching module, a wavefield solving module, and a reconstruction module.

[0032] The signal acquisition module is used to acquire information about the wave signals of the structure used to detect the target object.

[0033] The frequency acquisition module is used to determine multiple frequency points corresponding to the target object based on the information of the wave signal.

[0034] The frequency segmentation module is used to decompose frequency information into multiple batches of frequency information, with each batch including at least one frequency information.

[0035] The wave field solving module is used to solve for the wave field corresponding to the frequency point information of the first batch of multiple batches by using a preset wave field as the input of the wave equation. It is also used to obtain the first wave field corresponding to the frequency point information of any second batch other than the first batch by using the first wave field as the input of the wave equation to solve for the second wave field corresponding to the frequency point information of the second batch.

[0036] The reconstruction module is used to obtain the wave field of the reflected wave of the wave signal by using the wave field corresponding to the frequency point information of each batch in multiple batches, and to determine the structure of the target object based on the wave field of the reflected wave.

[0037] Thirdly, this application provides a wavefield reconstruction apparatus. This apparatus can be a computing device executing a wavefield reconstruction method for a wave signal, or a chip or system-on-a-chip within the computing device. It can also be a functional module within the computing device executing the wavefield reconstruction method for a wave signal, used to implement the method in the first aspect or any optional implementation of the first aspect. This wavefield reconstruction apparatus can implement the functions performed by the computing device in any possible implementation of the first aspect or the first aspect, and the functional module can be implemented in hardware. In an optional implementation, the wavefield reconstruction apparatus includes a processor and a memory. The processor executes instructions stored in the memory to cause the wavefield reconstruction apparatus to perform the method as described in the first aspect or any optional implementation of the first aspect.

[0038] Fourthly, this application provides an image reconstruction system, which includes a processor, a wave signal generator, a wave signal acquisition unit, a wave equation solver, and a display.

[0039] The wave signal generator is used to: emit wave signals to probe the structure of the target object. The wave signal acquisition unit is used to: acquire information from the wave signals. The wave equation solver is used to: based on the information from the wave signals, execute the method in the first aspect or any optional implementation of the first aspect to obtain the wave field of the reflected wave. The processor is used to: determine the structure of the target object based on the wave field of the reflected wave. The display is used to: display the structure of the target object.

[0040] In one alternative implementation, the processor and display can be independent devices or integrated together. For example, the processor's functionality is integrated into the processor itself.

[0041] In one alternative implementation, the processor and the wave signal generator can be independent devices or integrated together. For example, the functionality of the wave signal generator can be integrated into the processor.

[0042] Fifthly, embodiments of this application provide a computer program product containing instructions that, when executed by a wave field reconstruction device, cause the wave field reconstruction device to perform the method described in the first aspect or any optional implementation thereof.

[0043] In a sixth aspect, embodiments of this application provide a computer-readable storage medium including computer program instructions. When the computer program instructions are executed by a wave field reconstruction apparatus, the wave field reconstruction apparatus executes the instructions in the computer program stored in the computer-readable storage medium to perform the method in the first aspect or any optional implementation of the first aspect.

[0044] The technical effects of any of the implementations in aspects two through six can be found in the first aspect or any optional implementation of the first aspect. Further details are omitted here. Based on the implementations provided in the above aspects, this application can be further combined to provide more implementations. Attached Figure Description

[0045] Figure 1 is a schematic diagram of CBS;

[0046] Figure 2 is a schematic diagram of the CBS iteration process;

[0047] Figure 3 is a schematic diagram of an application scenario of the wave field reconstruction method for wave signals provided in this application;

[0048] Figure 4 is a schematic diagram of the application scenario of the wave field reconstruction method for wave signals provided in this application;

[0049] Figure 5 is a flowchart illustrating the wave field reconstruction method for wave signals provided in this application.

[0050] Figure 6 is a schematic diagram of multiple frequency points in batches corresponding to the target object provided in this application;

[0051] Figure 7 is a schematic diagram of the wave field solution process provided in this application;

[0052] Figure 8 is a flowchart illustrating the batch division process provided in this application;

[0053] Figure 9 is a schematic diagram of the batch division process provided in this application (II);

[0054] Figure 10 is a schematic diagram of the wave field solution process provided in this application (II).

[0055] Figure 11 is a schematic flowchart of the wave field reconstruction method for wave signals provided in this application (II).

[0056] Figure 12 is a schematic flowchart of the wave field reconstruction method for wave signals provided in this application.

[0057] Figure 13 is a schematic diagram of the wave field reconstruction device provided in this application.

[0058] Figure 14 is a schematic diagram of the wave field reconstruction device provided in this application. Detailed Implementation

[0059] Wave equation: used to describe the wave phenomenon of wave signals, where the wave phenomenon can be characterized by wave field.

[0060] Wave field: The spatial distribution state formed when a wave propagates through space. The spatial distribution state describes how various wave properties (amplitude, phase, frequency, wavelength, or wave speed, etc.) change with spatial location. The spatial distribution state can also be called a physical field. Alternatively, the wave field can also be called wave field information, sound field, electromagnetic wave field, electric field, the physical field of a wave, or other names; this application does not limit its application to any particular name.

[0061] Wave imaging technology (which can also generate wave images): a technique that uses the wave field properties of waves to generate images of the internal structure of an object.

[0062] Waves can also be called wave signals, waves, or other names.

[0063] Based on wave type and application field, wave imaging can be divided into ultrasonic imaging, microwave imaging, seismic imaging, and optical imaging.

[0064] Ultrasonic imaging: sending high-frequency sound wave signals to an object, receiving the echo signals reflected back from the object, and processing the echo signals to form an image.

[0065] Seismic imaging: Inferring subsurface geological structures based on changes in seismic waves as they propagate through the Earth's interior. These changes include variations in the propagation path and velocity of the seismic waves.

[0066] Optical imaging: Imaging using visible light or other forms of electromagnetic waves (such as infrared, X-rays, etc.).

[0067] Taking ultrasound imaging as an example, the processing procedure for wave imaging will be explained. The wave imaging processing procedure typically includes the following three stages:

[0068] Phase 1, Forward Modeling. A forward model is established to simulate the propagation behavior of waves within objects, i.e., solving the wave equation. This wave equation can then be used to predict the echo signals reflected back from objects with different structures.

[0069] Phase ②: Data Acquisition and Preprocessing. Ultrasonic waves are generated using an ultrasonic probe, and signals reflected back from the object being tested are received. The returned signals undergo preprocessing such as filtering and gain adjustment to form echo signals.

[0070] Phase 3, Inversion. The wave equation is used to simulate the predicted echo signals of the object under different internal structures. From multiple predicted echo signals, the most similar predicted echo signal to the acquired echo signal is determined, and the internal structure corresponding to this most similar predicted echo signal is identified as the internal structure of the object under test.

[0071] Phase 4 involves converting the most similar predicted echo signal into a visual image.

[0072] As can be seen from the above wave imaging process, solving the wave equation is involved in both the forward modeling and inversion stages. In order to accurately describe the propagation of ultrasound in the object under test, it is necessary to accurately solve the wave equation. In the inversion stage, the wave equation is used to compare the error between the predicted echo signal and the acquired echo signal, and the predicted internal structure of the object under test is adjusted based on the error, thereby inferring the internal structure of the object under test.

[0073] Currently, the main methods for solving wave equations are the finite-difference time-domain method, the finite-difference frequency-domain method, and the CBS algorithm.

[0074] The following sections provide illustrative examples of the finite-difference time-domain method, the finite-difference frequency-domain method, and the CBS algorithm.

[0075] The finite-difference time-domain method discretizes the continuous wave signal in both time and space, forming multiple grids at each sampling time. Each grid contains multiple sampling points, and each sampling point is a spatial location point in a spatial coordinate system.

[0076] In the finite-difference time-domain method, at each sampling time, for each sampling point, the wave field of each sampling point at the sampling time is obtained by solving the difference equation between each sampling point and its adjacent sampling points. The wave field of each sampling point at different sampling times is continuously solved in the order from early to late time to obtain the wave field of the wave signal.

[0077] The finite-difference frequency domain method transforms a continuous wave signal into the frequency domain, yielding frequency domain equations for both the frequency domain and space. By discretizing these equations using finite differences, the frequency equations for each frequency point in different spatial dimensions are obtained. Multiple frequency points are formed within a single spatial dimension. For each frequency point in a given dimension, the wave field of that frequency point in that dimension is obtained based on its frequency and the frequencies of its neighboring frequencies. The wave field of the wave signal is then derived from the wave fields of each frequency point in different dimensions.

[0078] The CBS algorithm divides the wave velocity field into a homogeneous part and a scattering part, treating the scattering part as the source term for solving the homogeneous parameter field. By gradually approximating the true scattering solution, the wave field of the wave signal is obtained. For example, the wave equation shown in Equation (1) is established. In Equation (1), k = ω / c0 represents the wave field number of the wave signal. Where ω is the frequency and c is the wave velocity field. For frequency domain wave signal sources, Let be the frequency domain wave field to be solved. The wavenumber field includes the wave number of the wave signal at each spatial location of the object under test at each sampling time. The wave velocity field includes the wave velocity of the wave signal at each spatial location of the object under test at each sampling time.

[0079] The wavenumber field can be decomposed into a homogeneous part k0 and a scattering part V by the following formula (2).

[0080] In formula (2), ε is a constant term. Substituting formula (2) into formula (1), we obtain the single-iteration form of the CBS algorithm, as shown in formula (3). The right-hand side of formula (3)... Treating them as known quantities, we obtain the solution in a single iteration. for in, F represents the positive Fourier transform, F -1 This represents the inverse Fourier transform, where p is the wavenumber coordinate.

[0081] In each iteration of solving the wave equation, the result obtained in each iteration is brought back to the right-hand side of formula (3) and the next iteration continues, forming the iterative form shown in formula (4).

[0082] As shown in Figure 1, in the first iteration, the initial estimate of the wave field, the source, and the wave velocity field are used as inputs to the wave equation, and the first iteration is executed through the input of formula (4). As shown in Figure 1, in subsequent iterations, for each iteration, the wave field of the scattered part is calculated based on the result of the previous iteration and the currently estimated scattering potential. The wave field is updated based on the calculated wave field of the scattered part to obtain the current iteration result, and it is determined whether the iteration process has converged. When the iteration process converges, the results of each iteration are accumulated to obtain the wave field of the wave signal. When the iteration process has not converged, the iteration continues to be performed with reference to the above formula (4).

[0083] The convergence of the iterative process can be defined as follows: the iterative residual between the current iteration result and the result of the previous iteration is less than or equal to a preset convergence threshold, or the number of iterations is greater than or equal to a number threshold. Taking the iterative residual as an example, as shown in Figure 2, as the number of iterations increases, the iterative residual gradually approaches 0, that is, the wave field of the scattering part gradually approaches the wave field of the true scattering part.

[0084] As discussed above, the finite-difference time-domain method introduces time information, which increases dispersion error when the interval between sampling times is large. While the finite-difference frequency-domain method does not introduce dispersion error, it requires solving the wavefield at every frequency point in every dimension, resulting in a large computational load and consuming significant computational resources. Furthermore, in the CBS algorithm, the number of iterations is related to the initial estimate of the wavefield. An unreasonable initial estimate will increase the number of iterations, consume more computational resources, and reduce the efficiency of wavefield solution.

[0085] Based on this, to reduce computational resource consumption, this application provides a wavefield reconstruction method. This method, based on the first wavefield corresponding to the frequency points of a batch of solved wavefields, sets the input of the wave equation and solves for the second wavefield corresponding to any frequency points of a second batch other than the first batch. It allows for flexible setting of the initial wavefield value during the wave equation solving process and ensures the rationality of the initial wavefield value setting, so that the input of the wave equation is closer to the second wavefield corresponding to the frequency points of the second batch. This reduces the number of iterations in the wavefield solving process, improves reconstruction efficiency, and reduces computational resource consumption. Furthermore, this method also divides multiple frequency points corresponding to the target object into batches, enabling parallel solving of all frequency points within the same batch, which further improves reconstruction efficiency and reduces computational resource consumption.

[0086] Specifically, during the wave field reconstruction process of the wave signal, the wave equation solver acquires information about the wave signal used to detect the structure of the target object. Based on this information, it determines multiple frequency points corresponding to the target object. These frequency points are then decomposed into multiple batches. For the first batch of frequency points solved in the multiple batches, a preset wave field is used as the input and output of the wave equation to solve for the wave field corresponding to the first batch of frequency points. For any other second batch of frequency points besides the first batch, the first wave field corresponding to the batch whose wave field has already been solved according to the wave equation is acquired. This first wave field is then used as the input of the wave equation to solve for the second batch of frequency points. The wave equation solver obtains the wave field of the reflected wave from the wave field corresponding to the frequency points of each batch in the multiple batches, and determines the structure of the target object based on the wave field of the reflected wave.

[0087] The technical solutions involved in this application can be applied not only to the field of ultrasonic imaging, but also to the fields of electromagnetic waves, light waves, visible waves, or mechanical waves, etc. The embodiments of this application do not limit the specific types of the above-mentioned wave signals.

[0088] Furthermore, this application does not limit the specific type of the target object. For example, the target object may include, but is not limited to: geology, biology, mechanical equipment, electronic products, express parcels, and the ground. Moreover, the wave field of the reflected wave can be used not only to determine the structure of the target object, but also to determine the material of the target object, the surface texture of the target object, cracks on the surface of the target object, or to detect the distance to the target object.

[0089] Furthermore, the technical solutions involved in this application can be used not only in current wave imaging technology, wave equation solvers, imaging equipment, imaging systems, and seismic survey equipment, but also in future wave imaging technology or imaging equipment, or servers, signal acquisition equipment, signal analysis equipment, wave imaging equipment, or seismic survey equipment that include wave equation solvers.

[0090] To make the objectives, technical solutions, and advantages of this application clearer, the application will now be described in further detail with reference to the accompanying drawings.

[0091] In the following description, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0092] Furthermore, in this application, directional terms such as "upper" and "lower" are defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms are relative concepts, used for relative description and clarification, and can change accordingly depending on the orientation of the components in the accompanying drawings.

[0093] The application scenarios of the wave field reconstruction method for wave signals are illustrated below with reference to Figures 3 to 5.

[0094] In one optional implementation, the wave field reconstruction method for wave signals provided in this application can be applied to scenarios where wave signal acquisition and wave field reconstruction are integrated. For example, the wave field reconstruction method for wave signals can be applied to a wave imaging device. This wave imaging device can be a CT scanner, MRT, MRI, X-ray machine, or other wave imaging devices. The embodiments of this application do not limit the specific type of wave imaging device.

[0095] When the wave field reconstruction method for wave signals is applied to a wave imaging device, the wave imaging device has both wave signal transmission and wave field reconstruction functions. For example, as shown in Figure 3, which is a schematic diagram of an application scenario of the wave field reconstruction method for wave signals provided in this application, the application scenario includes a wave imaging device. In some alternative embodiments, the wave imaging device 100 may also be referred to as a wave imaging system, an image reconstruction system, an image reconstruction apparatus, or other names; this application embodiment does not limit this.

[0096] As shown in Figure 3, the wave imaging device 100 includes at least: a processor 10, a wave signal generator 20, a wave equation solver 30, a wave signal acquisition unit 40, and a display 50. The processor 10, wave signal generator 20, wave equation solver 30, wave signal acquisition unit 40, and display 50 are connected via a bus 60.

[0097] In some optional scenarios, the processor 10, wave signal generator 20, wave equation solver 30, wave signal acquisition unit 40, and display 50 can be deployed in the same device. In another optional scenario, the processor 10, wave signal generator 20, wave equation solver 30, wave signal acquisition unit 40, and display 50 can be deployed in different devices, or at least two of the components can be deployed in different devices. For example, the wave signal generator 20, wave equation solver 30, and wave signal acquisition unit 40 can be deployed in device 1, and the processor 10 and display 50 can be deployed in device 2, with device 1 and device 2 connected via network communication. This application embodiment does not limit the deployment method of the components in the wave imaging device 100.

[0098] The functions of each component in the wave imaging device 100 are described below by way of example.

[0099] Wave signal generator 20 is used to generate wave signals. In some optional embodiments, the wave signal can be an ultrasonic signal, an optical signal, an electromagnetic signal, or other types of wave signals, etc., and this application embodiment does not limit this. Accordingly, when the wave signal is an ultrasonic signal, the wave signal generator 20 can be an ultrasonic probe. When the wave signal is an optical signal, the wave signal generator 20 can be a light source detector. When the wave signal is an electromagnetic signal, the wave signal generator 20 can be an electromagnetic wave generator. This application embodiment does not limit the specific type of wave signal generator 20.

[0100] The wave signal acquisition unit 40 is used to acquire the wave signal generated by the wave signal generator 20, the reflected wave signal formed after the acquired wave signal is emitted by the target object, and to send the wave signal and reflected wave signal to the wave equation solver 30, or to send the wave signal and reflected wave signal to the processor 10.

[0101] In some optional scenarios, when the wave signal acquisition unit 40 sends wave signals and reflected wave signals to the processor 10, the processor 10 sends a wave field solution instruction to the wave equation solver 30, which carries the wave signals and reflected wave signals.

[0102] The wave equation solver 30 is used to receive wave signals and reflected wave signals, and based on the wave signals and reflected wave signals, execute the wave field reconstruction method provided in this application to obtain the wave field of the reflected wave, and send the wave field of the reflected wave to the processor 10 or to the display 50.

[0103] The processor 10 provides computing resources and sends instructions to the wave signal generator 20, the wave equation solver 30, the wave signal acquisition unit 40, and the display 50 to execute corresponding instructions, thereby realizing wave field reconstruction or other functions of the wave signal. For example, the processor 10 receives the wave field of the reflected wave sent by the wave equation solver 30, determines the structure of the target object based on the wave field of the reflected wave, and sends the structure of the target object to the display 50.

[0104] In some alternative scenarios, processor 10 may specifically be a CPU, graphics processing unit (GPU), microprocessor (MP), digital signal processor (DSP), or neural processing unit (NPU), which can implement or execute various exemplary logic blocks, modules, and circuits described in connection with the embodiments of this application. Processor 10 may also be a combination of functions that implement computing capabilities, such as including one or more microprocessor combinations, a combination of DSP and microprocessor, etc.

[0105] Display 50 is used to display the structure of the target object. Alternatively, when the wave equation solver 30 sends the wave field of the reflected wave to display 50, display 50 can also be used to determine the structure of the target object based on the wave field of the reflected wave and display the structure of the target object.

[0106] In an alternative scenario, the functions implemented by the processor 10, wave signal generator 20, wave equation solver 30, wave signal acquisition device 40, and display 50 can be performed by the wave imaging device 100 or other components of the wave imaging device 100. This application does not limit the implementation method.

[0107] The processor 10 and the wave equation solver 30 can be independent devices or integrated devices. For example, the function of the wave equation solver 30 is integrated into the processor 10.

[0108] The system architecture and application scenarios described in this application are intended to more clearly illustrate the technical solutions of this application and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0109] The following is an example of the interaction process between the components in the wave imaging device 100, based on the wave imaging device 100 provided in Figure 3 above, taking the field of ultrasonic imaging as an example.

[0110] The interaction process between the components in the wave imaging device 100 includes stages ① to ⑩. Among them:

[0111] Phase ①: In response to the first request, the processor 10 sends a first instruction to the wave signal generator 20.

[0112] The first request is used to instruct the wave imaging device 100 to execute a structure acquisition request for the target object.

[0113] In some alternative implementations, the first request may be input by an inspector via the display 50 of the wave imaging device 100 or a start button on the wave imaging device 100. Alternatively, in other alternative implementations, the first request may be sent to the wave imaging device 100 by an external device. This external device may be a terminal device, such as a client 230, a server, etc. This application embodiment does not limit the specific form of the external device.

[0114] In stage ②, the wave signal generator 20 responds to the first command, generates an ultrasonic signal, and emits an ultrasonic signal.

[0115] In contrast to the processing in stage ①, in stage ②, the wave signal generator 20 receives the first instruction sent by the processor 10.

[0116] In one alternative implementation, the processor 10 can periodically send first instructions to the wave signal generator 20 over a period of time, causing the wave signal generator 20 to periodically generate ultrasonic signals. Different first instructions correspond to ultrasonic signals with different frequencies, or different first instructions correspond to ultrasonic signals with different signal sources.

[0117] In another alternative implementation, the processor 10 sends a first instruction to the wave signal generator 20. The wave signal generator 20 periodically generates multiple different ultrasonic signals over a period of time. These different ultrasonic signals have different frequencies or signal sources.

[0118] In stage ③, the processor 10 sends a second instruction to the wave signal acquisition unit 40.

[0119] In one alternative implementation, the processor 10 may send a second instruction to the wave signal collector 40 after detecting that the wave signal generator 20 has emitted an ultrasonic signal.

[0120] For example, after emitting an ultrasonic signal, the wave signal generator 20 returns a first response to the processor 10. Upon receiving the first response, the processor 10 sends a second instruction to the wave signal acquisition unit 40. The first response indicates that the wave signal generator 20 has emitted an ultrasonic signal.

[0121] For example, the processor 10 detects the state of the wave signal generator 20. If the wave signal generator 20 is in the working state, the processor 10 sends a second instruction to the wave signal acquisition unit 40.

[0122] In another alternative implementation, the processor 10 may also send a second instruction to the wave signal collector 40 after sending the first instruction to the wave signal generator 20.

[0123] The two optional implementation methods described above are merely different triggering methods for the processor 10 to send the second instruction to the wave signal acquisition unit 40. In other embodiments, the processor 10 may send the second instruction in other ways. For example, after responding to the first request, the processor 10 sends the first instruction to the wave signal generator 20 and the second instruction to the wave signal acquisition unit 40. This application embodiment does not limit this.

[0124] In stage 4, the wave signal acquisition unit 40 responds to the second command and acquires the ultrasonic signal emitted by the wave signal generator 20, as well as the reflected wave signal after the ultrasonic signal is reflected by the target object.

[0125] In contrast to the processing in stage ③, in stage ④, the wave signal acquisition unit 40 receives the second instruction sent by the processor 10.

[0126] In one alternative implementation, the wave signal acquisition unit 40 can periodically acquire signals to obtain the ultrasonic signal and the reflected wave signal at each sampling moment.

[0127] In stage 5, the wave signal acquisition unit 40 sends the ultrasonic signal and the reflected wave signal to the wave equation solver 30.

[0128] In stage 6, the wave equation solver 30 reconstructs the wave field of the predicted reflected wave signal under various different structures based on the ultrasonic signal, and determines the predicted reflected wave signal that is most similar to the reflected wave signal from multiple predicted reflected wave signals based on the reflected wave signal.

[0129] In contrast to the processing in stage ⑤, in stage ⑥, the wave equation solver 30 receives the ultrasonic signal and the reflected wave signal sent by the wave signal acquisition unit 40.

[0130] In stage 7, the wave equation solver 30 sends the wave field of the predicted reflected wave signal that is most similar to the reflected wave signal to the processor 10.

[0131] In stage ⑧, the processor 10 determines the structure of the target object based on the wave field of the predicted reflected wave signal that is most similar to the reflected wave signal.

[0132] In contrast to the processing in stage ⑥, in stage ⑦, the processor 10 receives the wave field of the predicted reflected wave signal that is most similar to the reflected wave signal sent by the wave equation solver 30.

[0133] In stage 9, the processor 10 sends the structural data of the target object to the display 50.

[0134] In one alternative implementation, the structural data of the target object includes the target object's dimensions, material, or three-dimensional spatial structure.

[0135] In another alternative implementation, the structural data of the target object includes rendering data of the target object's internal structure.

[0136] In stage 10, the display 50 shows the structure of the target object based on the target object's structure.

[0137] In contrast to the processing in stage ⑧, in stage ⑨, the display 50 receives the structural data of the target object sent by the processor 10.

[0138] In one alternative implementation, the structural data of the target object includes the target object's size, material, or three-dimensional spatial structure. The display 50 renders the target object based on its size, material, or three-dimensional spatial structure and displays the rendered target object's structure.

[0139] In some alternative implementations, the structural data of the target object includes rendering data of the target object's internal structure. The display 50 displays the structure of the target object by showing this rendering data of its internal structure.

[0140] In the above-described interactive process, during the reconstruction of the target object's structure, the wave equation solver 30, in conjunction with the wave signal acquisition unit 40 and the wave signal generator 20, achieves wavefield reconstruction. Furthermore, during the wavefield reconstruction process, the wave equation solver 30 can implement the wavefield reconstruction method for wave signals provided in this application, thereby achieving wavefield reconstruction. For the wavefield reconstruction process of wave signals, please refer to the embodiments provided in Figures 5 to 12 below; the embodiments of this application will not be described in detail here.

[0141] Figure 3 above illustrates the application scenario of the wave field reconstruction method using an integrated wave signal acquisition and wave field reconstruction approach. In other embodiments, the wave field reconstruction method may also be applied to other scenarios, which are not limited in this application. For example, the wave field reconstruction method can also be applied to scenarios where wave signal acquisition and wave field reconstruction are separate.

[0142] As shown in Figure 4, Figure 4 is a schematic diagram of the second application scenario of the wave field reconstruction method for wave signals provided in this application. This application scenario 200 includes: a work terminal 220, a client 230, and a server 201. Among them, the server 201 is connected to the work terminal 220 and the client 230 via the network. The server 201 is used to provide wave field reconstruction services to the work terminal 220 and image display services to the client 230.

[0143] The following provides exemplary descriptions of the operating terminal 220 and the client 230.

[0144] First, the working terminal 220 will be described by way of example. The working terminal 220 can refer to the physical carrier tool used by the test personnel to transmit and collect wave signals, and is used to provide wave signals and reflected wave signals after reflection by the target object to the server 201. In some optional embodiments, the working terminal 220 may also be called a surveyor, a first terminal, a measurement terminal, or other names, and this application embodiment does not limit this.

[0145] In an optional scenario, the work terminal 220 may be a terminal capable of generating and acquiring wave signals. The specific technology and equipment form employed in the work terminal 220 according to this application embodiment are not limited. For example, the work terminal 220 may include at least a communication interface and the aforementioned wave signal acquisition device 40 and wave signal generator 20. The communication interface is used to send wave signals and reflected wave signals after reflection from the target object to the server 201.

[0146] In an optional scenario, the work terminal 220 is equipped with a measurement application, such as a seismic survey application, an object texture recognition application, or an environmental recognition application. This measurement application can obtain measurement tasks for the target object from the server 201 online or offline, and execute the measurement tasks to acquire wave signals and reflected wave signals after reflection from the target object.

[0147] Next, an example description of client 230 will be provided.

[0148] In a first optional implementation, the client 230 can be a computer running an application, which can be a physical machine or a virtual machine. For example, if the computer running the application is a physical computing device, it can be a host or a terminal. The terminal can also be called a terminal device, user equipment (UE), mobile station (MS), mobile terminal (MT), etc. Terminals can be mobile phones, tablets, laptops, desktop computers, virtual reality (VR) terminal devices, augmented reality (AR) terminal devices, wireless terminals in industrial control, wireless terminals in autonomous driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, etc. The embodiments of this application do not limit the specific technology or device form adopted by the client 230.

[0149] In the second optional implementation, client 230 can be an application, such as a structure display application, a surface texture display application, an environment awareness application, etc. Alternatively, client 230 can be a network client. Or, client 230 can run on a terminal device. The terminal device can include, but is not limited to, an in-vehicle central control screen, a mobile terminal, a tablet computer, a personal computer, or a laptop computer.

[0150] The two implementation methods described above are merely different ways of implementing the client 230. In practical applications, the client 230 can also have other implementation methods. For example, the client 230 and the aforementioned work terminal 220 can be deployed in the same device. Alternatively, the client 230 and the aforementioned work terminal 220 can be the same terminal; this embodiment of the application does not limit this.

[0151] The above-mentioned server 201 is described below as an example.

[0152] In one alternative implementation, server 201 can be deployed in the cloud, or server 201 can be deployed in a physical environment. Server 201 is used to provide measurement services, wave field reconstruction services, target object image display services, target object image reconstruction services, etc.

[0153] The following description uses the example of server 201 being deployed in the cloud. As shown in Figure 4, server 201 includes cloud service platform 240 and cloud platform 210. Wavefield reconstruction device 212 is deployed in cloud platform 210. In some alternative embodiments, wavefield reconstruction device 212 may also be called wavefield reconstruction device 212 for wave signals, wavefield reconstruction device 212 for reflected waves, image reconstruction device, wave imaging device, or other names; this embodiment does not limit the specific name used.

[0154] In one alternative implementation, as shown in Figure 4, the cloud platform 210 further includes a computing cluster 211. The computing cluster 211 refers to a collection of computers connected via a local area network (LAN) or the Internet. As shown in Figure 4, the computing cluster 211 includes multiple hosts.

[0155] In one alternative example, the Tron Reconstruction Device 212 can be deployed independently on a single host of the computing cluster 211. Alternatively, in some embodiments, the Tron Reconstruction Device 212 can be distributed across multiple hosts of the computing cluster 211. Alternatively, the Tron Reconstruction Device 212 can be deployed independently in a single virtual instance on a single host of the computing cluster 211, or in multiple virtual instances on a single host. Alternatively, in some embodiments, the Tron Reconstruction Device 212 can be distributed across multiple virtual instances on multiple hosts of the computing cluster 211. This application does not limit the scope of the embodiments in this regard.

[0156] Virtual instances can also be called virtual machines (VMs) or containers.

[0157] As shown in Figure 4, the wavefield reconstruction device 212 is abstracted by the cloud service provider on the cloud service platform 240 as a measurement service or wave imaging service and provided to users. After the user purchases the wave imaging service on the cloud service platform 240 through the work terminal 220 and client 230, the cloud environment provides the wave imaging service to the user using the wavefield reconstruction device 212 deployed on the cloud platform 210. When using the wave imaging service, the user can upload wave signals and reflected wave signals after reflection from the target object through the application program interface (API) or graphical user interface (GUI) in the work terminal 220. The wavefield reconstruction device 212 in the cloud environment receives the wave signals and reflected wave signals after reflection from the target object, performs wavefield reconstruction, obtains the wavefield of the reflected wave, and obtains the business results based on the wavefield of the reflected wave. The wavefield reconstruction device 212 returns data such as the wavefield of the reflected wave or business results during the data processing process to the user through the API or GUI.

[0158] Alternatively, the user can upload the identification information of the target object to be viewed to the cloud environment via the API or GUI in client 230. The wave field reconstruction device 212 in the cloud environment returns the business results of the target object to client 230 via API or GUI. The business results are used to provide images of the internal structure, surface texture, or environment of the target object.

[0159] In addition, in some other embodiments, the function of the wave field reconstruction device 212 may be performed by the cloud platform 210 or other components of the cloud platform 210, and this application does not limit its implementation.

[0160] During the wave field reconstruction process, the aforementioned wave field reconstruction device 212 can provide the client 230 with a structural image (texture image) of the target object based on the wave signal collected by the operating terminal 220. Furthermore, the wave field reconstruction device 212 can implement the wave field reconstruction method for the wave signal provided in this application during the wave field reconstruction process. The wave field reconstruction process will be described exemplarily below with reference to Figures 5 to 12.

[0161] Please refer to Figure 5, which is a schematic flowchart of the wave field reconstruction method for wave signals provided in this application. The wave field reconstruction method for wave signals shown includes steps S610 to S660.

[0162] S610, the wave field reconstruction device 212 acquires information about the wave signal used to detect the structure of the target object.

[0163] In some alternative approaches, the wave signal may also be referred to as the incident wave signal, the source wave signal, the wave signal, or other names, and the embodiments of this application do not limit this.

[0164] In an alternative example, the wave signal may be a wave signal generated by the wave signal generator 20 described above, or the wave signal may be a wave signal generated by the work terminal 220 described above.

[0165] In one optional implementation, the wave signal information may include, but is not limited to: source information, frequency information, amplitude, phase, wavelength information, waveform information, and wave signal type. The source information indicates the location of the signal source generating the wave signal, including its coordinates, elevation angle, and deflection angle. The frequency information includes the center frequency and bandwidth of the wave signal. The waveform information describes the waveform of the wave signal, which may include, but is not limited to: pulse wave, continuous wave, rectangular wave, square wave, sine wave, sawtooth wave, or triangular wave.

[0166] In one alternative implementation, the wave field reconstruction device 212 has multiple methods for acquiring wave signal information. For example:

[0167] In one implementation, the wave field reconstruction device 212 reads the stored wave signal information. For example, the wave field reconstruction device 212 reads the wave signal information from local memory. Alternatively, the wave field reconstruction device 212 reads the wave signal information from an external storage device.

[0168] In the second implementation, the wave field reconstruction device 212 receives wave signal information sent by an external device. This external device can be the aforementioned operating terminal 220 or the aforementioned wave signal generator 20. This application embodiment does not limit the specific form of the external device.

[0169] In the third implementation, the wavefield reconstruction device 212 sends a source excitation command to the operation terminal 220. In response to the source excitation command, the operation terminal 220 generates a wave signal, collects the wave signal information, and sends the wave signal information to the wavefield reconstruction device 212. The wavefield reconstruction device 212 receives the wave signal information sent by the operation terminal 220.

[0170] The three implementation methods described above are merely different ways in which the wave field reconstruction device 212 acquires wave signal information. In other embodiments, the wave field reconstruction device 212 may also employ other implementation methods to acquire wave signal information. For example, the wave field reconstruction device 212 may generate seismic source excitation and acquire first wave information based on the seismic source excitation. This application embodiment does not limit this approach.

[0171] S620, the wave field reconstruction device 212 determines multiple frequency points corresponding to the target object based on the information of the wave signal.

[0172] The target object corresponds to multiple frequency points, including frequency points of interest within the frequency range of the wave signal. Each frequency point has a frequency value and an amplitude. In some optional embodiments, the frequency point may also be referred to as frequency point information, sampling point, sampling frequency point, or other names, and this application embodiment does not limit this.

[0173] In the first optional approach, the "frequency of interest" can be a frequency point within the frequency range of the wave signal whose frequency value satisfies a frequency condition. This frequency condition can be a frequency greater than or equal to x MHz, or a frequency less than or equal to y Hz. Here, x and y are both positive integers greater than or equal to 1. For example, in an ultrasound imaging scenario, candidate frequency points within the frequency range of the wave signal whose frequency value is greater than or equal to x MHz are selected as the frequency of interest. As another example, in a geological exploration scenario, candidate frequency points within the frequency range of the wave signal whose frequency value is less than or equal to y Hz are selected as the frequency of interest.

[0174] In the second alternative approach, the "frequency of interest" can also be a frequency in the wave signal with a signal-to-noise ratio (SNR) greater than a SNR threshold. For example, within the frequency range of the wave signal, the SNR of each candidate frequency is calculated, and candidate frequencies with an SNR greater than the SNR threshold are selected as the frequencies of interest.

[0175] In the third option, the "frequency of interest" can also be any frequency within the frequency range of the wave signal.

[0176] The three optional methods described above are merely different implementations for obtaining the frequency point of interest. In other embodiments, the wavefield reconstruction device 212 can also employ other implementation methods to obtain the frequency point of interest. For example, the wavefield reconstruction device 212 selects initial frequency points whose frequency values ​​satisfy frequency conditions from the frequency range of the wave signal, and selects the initial frequency points whose signal-to-noise ratio (SNR) is greater than a SNR threshold as the frequency points of interest. Another example is that the wavefield reconstruction device 212 predicts the prediction probability of each frequency value within the frequency range of the wave signal, and selects the frequency values ​​whose prediction probability is greater than or equal to a probability threshold as the frequency points of interest. Yet another example is that the wavefield reconstruction device 212 inputs the frequency range of the wave signal into a prediction model to obtain the frequency point of interest. This application does not limit the specific implementation of these methods. The prediction model can be a machine learning-based model or a neural network-based model; this application does not limit the specific form of the prediction model.

[0177] S630, the wave field reconstruction device 212 decomposes multiple frequency points into multiple batches of frequency points.

[0178] Each batch includes at least one frequency point, meaning each batch includes the frequency value of at least one frequency point.

[0179] In one optional implementation, the wavefield reconstruction device 212 can sort the multiple frequency points corresponding to the target object in ascending order of frequency value to form a frequency point sequence. The multiple frequency points in the frequency point sequence are then decomposed into multiple batches of frequency points. As shown in Figure 5, m batches are obtained, where m is a positive integer greater than 2.

[0180] In a first alternative approach, the wavefield reconstruction device 212 treats one frequency point in the frequency point sequence as a batch. For example, taking a target object with multiple frequency points including 20 frequency points as an example, as shown in Figure 6(a), the frequency point sequence includes frequency points ω1 to ω20, and the frequency values ​​of frequency points ω1 to ω20 increase sequentially. The wavefield reconstruction device 212 treats the i-th frequency point as the i-th batch, where i is a positive integer greater than or equal to 1 and less than or equal to 20.

[0181] In the second optional implementation, the wavefield reconstruction device 212 can cluster multiple frequency points in the frequency point sequence to obtain multiple clusters. Each cluster includes one or more frequency points, and the frequency difference between a frequency point in each cluster and the cluster center point is less than or equal to a preset threshold. During each division process, the wavefield reconstruction device 212 selects one frequency point from each cluster to form a frequency point group, and uses this frequency point group as the batch obtained in that division.

[0182] For example, taking the frequency point sequence provided in Figure 6(a) as an example, as shown in Figure 6(b), the wavefield reconstruction device 212 clusters the frequency points ω1 to ω20 in the frequency point sequence to obtain 5 clusters: cluster 1, cluster 2, cluster 3, cluster 4, and cluster 5. Cluster 1 includes frequency points ω1, ω2, ω3, and ω4. Cluster 2 includes frequency points ω5, ω6, ω7, and ω8. Cluster 3 includes frequency points ω9, ω10, ω11, and ω12. Cluster 4 includes frequency points ω13, ω14, ω15, and ω16. Cluster 5 includes frequency points ω17, ω18, ω19, and ω20. In each division, the wave field reconstruction device 212 selects a frequency point from cluster 1, cluster 2, cluster 3, cluster 4 and cluster 5 respectively, and divides the selected 5 frequency points into the same batch.

[0183] For example, in the first partitioning, ω1 in cluster 1, ω5 in cluster 2, ω9 in cluster 3, ω13 in cluster 4, and ω17 in cluster 5 are designated as the mid-frequency points of batch 1. In the second partitioning, ω2 in cluster 1, ω6 in cluster 2, ω10 in cluster 3, ω14 in cluster 4, and ω18 in cluster 5 are designated as the mid-frequency points of batch 2. In the third partitioning, ω3 in cluster 1, ω7 in cluster 2, ω11 in cluster 3, ω15 in cluster 4, and ω19 in cluster 5 are designated as the mid-frequency points of batch 3. In the fourth partitioning, ω4 in cluster 1, ω8 in cluster 2, ω12 in cluster 3, ω16 in cluster 4, and ω20 in cluster 5 are designated as the mid-frequency points of batch 4. As shown in Figure 6(c), the multiple frequency points corresponding to the target object are divided into batches 1, 2, 3, and 4. Batch 1 includes frequency points ω1, ω5, ω9, ω13, and ω17. Batch 2 includes frequency points ω2, ω6, ω10, ω14, and ω18. Batch 3 includes frequency points ω3, ω7, ω11, ω15, and ω19. Batch 4 includes frequency points ω4, ω8, ω12, ω16, and ω20.

[0184] The above two implementation methods are merely different ways for the wave field reconstruction device 212 to decompose multiple frequency points into multiple batches of frequency points. In other embodiments, the wave field reconstruction device 212 can also use other implementation methods to decompose multiple frequency points into multiple batches of frequency points. For example, the wave field reconstruction device 212 implements batch division with reference to the implementation method provided in FIG8 below. As another example, the wave field reconstruction device 212 implements batch division with reference to the implementation method provided in FIG9 below. This application embodiment does not limit this aspect.

[0185] In one alternative implementation, for each of multiple batches, the wavefield reconstruction device 212 can solve the wavefield corresponding to each frequency point in that batch in parallel. After completing the wavefield solution for each frequency point in that batch, the wavefield solution is then performed for each frequency point in the next batch of that batch.

[0186] In some alternative embodiments, this application does not limit the number of batches or the number of intermediate frequency points in each batch. The number of batches and the number of intermediate frequency points in each batch can be selected according to the actual application scenario. For example, to reduce the resources occupied by parallel solving of each frequency point in the same batch, the number of intermediate frequency points in each batch can be set according to the computing power of the device where the wave field reconstruction device 212 is located. As another example, to improve the efficiency of wave field solving, the number of intermediate frequency points in each batch can be increased to reduce the number of batches, thereby improving the efficiency of wave field solving.

[0187] S640, for the first batch of frequencies to be solved in multiple batches, the wave field reconstruction device 212 uses a preset wave field as the input of the wave equation to solve for the wave field corresponding to each frequency point in the first batch.

[0188] In the first optional implementation, the first batch can be the first batch in the solution order among multiple batches. As shown in Figure 5, the first batch is batch 1.

[0189] The wave field reconstruction device 212 can be set to solve each batch in multiple batches, and solve each batch in multiple batches in the order of solving.

[0190] In one alternative approach, the solution order of batches is related to the batch partitioning time. For example, batches partitioned earlier have a higher solution order.

[0191] In another alternative approach, the solution order of batches is related to the frequency values ​​of the points within the batch. For example, batches with lower frequencies have a higher solution order.

[0192] In the second alternative implementation, the first batch can be a batch randomly selected by the wave field reconstruction device 212 from multiple batches.

[0193] The two optional implementation methods mentioned above are only different ways of selecting the first batch of wave field reconstruction device 212. In other embodiments, wave field reconstruction device 212 may also use other implementation methods to select the first batch, and this application embodiment does not limit this.

[0194] In one alternative implementation, "solving the wavefield corresponding to each frequency point in the first batch" can be achieved by the wavefield reconstruction device 212 predicting the spatial geometric model of the target object, forming a predicted structure of the target object. The wavefield reconstruction device 212 uses wave equations to simulate the propagation behavior of each frequency point in the first batch within the target object, predicting the response characteristics of each frequency point in the first batch under the predicted structure of the target object. These response characteristics include the aforementioned amplitude, phase, frequency, wavelength, or wave velocity.

[0195] The wave equation is related to the type of wave signal. For example, when the wave signal is a sound wave, the wave equation is the sound wave equation. Similarly, when the wave signal is an electromagnetic wave, the wave equation is the electromagnetic wave equation. This application does not limit the specific form of the wave equation. The following explanation uses the sound wave equation as an example. This sound wave equation is shown in formula (3) above.

[0196] In a first optional embodiment, the wave field reconstruction device 212 can predict the wave velocity of sound waves at each spatial location of the target object based on the predicted structure of the target object and the medium density of the target object, thus forming a wave velocity field. For example, the predicted structure of the target object and the medium of the target object are input into a wave velocity prediction model to obtain the wave velocity at each spatial location of the target object. The wave velocity prediction model can be a mathematical model, a machine learning-based prediction model, or a neural network-based prediction model, etc. The wave velocity field includes the wave velocity of sound waves at each spatial location of the target object.

[0197] In a second alternative implementation, the wave field reconstruction device 212 can define the wave velocity field based on the physical properties of the target object. These physical properties include the predicted structure of the target object and the medium density of the target object, etc.

[0198] In a third optional implementation, the wave field reconstruction device 212 can also acquire observation data of the wave signal, and obtain the wave velocity of the sound wave at each spatial location of the target object based on the observation data, thus forming a wave velocity field. Here, the observation data refers to the wave signal collected after the wave signal is reflected by the target object.

[0199] The three optional implementation methods described above are merely different ways in which the wave field reconstruction device 212 acquires the wave velocity field. In other embodiments, the wave field reconstruction can also acquire the wave velocity field in other ways, such as by the wave field reconstruction device 212 reading the wave velocity field input from an external device. This application does not limit this aspect.

[0200] In one alternative implementation, the wave field reconstruction device 212 can solve the wave equation by referring to the CBS algorithm provided by formulas (1) to (4) above to obtain the wave field of each frequency point in the first batch.

[0201] For example, for each frequency point in the first batch, the wave field reconstruction device 212 uses the frequency domain signal of the wave signal, the wave velocity field, and the frequency of each frequency point as inputs to formula (3) to establish the wave equation for each frequency point in the first batch. The wave field reconstruction device 212 refers to the above formula (4) to form an iterative form for solving the wave equation for each frequency point in the first batch, and uses the preset wave field as the initial estimate for the first iteration for iteration until the iteration process converges, thereby obtaining the response characteristics of each frequency point in the first batch at each spatial location in the predicted structure of the target object, and thus obtaining the wave field corresponding to each frequency point in the first batch.

[0202] In one optional approach, the preset wavefield can be a fixed value pre-set by the wavefield reconstruction device 212. For example, the preset wavefield can be a zero field, that is, the wavefield of each frequency point in the initial state (sampling time is 0). In the initial state, the response characteristics of each frequency point at each spatial location in the predicted structure of the target object are 0. In some optional approaches, the zero field can also be called the zero wavefield, the background wavefield, or other names. This application embodiment does not limit this.

[0203] S650, for any second batch frequency point other than the first batch, the wave field reconstruction device 212 acquires the first wave field corresponding to the frequency point of the batch whose wave field has been solved according to the wave equation, and uses the first wave field as the input of the wave equation to solve the second wave field corresponding to the frequency point of the second batch.

[0204] As shown in Figure 5, the second batch is any batch i, where i is an integer greater than 1.

[0205] In a first alternative implementation, "the frequency points of the batches whose wave fields have been solved" can be the frequency points of all batches whose wave fields have been solved in multiple batches.

[0206] For example, taking the multiple frequency points of the target object provided in Figure 6 above as an example, the wave field reconstruction device 212 solves the wave field in the order of batch 1 → batch 2 → batch 3 → batch 4. When the second batch is batch 2, the frequency points of the batch whose wave field has been solved can be frequency points ω1, ω5, ω9, ω13 and ω17 in batch 1. When the second batch is batch 4, the frequency points of the batch whose wave field has been solved include the frequency points in batch 1, the frequency points in batch 2 and the frequency points in batch 3.

[0207] In a second optional implementation, "frequency points of the batch whose wave field has been solved" can be frequency points in the batch whose wave field has been solved and whose frequency difference with that in the second batch is less than a preset difference.

[0208] For example, taking the multiple frequency points of the target object provided in Figure 6 above as an example, the wave field reconstruction device 212 solves the problem in the order of batch 1 → batch 2 → batch 3 → batch 4. When the second batch is batch 4, since the frequency difference between the frequency points in batch 3 and the frequency points in batch 4 is smaller than that between batch 1 and batch 2, the wave field reconstruction device 212 uses the frequency points in batch 3 as the frequency points of the batch whose wave field has been solved.

[0209] The two optional implementation methods described above are merely different ways of obtaining the frequency points of the batch of solved wave fields by the wave field reconstruction device 212. In other embodiments, the wave field reconstruction device 212 may also use other implementation methods to obtain the frequency points of the batch of solved wave fields. This application embodiment does not limit this.

[0210] In one alternative implementation, for each frequency point in the second batch, the wave field reconstruction device 212 obtains a candidate frequency point that matches the frequency value of each frequency point from the frequency points of the batch whose wave fields have been solved, and obtains the first wave field based on the wave field corresponding to the candidate frequency point.

[0211] The wave field corresponding to the candidate frequency point can be the wave field corresponding to the candidate frequency point when the iteration process converges.

[0212] Here, "candidate frequency points matching the frequency value of each frequency point" can be the frequency point with the smallest distance between its frequency value and the frequency value of each frequency point in the batch of frequency points whose wave field has been solved. Alternatively, "candidate frequency points matching the frequency value of each frequency point" can be the frequency points in the batch of frequency points whose frequency value is less than or equal to a preset distance threshold. That is, for each frequency point in the second batch, there are one or more candidate frequency points that match the frequency value of each frequency point.

[0213] In the first alternative approach, for each frequency point in the second batch, there exists a candidate frequency point. The wavefield reconstruction device 212 uses the wavefield corresponding to the candidate frequency point as the first wavefield corresponding to that frequency point.

[0214] In the second alternative approach, for each frequency point in the second batch, there are multiple candidate frequencies. The wavefield reconstruction device 212 uses the arithmetic mean, weighted average, median, maximum, or minimum value of the wavefields corresponding to the multiple candidate frequencies as the first wavefield corresponding to that frequency point.

[0215] In the third alternative approach, for each frequency point in the second batch, there are multiple candidate frequencies. The wavefield reconstruction device 212 interpolates the wavefields corresponding to the multiple candidate frequencies to obtain the first wavefield corresponding to that frequency point. For example, the wavefield reconstruction device 212 performs nearest neighbor interpolation, linear interpolation, quadratic interpolation, or cubic interpolation on the wavefields corresponding to the multiple candidate frequencies based on the frequency value of that frequency point and the frequency values ​​of the multiple candidate frequencies to obtain the first wavefield corresponding to that frequency point.

[0216] The above three optional methods are only different ways of obtaining the first wave field by the wave field reconstruction device 212. In other embodiments, the wave field reconstruction device 212 can also use other methods to obtain the first wave field. For example, the wave field reconstruction device 212 can also use the embodiment provided in FIG10 below to obtain the first wave field. This application embodiment does not limit this.

[0217] In one alternative implementation, for each frequency point in the second batch, after acquiring the first wavefield of that frequency point, the wavefield reconstruction device 212 uses the first wavefield of that frequency point as input to the wave equation and solves the wave equation with reference to S640 above to obtain the second wavefield of that frequency point. After acquiring the second wavefield of each frequency point in the second batch, the wavefield reconstruction device 212 selects a third batch from the remaining batches and solves the wavefield corresponding to each frequency point in the third batch with reference to S650 above, until the wavefield of each batch in multiple batches has been solved. Then, the wavefield reconstruction device 212 executes S660 below to determine the structure of the target object.

[0218] For example, taking the multiple frequency points corresponding to the target object provided in Figure 6 as an example, as shown in Figure 7, Figure 7 is a schematic diagram of the wave field solution process provided in this application. In the wave field solution process of batch 1, the information of the zero field, wave velocity field, and wave signal is used as the input of the wave equation of batch 1. The wave field of batch 1 is solved iteratively by the CBS algorithm to obtain wave field 1 corresponding to the frequency point of batch 1. In the wave field solution process of batch 2, the information of wave field 1, wave velocity field, and wave signal corresponding to the frequency point of batch 1 is used as the input of the wave equation of batch 2. The wave field of batch 2 is solved iteratively by the CBS algorithm to obtain wave field 2 corresponding to the frequency point of batch 2. In the wave field solution process of batch 3, the information of wave field 2, wave velocity field, and wave signal corresponding to the frequency point of batch 2 is used as the input of the wave equation of batch 3. The wave field of batch 3 is solved iteratively by the CBS algorithm to obtain wave field 3 corresponding to the frequency point of batch 3. In the process of solving the wave field of batch 4, the information of wave field 3, wave velocity field and wave signal corresponding to the frequency point of batch 3 is used as the input of the wave equation of batch 4, and the wave field 4 of batch 4 is solved iteratively by CBS algorithm.

[0219] As shown in Figure 7, for all batches except the first batch, the wavefield corresponding to the frequency points of the previously solved batch is used as the initial wavefield for the current batch. This allows for flexible setting of the initial wavefield during the wave equation solution process and ensures its rationality, making the input of the wave equation closer to the second wavefield corresponding to the frequency points of the second batch. This reduces the number of iterations in the wavefield solution process, improves reconstruction efficiency, and reduces computational resource consumption.

[0220] S660, the wave field reconstruction device 212 obtains the wave field of the reflected wave of the wave signal by the wave field corresponding to the frequency point of each batch in multiple batches, and determines the structure of the target object based on the wave field of the reflected wave.

[0221] The "wave field of the reflected wave of the wave signal" can refer to the wave field of the reflected wave obtained by fitting the wave equation to the predicted structure of the target object. In some alternative methods, the wave field of the reflected wave can also be called the fitted wave field, simulated wave field, fitted reflected wave field, predicted wave field, or other names, and the embodiments of this application do not limit this.

[0222] Among them, the wave field of the reflected wave of the wave signal includes the wave field of each spatial location of the target object at different sampling times.

[0223] In one alternative implementation, the wave field reconstruction device 212 can sort the wave fields corresponding to the frequency points of each batch in multiple batches according to the frequency points from large to small, so as to obtain the wave field of the reflected wave of the wave signal.

[0224] In one optional implementation, the wavefield reconstruction device 212 can sort the wavefields corresponding to the frequency points of each batch in multiple batches to obtain the wavefield of the initial reflected wave of the wave signal. The initial reflected wave of the wave signal is then subjected to one or more processing methods, including denoising, feature extraction, or wavefield transformation, to obtain the wavefield of the reflected wave of the wave signal.

[0225] Among them, noise removal can be achieved by the wave field reconstruction device 212 removing noise from the wave field of the initial reflected wave through a bandpass filter, a low-pass filter, or a high-pass filter.

[0226] Feature extraction can be performed by the wave field reconstruction device 212 to extract features such as amplitude, phase, and peak value from the wave field of the initial reflected wave.

[0227] Wave field transformation can refer to transforming the wave field of the initial reflected wave from the frequency domain to the time domain, or transforming the wave field of the initial reflected wave from the time domain to the frequency domain.

[0228] In a first optional implementation, to further determine the accuracy of the predicted structure of the target object, the wavefield reconstruction device 212 determines the reflected wave signal based on the wavefield of the reflected wave. The reflected wave signal is compared with the observation data to obtain the fitting error of the reflected wave signal relative to the observation data. If the fitting error is less than or equal to a preset error threshold, the predicted structure of the target object is taken as the structure of the target object. If the fitting error is greater than the preset error threshold, the wavefield reconstruction device 212 corrects the predicted structure of the target object based on the fitting error, obtaining a new predicted structure of the target object. Based on the new predicted structure of the target object, steps S640 to S650 are executed to obtain a new reflected wave signal, and the fitting error is updated based on the new reflected wave signal until the latest fitting error is less than or equal to the preset error threshold. Then, the predicted structure corresponding to the latest fitting error is taken as the structure of the target object.

[0229] The fitting error can be obtained by calculating the mean square error, L2 norm, or no correlation coefficient between the reflected wave signal and the observed data.

[0230] In one alternative example, the wavefield reconstruction device 212 can correct the predicted structure of the target object by using the gradient descent method, the conjugate gradient method, or the full-wave inversion method to obtain a new predicted structure of the target object.

[0231] In a second alternative implementation, the wavefield reconstruction device 212 can also pre-simulate different predicted structures for the target object. For each predicted structure, steps S640 to S650 are executed to obtain the wavefield of the reflected wave under each predicted structure. The wavefield of the reflected wave under each predicted structure is compared with the observed wavefield to obtain the error of the wavefield of the reflected wave under each predicted structure. The predicted structure with the smallest error among the candidate predicted structures whose error is less than or equal to the error threshold is selected as the structure of the target object.

[0232] The two optional implementation methods described above are merely different ways of determining the structure of the target object by the wave field reconstruction device 212. In other embodiments, the wave field reconstruction device 212 may also use other implementation methods to determine the structure of the target object, and this application embodiment does not limit this.

[0233] Based on the embodiment shown in Figure 5, the wave equation input is set based on the first wave field corresponding to the frequency points of the batch whose wave field has been solved, and the second wave field corresponding to any frequency point of the second batch other than the first batch is solved. This allows for flexible setting of the initial wave field value during the wave equation solution process and ensures the rationality of the initial wave field value setting, so that the input of the wave equation is closer to the second wave field corresponding to the frequency points of the second batch. This reduces the number of iterations in the wave field solution process, improves reconstruction efficiency, and reduces computational resources consumed. Furthermore, this method also divides multiple frequency points corresponding to the target object into batches, enabling parallel solution of all frequency points within the same batch, which can further improve reconstruction efficiency and reduce computational resources consumed.

[0234] Figure 5 above illustrates the wave field reconstruction method for wave signals provided in this application, with the wave field reconstruction device 212 as the executing entity. In some optional implementations, the wave field reconstruction method for wave signals provided in this application can also be executed by other computing devices. For example, such computing devices may include, but are not limited to: the wave equation solver 30, the wave imaging device 100, the server 201, distributed computing nodes, centralized computing nodes, structural surveying equipment, crack detectors, radar, or servers or computing nodes with wave field reconstruction functions, or other nodes or clusters capable of executing the wave field reconstruction method for wave signals provided in this application.

[0235] In one optional implementation, to ensure the reliability of the initial wavefield setting during the second batch of wavefield solution, the wavefield reconstruction device 212 selects frequencies with significant frequency value differences as a batch when decomposing multiple frequency points into multiple batches. This ensures that the wavefield differences between different frequencies within each batch are substantial. Frequency points with similar values ​​are then decomposed into different batches so that subsequent batches can utilize the wavefields corresponding to frequencies with similar values ​​from previous batches, ensuring the rationality of the initial wavefield value setting.

[0236] The following is an exemplary description of how the wave field reconstruction device 212 decomposes multiple frequency points into multiple batches of frequency points based on frequency values.

[0237] Please refer to Figure 8, which is a schematic diagram of the batch division process provided in this application. The batch division process shown includes steps S631A to S632A.

[0238] S631A, the wave field reconstruction device 212 sorts the frequency points of the target object in ascending order of frequency value to form a frequency point sequence.

[0239] S632A, the wave field reconstruction device 212 divides the frequency points in the frequency point sequence that are spaced apart into the same batch according to the batch number, thus obtaining multiple batches.

[0240] In one alternative implementation, during the initial batch partitioning, starting from the first frequency point in the frequency point sequence, frequencies spaced apart by a certain number of batches are assigned to the first batch. In subsequent batch partitioning, the next frequency point in the frequency point sequence adjacent to a frequency point from the previous batch is assigned to the current batch.

[0241] For example, taking a frequency sequence including ω1, ω2, ..., ωn as an example, when the number of batches is m, for the i-th batch, starting from the i-th frequency point ωi in the frequency sequence, the frequency points every m intervals are taken as the frequency points in the i-th batch, that is, the frequency points in the i-th batch are (ωi, ωi+m, ωi+2m, ...). For the (i+1)-th batch, the next frequency point (ωi+1, ωi+1+m, ωi+1+2m, ...) adjacent to the frequency point in the i-th batch is assigned to the (i+1)-th batch.

[0242] For example, taking the target object corresponding to multiple frequency points provided in Figure 6(a) above as an example, when the batch size is 4, a frequency point is selected every 4 frequency points during the batch division. As shown in Figure 8, starting from ω1, frequency points ω1, ω5, ω9, ω13, and ω17 are assigned to batch 1. During the batch 2 division process, starting from the frequency point ω2 adjacent to ω1, frequency points ω2, ω6, ω10, ω14, and ω18 are assigned to batch 2. During the batch 3 division process, starting from the frequency point ω3 adjacent to ω2, frequency points ω3, ω7, ω11, ω15, and ω19 are assigned to batch 3. During the batch 4 division process, starting from the frequency point ω4 adjacent to ω3, frequency points ω4, ω8, ω12, ω16, and ω20 are assigned to batch 4.

[0243] Based on the embodiment provided in Figure 8, in the process of decomposing multiple frequency points into multiple batches of frequency points, the wave field reconstruction device 212 divides the frequency points in the frequency point sequence into the same batch according to the number of batches. Since the frequencies between adjacent frequency points in the frequency point sequence are similar, the frequency points with similar frequency values ​​can be decomposed into different batches by means of interval sampling, so that the subsequent batches can use the wave field corresponding to the frequency points with similar frequency values ​​in the previous batches, ensuring the rationality of the initial wave field value setting.

[0244] Figure 8 above illustrates how the wavefield reconstruction device 212 decomposes multiple frequency points into multiple batches of frequency points, using the frequency value of a frequency point as an example. In other embodiments, to further ensure the wavefield difference between different frequency points in each batch, the wavefield reconstruction device 212 can select frequency points in the current batch from multiple frequency points with unsolved wavefields based on the wavefields corresponding to each frequency point in the previous batch.

[0245] As shown in Figure 9, which is a schematic diagram of the batch division process provided in this application, the batch division process includes steps S631B to S635B.

[0246] S631B, the wave field reconstruction device 212 sorts the frequency points of the target object in ascending order of frequency value to form a frequency point sequence.

[0247] S632B, wave field reconstruction device 212 selects the first batch of frequencies to be solved from the frequency point sequence.

[0248] In the first alternative implementation, the wave field reconstruction device 212 can select the first batch of frequencies to be solved from the frequency point sequence according to the batch number.

[0249] For example, the wave field reconstruction device 212 can obtain the number of frequency points contained in each batch according to the batch number and the total number of frequency points in the frequency point sequence. The first frequency point of the first batch to be solved is randomly selected from the frequency point sequence according to the number of frequency points contained in each batch.

[0250] In the second alternative implementation, the wavefield reconstruction device 212 can select the frequency points of the first batch to be solved, referring to the above-described S630, according to the batch quantity. This embodiment of the application will not elaborate further on this.

[0251] In a third alternative implementation, the wavefield reconstruction device 212 can select the frequency points of the first batch to be solved, referring to S632A above, according to the batch quantity. This embodiment will not be elaborated upon further.

[0252] The above three optional implementation methods are only different ways of selecting the first batch of frequencies for the first solution by the wave field reconstruction device 212. In other embodiments, the wave field reconstruction device 212 may also use other implementation methods to select the first batch of frequencies for the first solution. This application embodiment does not limit this.

[0253] S633B, the wave field reconstruction device 212 uses a preset wave field as the input of the wave equation to solve for the wave field corresponding to each frequency point in the first batch.

[0254] In one alternative implementation, the wave field reconstruction device 212 can solve for the wave field corresponding to each frequency point in the first batch by referring to the above S640. This embodiment of the application will not elaborate on this.

[0255] S634B, the wave field reconstruction device 212 selects frequency points of the second batch from the first remaining frequency points of the frequency point sequence based on the wave field similarity between each frequency point in the first batch.

[0256] The first remaining frequency point refers to the remaining frequency points in the frequency point sequence excluding the frequency points in the first batch.

[0257] In one optional implementation, if the wavefield similarity between all frequency points in the first batch is less than the wavefield similarity threshold, the wavefield reconstruction device 212 assigns the next frequency point adjacent to the mid-frequency point in the first batch from the first remaining frequency points to the second batch. This ensures a significant wavefield difference between frequency points in the second batch and ensures similarity between frequency points in adjacent batches, thereby guaranteeing the reliability of the initial wavefield of each frequency point in subsequent batches.

[0258] In another alternative implementation, if a first frequency point with a wavefield similarity greater than or equal to a wavefield similarity threshold exists in the first batch, the wavefield reconstruction device 212, based on the second frequency point in the first batch, assigns the frequency points adjacent to the second frequency point among the first remaining frequency points to the second batch. This reduces the wavefield similarity between frequency points in the second batch.

[0259] Among them, the second frequency point is the frequency point in the first batch where the wave field similarity is less than the wave field similarity threshold.

[0260] The two optional implementation methods mentioned above are only different ways of selecting the second batch of frequency points for the wave field reconstruction device 212. In other embodiments, the wave field reconstruction device 212 may also use other implementation methods to select the second batch of frequency points. This application embodiment does not limit this.

[0261] S635B, the wave field reconstruction device 212 solves the wave field corresponding to each frequency point in the second batch based on the wave field corresponding to each frequency point in the first batch, and selects the frequency points of the third batch from the second remaining frequency points of the frequency point sequence based on the wave field similarity between each frequency point in the second batch.

[0262] The second remaining frequency point refers to the remaining frequency points in the first remaining frequency point excluding the frequency points in the second batch.

[0263] In one alternative implementation, the wave field reconstruction device 212 refers to the above-described S650 to solve the wave field corresponding to each frequency point in the second batch, which is not limited in this embodiment of the application.

[0264] In one alternative implementation, the wave field reconstruction device 212 may refer to the above-described S634B to select a third batch of frequency points from the second remaining frequency points. This embodiment of the application will not elaborate on this.

[0265] In one optional implementation, after selecting the third batch of frequencies, the wavefield reconstruction device 212 determines whether there are still frequencies in the frequency sequence with unsolved wavefields (S1). If there are frequencies in the frequency sequence with unsolved wavefields, the wavefield reconstruction device 212 repeats S635B (S2) to continue dividing the next batch until all frequencies in the frequency sequence have solved their wavefields, at which point the wavefield reconstruction device 212 executes S660. If there are no frequencies in the frequency sequence with unsolved wavefields, the wavefield reconstruction device 212 executes S660 (S3).

[0266] Based on the embodiment provided in Figure 9, during the batch division process, the wave field reconstruction device 212 selects the frequency points in the current batch from multiple unsolved wave field frequency points based on the wave field corresponding to each frequency point in the previous batch, ensuring that the wave field difference between different frequency points in each batch is large and ensuring the rationality of the initial wave field value setting.

[0267] In one optional implementation, when allocating wavefield solutions, to shorten the wavefield rescue time and improve wavefield solution efficiency, during the wavefield solution process of the current batch, if the intermediate wavefield corresponding to each frequency point in the current batch meets the preset wavefield requirements during the iteration process, the wavefield reconstruction device 212 triggers the wavefield solution of the next batch. This shortens the waiting time for triggering the next batch. Furthermore, after triggering the next batch of wavefield solutions, the wavefield reconstruction device 212 can solve the wavefields of adjacent batches in parallel, further shortening the wavefield rescue time and improving wavefield solution efficiency.

[0268] In a first optional implementation, the preset wavefield requirement may be that the iterative residual of the intermediate wavefield corresponding to the frequency point is less than or equal to a residual threshold. The residual threshold is greater than the aforementioned convergence threshold.

[0269] In some alternative approaches, the residual threshold can be preset by the wavefield reconstruction device 212 or by the tester. Alternatively, the residual threshold can be set based on a convergence threshold, for example, by multiplying the convergence threshold by a coefficient. The coefficient is a decimal less than 1 and greater than 0.

[0270] In a second alternative implementation, the preset wave field requirement may also be that the change in the iterative residual of the intermediate wave field corresponding to the frequency point is less than a preset transformation threshold.

[0271] For example, during the wavefield solution process at a frequency point, the wavefield reconstruction device 212 performs differential analysis on the iterative residuals under different iterations to obtain the change in the iterative residuals under different iterations. For each iteration in multiple iterations, if the change in the iterative residual of that iteration is less than a preset transformation threshold, then it is determined that the intermediate wavefield obtained in that iteration meets the preset wavefield requirements.

[0272] In a third alternative implementation, the preset wave field requirement may also be that the number of iterations of the frequency point is greater than or equal to a threshold.

[0273] The above three optional implementation methods are merely alternatives to those with different preset wave field requirements. In other embodiments, the preset wave field requirements may take other forms. This application does not limit these aspects.

[0274] In one optional implementation, after the wavefield reconstruction device 212 triggers the wavefield solution for the next batch, it continues to solve the wavefield for the frequency points in the current batch until the iteration process for each frequency point in the current batch converges, thus obtaining the wavefield for each frequency point. To further shorten the wavefield solution time and reduce the number of iterations in the wavefield solution process, during the process of triggering the wavefield solution for the next batch, the wavelength reconstruction device obtains the first wavefield based on the intermediate wavefield corresponding to the frequency points of the batches whose wavefields have already been solved, and uses the first wavefield as the initial wavefield for the wavefield solution of the next batch.

[0275] Here, "the batch with the solved wavefield" can refer to a batch in which the intermediate wavefield has been solved. In some alternative methods, the batch with the solved intermediate wavefield can be a batch in which the wavefield has been solved, that is, a batch in which the iterative process at each frequency point has converged. In other alternative methods, the batch with the solved intermediate wavefield can be a batch in which the intermediate wavefield has been solved, but the wavefield has not yet been solved, that is, a batch in which the iterative process at each frequency point has not yet converged.

[0276] In one alternative approach, similar to the acquisition method of the first wavefield in S650 described above, during the process of obtaining the first wavefield based on the intermediate wavefields corresponding to the frequency points of the batches of solved wavefields, the first wavefield can be the intermediate wavefields corresponding to the frequency points of the batches of solved wavefields. Alternatively, the first wavefield can also be the arithmetic mean, weighted average, median, maximum, or minimum value of the intermediate wavefields corresponding to the frequency points of the batches of solved wavefields. Alternatively, the first wavefield can also be the interpolation result of the intermediate wavefields corresponding to the frequency points of the batches of solved wavefields.

[0277] For example, taking the multiple frequency points corresponding to the target object provided in Figure 6 as an example, when the first wavefield is the intermediate wavefield corresponding to the frequency points of the batch whose wavefields have been solved, as shown in Figure 10, which is a schematic diagram of the wavefield solution process provided in this application, in the wavefield solution process of batch 1, the information of the zero field, wave velocity field, and wave signal is used as the input of the wave equation of batch 1, and the wavefield of batch 1 is solved iteratively by the CBS algorithm. When the intermediate wavefield 1 corresponding to the frequency point of batch 1 is obtained, the wavefield solution of batch 2 is triggered. The information of the intermediate wavefield 1, wave velocity field, and wave signal corresponding to the frequency point of batch 1 is used as the input of the wave equation of batch 2, and the wavefield of batch 2 is solved iteratively by the CBS algorithm. When the intermediate wavefield 2 corresponding to the frequency point of batch 2 is obtained, the wavefield solution of batch 3 is triggered. The intermediate wavefield 2 corresponding to the frequency point of batch 2 is used as the input of the wave equation of batch 3, and the wavefield of batch 3 is solved iteratively by the CBS algorithm.

[0278] As shown in Figure 10, after triggering the wavefield solution for batch 2, the wavefield reconstruction device 212 continues to iteratively solve the wavefield for batch 1 using the CBS algorithm until the iteration process converges, thus obtaining the wavefield 1 corresponding to the frequency point of batch 1. Similarly, after triggering the wavefield solution for batch 3, the wavefield reconstruction device 212 continues to iteratively solve the wavefield for batch 2 using the CBS algorithm until the iteration process converges, thus obtaining the wavefield 2 corresponding to the frequency point of batch 2.

[0279] As shown in Figure 10, compared to the wavefield solution process provided in Figure 7, in Figure 10, the wavefield reconstruction device 212 starts the wavefield solution for the next batch ahead of time after obtaining the intermediate wavefield corresponding to the frequency point of the current batch. This increases the parallelism of the computation, thereby reducing the wavefield solution time and improving the efficiency of wavefield solution.

[0280] In one alternative implementation, starting the next batch of wavefield solutions early increases computational parallelism, requiring more computational resources. When the computing power of the device housing the wavefield reconstruction device 212 is limited, starting the next batch of wavefield solutions early increases the solution time for each batch, thus reducing wavefield solution efficiency. Conversely, when the computing power of the device housing the wavefield reconstruction device 212 is sufficient, waiting for the iterative process of all frequencies in the previous batch to converge before starting the next batch of wavefield solutions reduces the utilization of computing resources and decreases wavefield solution efficiency. Therefore, to improve computing resource utilization and wavefield solution efficiency, the wavefield reconstruction device 212 can determine whether to start the next batch of wavefield solutions early based on the computing power of the device housing the wavefield reconstruction device 212.

[0281] In the first optional example, after S630, the wavefield reconstruction device 212 obtains the computing power of the computing device where it is located. If the computing power is greater than a preset computing power threshold, the wavefield reconstruction device 212 starts the next batch of wavefield solutions ahead of schedule, following the wavefield solution process provided in Figure 10. If the computing power is less than the preset computing power threshold, the wavefield reconstruction device 212 starts the next batch of wavefield solutions after the iteration process of all frequencies in the previous batch has converged, following the wavefield solution process provided in Figure 7.

[0282] In the second optional example, after starting the solution for the current batch, the wavefield reconstruction device 212 obtains the computing power of the computing device where it is located. If the computing power is greater than a preset computing power threshold, the wavefield reconstruction device 212 starts solving the wavefield for the next batch after solving the intermediate wavefield at the frequency point of the current batch. If the computing power is less than the preset computing power threshold, the wavefield reconstruction device 212 starts solving the wavefield for the next batch after solving the wavefield at the frequency point of the current batch.

[0283] The two optional examples above are merely different implementations of the wavefield reconstruction device 212 determining whether to start the next batch of wavefield solutions ahead of schedule based on the computing power of the computing device where the wavefield reconstruction device 212 is located. In other embodiments, the wavefield reconstruction device 212 may also use other implementations to determine whether to start the next batch of wavefield solutions ahead of schedule. This application does not limit this.

[0284] In one alternative implementation, to better illustrate the wave field solution method provided in this application, the wave field reconstruction process for any frequency point in any batch is illustrated below.

[0285] First, taking the convergence of the frequency point iteration process and the initiation of the next batch of wave field solutions as an example, the wave field reconstruction process of the frequency point is illustrated.

[0286] As shown in Figure 11, Figure 11 is a schematic flowchart of the wave field reconstruction method for wave signals provided in this application. The flowchart of the wave field reconstruction method for wave signals shown includes steps S121 to S126.

[0287] S121, the wave field reconstruction device 212 acquires information about the wave signal and the wave velocity field.

[0288] S122, the wave field reconstruction device 212 selects the frequency points that need to be solved in the current batch from multiple frequency points corresponding to the target object.

[0289] S123, when the current batch is the first batch to be solved, the wave field reconstruction device 212 uses the zero field as the initial wave field for each frequency point in the current batch.

[0290] After executing S123, execute S215.

[0291] S124, if the current batch is not the first batch to be solved, the wave field reconstruction device 212 constructs the initial wave field corresponding to each frequency point in the current batch based on the wave field of the frequency points of the solved wave field.

[0292] S125, the wave field reconstruction device 212 takes the initial wave field, wave velocity field and wave signal information as input and calls the CSB solver to solve the wave field of each frequency point in the current batch.

[0293] S126, saves the wave field solved for each frequency point in the current batch.

[0294] Based on the embodiment provided in Figure 11, the wave field creation device constructs an initial wave field for batches that are not solved for the first time, using the wave field at the frequency points of the solved wave field, thereby reducing the number of iterations required for wave field solution and improving computational efficiency.

[0295] Secondly, taking the example of starting the next batch of wavefield solutions ahead of time after solving the intermediate wavefield at a frequency point, the wavefield reconstruction process at a frequency point will be illustrated.

[0296] As shown in Figure 12, Figure 12 is a schematic flowchart of the wave field reconstruction method for wave signals provided in this application. The flowchart of the wave field reconstruction method for wave signals shown includes steps S131 to S137.

[0297] S131-S132: Refer to S121-S122 above. The embodiments of this application will not be repeated here.

[0298] S133, when the current batch is the first batch to be solved, the wave field reconstruction device 212 uses the zero field as the initial wave field for each frequency point in the current batch.

[0299] After executing S133, execute S135.

[0300] S134, if the current batch is not the first batch to be solved, the wavefield reconstruction device 212 constructs the initial wavefield corresponding to each frequency point in the current batch based on the intermediate wavefield of the frequency points of the intermediate wavefield that have been solved.

[0301] S135, the wave field reconstruction device 212 takes the information of the initial wave field, wave velocity field and wave signal as input, and calls the CSB solver to solve the wave field of each frequency point in the current batch.

[0302] S136, after solving the intermediate wave field of each frequency point in the current batch, save the intermediate wave field of each frequency point in the current batch, and select the frequency points to be solved in the next batch from the multiple frequency points corresponding to the target object.

[0303] If the intermediate wavefield of each frequency point in the current batch has not been solved, continue to execute S135 until the intermediate wavefield of each frequency point in the current batch is solved.

[0304] S137, if the CSB iteration of each frequency point in the current batch converges, save the wave field of each frequency point in the current batch.

[0305] If the CSB iteration for each frequency point in the current batch fails to converge, continue executing S135 until the CSB iteration for each frequency point in the current batch converges.

[0306] Based on the embodiment provided in Figure 12, the wavefield reconstruction device 212 can start the wavefield solution for the next batch in advance if the CSB iteration for each frequency point in the current batch has not converged, thereby increasing the parallelism of the calculation.

[0307] To achieve the functions of the above embodiments, the wave field reconstruction apparatus 212 includes hardware and / or software modules that execute the corresponding functions. Those skilled in the art should readily recognize that, based on the units and method steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0308] Figures 3 to 12 above describe in detail the wavefield reconstruction equipment, wavefield reconstruction device 212, and wavefield reconstruction method for wave signals provided in this application. The wavefield reconstruction device 212, based on the first wavefield corresponding to the frequency points of the batches of wavefields that have already been solved, sets the input of the wave equation and solves for the second wavefield corresponding to the frequency points of any second batch other than the first batch. This allows for flexible setting of the initial wavefield value during the wave equation solving process, reducing the required number of iterations for convergence and improving computational efficiency.

[0309] In this embodiment, the wavefield reconstruction device 212 can be grouped into functional modules according to the method example described above. For example, each functional group can be assigned to a specific functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module.

[0310] For example, taking the wave field reconstruction device 212 implemented by software modules as an example, as shown in Figure 13, the wave field reconstruction device 212 includes a signal acquisition module 121, a frequency acquisition module 122, a frequency batching module 123, a wave field solving module 124, and a reconstruction module 125.

[0311] The signal acquisition module 121 is used to acquire information about the wave signal of the structure used to detect the target object. For example, the signal acquisition module 121 executes S610 in Figure 5 above.

[0312] The frequency acquisition module 122 is used to determine multiple frequency points corresponding to the target object based on the information of the wave signal. For example, the frequency acquisition module 122 executes S620 in Figure 5 above.

[0313] The frequency segmentation module 123 is used to decompose frequency information into multiple batches of frequency information, each batch including at least one frequency information. For example, the frequency segmentation module 123 executes S630 in Figure 5 above.

[0314] The wavefield solving module 124 is used to solve for the wavefield corresponding to the frequency information of the first batch of multiple batches, using a preset wavefield as input to the wave equation; and to obtain the first wavefield corresponding to the frequency information of any second batch other than the first batch, based on the wave equation, and use the first wavefield as input to the wave equation to solve for the second wavefield corresponding to the frequency information of the second batch. For example, the wavefield solving module 124 executes S640 to S650 in Figure 5 above.

[0315] The reconstruction module 125 is used to obtain the wave field of the reflected wave of the wave signal by using the wave field corresponding to the frequency point information of each batch in multiple batches, and to determine the structure of the target object based on the wave field of the reflected wave. For example, the reconstruction module 125 executes S660 in Figure 5 above.

[0316] The signal acquisition module 121, frequency acquisition module 122, frequency batching module 123, wave field solving module 124, and reconstruction module 125 can be implemented in software or hardware. For example, the implementation of the wave field solving module 124 will be described below. Similarly, the implementation of the signal acquisition module 121, frequency acquisition module 122, frequency batching module 123, and reconstruction module 125 can refer to the implementation of the wave field solving module 124.

[0317] As an example of a software functional unit, processing module 132 may include code running on a computing instance. The computing instance may include at least one of a physical host (computing device), a virtual machine, and a container. Further, the aforementioned computing instance may be one or more. For example, processing module 132 may include code running on multiple hosts / virtual machines / containers. It should be noted that the multiple hosts / virtual machines / containers used to run the code may be distributed in the same region or in different regions. Further, the multiple hosts / virtual machines / containers used to run the code may be distributed in the same availability zone (AZ) or in different AZs, each AZ including one or more geographically proximate data centers. Typically, a region may include multiple AZs.

[0318] Similarly, multiple hosts / virtual machines / containers used to run this code can be distributed within the same Virtual Private Cloud (VPC) or across multiple VPCs. Typically, a VPC is set up within a region. Communication between two VPCs within the same region, as well as between VPCs in different regions, requires a communication gateway to be set up within each VPC to enable interconnection between VPCs.

[0319] As an example of a hardware functional unit, the processing module 132 may include at least one computing device, such as a server. Alternatively, the processing module 132 may also be a device implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be implemented using a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), generic array logic (GAL), or any combination thereof.

[0320] The processing module 132 includes multiple computing devices that can be distributed within the same region or in different regions. Similarly, the communication module 131 includes multiple computing devices that can be distributed within the same Availability Zone (AZ) or in different AZs. Likewise, the processing module 132 includes multiple computing devices that can be distributed within the same Virtual Private Cloud (VPC) or in multiple VPCs. These multiple computing devices can be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0321] It should be noted that, in other embodiments, the signal acquisition module 121 can be used to execute any step in the wavefield reconstruction method. The frequency acquisition module 122 can be used to execute any step in the wavefield reconstruction method. The frequency batching module 123 can be used to execute any step in the wavefield reconstruction method. The wavefield solving module 124 can be used to execute any step in the wavefield reconstruction method. The reconstruction module 125 can be used to execute any step in the wavefield reconstruction method. The signal acquisition module 121, frequency acquisition module 122, frequency batching module 123, wavefield solving module 124, and reconstruction module 125 can all be used to execute any step in the wavefield reconstruction method. The steps implemented by the signal acquisition module 121, frequency acquisition module 122, frequency batching module 123, wavefield solving module 124, and reconstruction module 125 can be specified as needed. The wave field reconstruction device 212 achieves all its functions by implementing different steps in the wave field reconstruction method through the signal acquisition module 121, frequency acquisition module 122, frequency batching module 123, wave field solution module 124, and reconstruction module 125.

[0322] For example, taking the wave field reconstruction device 212 implemented through a hardware structure as an example, as shown in FIG14, the wave field reconstruction device 212 may include a bus 142, a processor 144, a memory 146, and a communication interface 148. The processor 144, the memory 146, and the communication interface 148 communicate with each other through the bus 142. The wave field reconstruction device 212 may be a server or a terminal device. It should be understood that this application does not limit the number of processors 144 and memory 146 in the wave field reconstruction device 212. In an optional embodiment, when the wave field reconstruction device 212 is implemented through a hardware structure, the wave field reconstruction device 212 may also be referred to as a computing device, a computing node, or a computing device cluster, etc., and this embodiment does not limit this.

[0323] Bus 142 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, only one line is used in Figure 14, but this does not imply that there is only one bus or one type of bus. Bus 142 can include pathways for transmitting information between various components of the wave field reconstruction device 212 (e.g., memory 146, processor 144, communication interface 148).

[0324] Processor 144 may include any one or more processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0325] In this application, processor 144 can execute the wavefield reconstruction method for the wave signal provided in FIG5 above. For example, it acquires information about the wave signal used to detect the structure of a target object. Based on the information about the wave signal, it determines multiple frequency points corresponding to the target object and decomposes these multiple frequency points into multiple batches of frequency points. For the first batch of frequency points solved in the multiple batches, it uses a preset wavefield as input to the wave equation to solve for the wavefield corresponding to each frequency point in the first batch. For any other second batch of frequency points besides the first batch, it acquires the first wavefield corresponding to the frequency points of the batch whose wavefield has been solved according to the wave equation, and uses the first wavefield as input to the wave equation to solve for the second wavefield corresponding to the frequency points of the second batch. It also obtains the wavefield of the reflected wave of the wave signal through the wavefield corresponding to the frequency points of each batch in the multiple batches, and determines the structure of the target object based on the wavefield of the reflected wave.

[0326] Memory 146 may include volatile memory, such as random access memory (RAM). Processor 144 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0327] The memory 146 stores executable program code, and the processor 144 executes the executable program code to implement the functions of the aforementioned communication module 131, processing module 132, and storage module 133, thereby realizing the wave field reconstruction method for wave signals. That is, the memory 146 stores instructions for executing the wave field reconstruction method for wave signals.

[0328] The communication interface 148 uses transceiver modules such as, but not limited to, network interface cards and transceivers to enable communication between the wave field reconstruction device 212 and other devices or communication networks.

[0329] The wave field reconstruction method for wave signals disclosed in the above embodiments can be applied to, or implemented by, processor 144. Processor 144 can be an integrated circuit chip with signal processing capabilities.

[0330] In implementation, each step of the above method can be completed by the integrated logic circuits in the hardware of the processor 144 or by instructions in software form. The processor 144 can be a general-purpose processor, including a CPU, a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete vacuum tubes or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly embodied in the execution of the hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 146, and the processor 144 reads the information in memory 146 and completes the steps of the above method in combination with its hardware.

[0331] In one possible implementation, the processor 144 can also be used to execute a wave field reconstruction method for wave signals. For specific implementation, please refer to the embodiments provided above for the wave field reconstruction method for wave signals. The embodiments of this application will not be repeated here.

[0332] In this embodiment of the application, the chip system may be composed of chips or may include chips and other discrete devices.

[0333] This application also provides a computer program product containing instructions. The computer program product may be software or program products containing instructions, capable of running on a computing device or stored on any usable medium. When the computer program product is run on at least one computing device, it causes the at least one computing device to perform the wavefield reconstruction method for the described wave signal.

[0334] For example, when a computer program product is run on at least one computing device, the at least one computing device performs the wave field reconstruction method of the wave signal shown in Figure 5.

[0335] This application also provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be implemented by a computer program instructing related hardware. This program can be stored in the computer-readable storage medium, and when executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be a terminal of any of the foregoing embodiments, such as an internal storage unit including a data transmission end and / or a data receiving end, like a hard disk or memory of the terminal. The computer-readable storage medium can also be an external storage device of the terminal, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal. Further, the computer-readable storage medium can include both the internal storage unit and the external storage device of the terminal. The computer-readable storage medium is used to store the computer program and other programs and data required by the terminal. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0336] It should be noted that the terms "first" and "second," etc., in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0337] It should be understood that in this application, "at least one (item)" means one or more, "more than one" means two or more, "at least two (items)" means two or three or more, and "and / or" is used to describe the relationship between related objects, indicating that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the related objects before and after are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0338] It should be understood that in the embodiments of this application, "B corresponding to A" means that B is associated with A. For example, B can be determined based on A. It should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information. Furthermore, the term "connection" in the embodiments of this application refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices, and the embodiments of this application do not impose any limitations on this.

[0339] Unless otherwise specified, the term "transmission" in the embodiments of this application refers to bidirectional transmission, encompassing the actions of sending and / or receiving. Specifically, "transmission" in the embodiments of this application includes sending data, receiving data, or both sending and receiving data. In other words, data transmission here includes uplink and / or downlink data transmission. Data may include channels and / or signals; uplink data transmission refers to uplink channel and / or uplink signal transmission, and downlink data transmission refers to downlink channel and / or downlink signal transmission.

[0340] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for wave field reconstruction of a wave signal, characterized in that, The method includes: Acquire information about wave signals used to probe the structure of the target object; Based on the information of the wave signal, determine multiple frequency point information corresponding to the target object; The frequency point information is decomposed into multiple batches of frequency point information, each batch including at least one frequency point information; For the frequency information of the first batch in the multiple batches, the preset wave field is used as the input of the wave equation to solve for the wave field corresponding to the frequency information of the first batch. For frequency information of any second batch other than the first batch, obtain the first wave field corresponding to the frequency information of the batch whose wave field has been solved according to the wave equation, and use the first wave field as the input of the wave equation to solve the second wave field corresponding to the frequency information of the second batch. The wave field of the reflected wave of the wave signal is obtained by using the wave field corresponding to the frequency point information of each batch in the multiple batches, and the structure of the target object is determined based on the wave field of the reflected wave.

2. The method according to claim 1, characterized in that, The wave equation is solved using the convergent Born series CBS.

3. The method according to claim 1 or 2, characterized in that, In each of the multiple batches, adjacent frequency point information is spaced m times apart, where m is the total number of the multiple batches.

4. The method according to claim 1 or 2, characterized in that, For each of the multiple batches, the wavefield similarity between different frequency points in each batch is less than the similarity threshold.

5. The method according to any one of claims 1 to 4, characterized in that, After decomposing the frequency point information into multiple batches of frequency point information, the method further includes: For the frequency information of the first batch in the multiple batches, a preset wave field is used as the input of the wave equation, and the wave equation is solved iteratively. During the iteration process, if the intermediate value corresponding to the frequency point information of the first batch meets the preset wave field requirements, the frequency point information of any other second batch besides the first batch in the multiple batches is obtained, and the first wave field step corresponding to the frequency point information of the batch whose wave field has been solved according to the wave equation is executed. Alternatively, if the iterative process converges, obtain the frequency information of any second batch other than the first batch among the multiple batches, and execute the first wave field step corresponding to the frequency information of the batch whose wave field has been solved according to the wave equation.

6. The method according to any one of claims 1 to 5, characterized in that, The first wave field includes: the wave field corresponding to the frequency information of the batch of wave fields that have been solved according to the wave equation, or the interpolation result of the wave field corresponding to the frequency information of the batch of wave fields that have been solved according to the wave equation.

7. The method according to any one of claims 1 to 5, characterized in that, The first wavefield includes: an intermediate wavefield corresponding to the frequency information of a batch of wavefields solved according to the wave equation, or an interpolation result of the intermediate wavefield corresponding to the frequency information of a batch of wavefields solved according to the wave equation; the intermediate wavefield is an intermediate value in the iterative solution process of the wave equation; the intermediate value meets a preset wavefield requirement; the preset wavefield requirement includes: the iteration residual is less than or equal to a residual threshold, or the number of iterations is greater than or equal to a threshold.

8. A wave field reconstruction device, characterized in that, The device includes: The signal acquisition module is used to acquire information about wave signals used to detect the structure of the target object. The frequency acquisition module is used to determine multiple frequency point information corresponding to the target object based on the information of the wave signal. The frequency point batching module is used to decompose the frequency point information into multiple batches of frequency point information, each batch including at least one frequency point information; The wave field solving module is used to solve for the wave field corresponding to the frequency point information of the first batch of the multiple batches by using a preset wave field as the input of the wave equation, and to obtain the first wave field corresponding to the frequency point information of any second batch other than the first batch by using the preset wave field as the input of the wave equation, and to solve for the second wave field corresponding to the frequency point information of the second batch by using the preset wave field as the input of the wave equation. The reconstruction module is used to obtain the wave field of the reflected wave of the wave signal through the wave field corresponding to the frequency point information of each batch in the plurality of batches, and to determine the structure of the target object based on the wave field of the reflected wave.

9. The apparatus according to claim 8, characterized in that, The wave equation is solved using the convergent Born series CBS.

10. The apparatus according to claim 8 or 9, characterized in that, In each of the multiple batches, adjacent frequency point information is spaced m times apart, where m is the total number of the multiple batches.

11. The apparatus according to claim 8 or 9, characterized in that, For each of the multiple batches, the wavefield similarity between different frequency points in each batch is less than the similarity threshold.

12. The apparatus according to any one of claims 8 to 11, characterized in that, The wave field solving module is used for: For the frequency information of the first batch in the multiple batches, a preset wave field is used as the input of the wave equation, and the wave equation is solved iteratively. During the iteration process, if the intermediate value corresponding to the frequency point information of the first batch meets the preset wave field requirements, the frequency point information of any other second batch besides the first batch in the multiple batches is obtained, and the operation of obtaining the first wave field corresponding to the frequency point information of the batch whose wave field has been solved according to the wave equation is executed. Alternatively, if the iterative process converges, obtain the frequency information of any second batch other than the first batch among the multiple batches, and perform the operation of obtaining the first wave field corresponding to the frequency information of the batch whose wave field has been solved according to the wave equation.

13. The apparatus according to any one of claims 8 to 12, characterized in that, The first wave field includes: the wave field corresponding to the frequency information of the batch of wave fields that have been solved according to the wave equation, or the interpolation result of the wave field corresponding to the frequency information of the batch of wave fields that have been solved according to the wave equation.

14. The apparatus according to any one of claims 8 to 12, characterized in that, The first wavefield includes: an intermediate wavefield corresponding to the frequency information of a batch of wavefields solved according to the wave equation, or an interpolation result of the intermediate wavefield corresponding to the frequency information of a batch of wavefields solved according to the wave equation; the intermediate wavefield is an intermediate value in the iterative solution process of the wave equation; the intermediate value meets a preset wavefield requirement; the preset wavefield requirement includes: the iteration residual is less than or equal to a residual threshold, or the number of iterations is greater than or equal to a threshold.

15. A computer program product containing instructions, characterized in that, When the instructions are executed by the computing device, the computing device performs the method as described in any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that, It includes computer program instructions, which, when executed by a computing device, cause the computing device to perform the method as described in any one of claims 1 to 7.

Images