Signal processing method and related device

Abstract

The application provides a signal processing method and related equipment. The method comprises iteratively performing the following operations until a first preset condition is met: obtaining phase data of multiple signals; sorting the phase data according to the acquisition time, and calculating the phase difference between adjacent phase data; any two adjacent signals correspond to a phase difference; determining at least one phase difference through a preset time window; in response to any phase difference in the preset time window satisfying a second preset condition, updating the phase data of the signals corresponding to the phase difference and all phase data after the phase difference in the preset time window; and moving the preset time window according to a preset step. Through the above method, the signal processing accuracy can be improved, the interference of abnormal data on the system can be reduced, and the utilization rate of signal data can be improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a signal processing method and related equipment. Background Technology

[0002] When using optical fiber as a transmission medium to transmit radio frequency signals, the effects of external forces and temperature on the optical fiber can cause phase drift of the radio frequency signal, which in turn affects the stability of the system.

[0003] In related technologies, the phase jitter of the link carried on the radio frequency signal transmitted back and forth is utilized. Specifically, the signal returned to the local end is phase-discriminated with the reference signal to determine the error signal. Then, the error signal is fed back to the compensation device to obtain a phase pre-compensation signal. After transmission through the optical fiber link, the phase of the pre-compensation signal cancels out the phase jitter caused by the link, and a phase-stable compensation signal can be obtained at the remote end.

[0004] However, it is impossible to evaluate the data processing after achieving fiber optic frequency transmission synchronization, and the synchronization devices between different fiber optic devices cannot be used directly with each other, resulting in low scalability of the fiber optic frequency transmission system. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide a signal processing method and related equipment.

[0006] For the purposes described above, this application provides a signal processing method, comprising iteratively performing the following operations until a first preset condition is met:

[0007] Acquire phase data of multiple signals;

[0008] The phase data are sorted according to the acquisition time, and the phase difference between adjacent phase data is calculated; any two adjacent signals correspond to one phase difference;

[0009] At least one phase difference is determined by using a preset time window;

[0010] In response to any phase difference within the preset time window satisfying the second preset condition, the phase data of the signals corresponding to the phase difference and all phase differences after the phase difference within the preset time window are updated.

[0011] The preset time window moves according to the preset step size.

[0012] Optionally, the second preset condition includes the phase difference exceeding a preset threshold range;

[0013] The step of updating the phase data of the signals corresponding to any phase difference within the preset time window and all subsequent phase differences within the preset time window in response to any phase difference satisfying the second preset condition includes:

[0014] In response to any phase difference exceeding the preset threshold range, the phase difference and all phase differences following the phase difference within the preset time window are determined as the target phase difference;

[0015] Determine the target signal corresponding to the target phase difference, and update the phase data of the target signal according to the sum of the target phase data and the target phase difference.

[0016] Optionally, the step of determining the preset threshold range includes:

[0017] Acquire the phase data of the training signal;

[0018] Based on the phase data of the training signal, the optimal solution α of the following objective function is obtained. * ;

[0019]

[0020] stC≥α≥0;

[0021] Where C represents the preset penalty factor, α represents the Lagrange operator, x represents the sample data, and i and j represent the order of the sample data;

[0022] According to the optimal solution α * The preset threshold range is determined.

[0023] Optionally, the step of determining the preset threshold range further includes:

[0024] Acquire the phase data of the training signal;

[0025] Based on the phase data of the training signal, the optimal solution α of the following objective function is obtained. * ;

[0026]

[0027] stC≥α≥0;

[0028] In this invention, x and y refer to time index and phase data, respectively, and σ is the user-defined function arrival rate.

[0029] According to the optimal solution α * The preset threshold range is determined.

[0030] Optionally, after acquiring the phase data of the training signal, the process includes:

[0031] Based on the phase data of the acquired training signal, the standardized phase data is obtained using the following formula;

[0032]

[0033] Where x represents the phase data of any of the signals used for training, x min x represents the minimum value among all the phase data of the acquired training signals. max x′ represents the maximum value among all the phase data of the acquired training signals, and x′ represents the standardized phase data;

[0034] Based on the standardized phase data, a predetermined number of eigenvectors are obtained through principal component analysis algorithm;

[0035] The element values ​​in the predetermined number of feature vectors are used as the phase data of the training signal.

[0036] Optionally, the method for generating the phase data includes:

[0037] Acquire voltage data for multiple of the signals;

[0038] Based on the voltage data, the phase data of the signal is calculated using the following formula;

[0039]

[0040] Where V(t) represents the voltage data of the signal, V Max V represents the maximum value in the voltage data of the signal. Min This represents the minimum value in the voltage data of the signal. This refers to the phase data.

[0041] Optionally, the first preset condition includes receiving a termination processing instruction.

[0042] Based on the same inventive concept, this application also provides a signal processing apparatus, comprising:

[0043] The acquisition module is configured to acquire phase data of multiple of the signals;

[0044] The first calculation module is configured to sort the phase data according to the acquisition time and calculate the phase difference between adjacent phase data; any two adjacent signals correspond to one phase difference;

[0045] The determination module is configured to determine at least one phase difference through a preset time window;

[0046] The second calculation module is configured to update the phase data of the signals corresponding to any phase difference within the preset time window and all phase differences after the phase difference within the preset time window in response to any phase difference satisfying the second preset condition.

[0047] The moving module is configured to move the preset time window according to a preset step size.

[0048] Based on the same inventive concept, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the signal processing method as described in any of the above claims.

[0049] Based on the same inventive concept, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to execute any of the signal processing methods described above.

[0050] As can be seen from the above, the signal processing method and related equipment provided in this application confirm whether the compensated signal data meets the signal phase difference requirements through a preset judgment method, and process signals that do not meet the requirements. By uniformly evaluating and processing the data in the above manner, the synchronization devices between different sets of fiber optic equipment can be directly used by each other, improving the scalability of the transmission system. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a schematic flowchart illustrating a signal processing method according to one or more embodiments of this application;

[0053] Figure 2 This is a schematic diagram of the structure of a signal processing apparatus according to one or more embodiments of this application;

[0054] Figure 3 This is a phase value change diagram before applying the signal processing method in one embodiment of this application;

[0055] Figure 4 This is a phase value change diagram after applying a signal processing method according to an embodiment of this application;

[0056] Figure 5 This is a schematic diagram of the hardware structure of an electronic device according to one or more embodiments of this application. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0058] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0059] As described in the background section, with the development of communication technology and the demand for long-distance communication, the technology of analog transmission of radio frequency (RF) signals using optical fibers has emerged. This technology modulates the RF signal onto an optical carrier and then uses optical fibers for analog transmission of the RF signal. Because RF signals are affected by external environmental factors such as stress and temperature during transmission, phase drift is easily generated. This phase drift affects the accurate phase feeding of distributed antenna systems, as well as stable phase transmission in space systems and clock synchronization in distributed systems.

[0060] The relevant technology mainly utilizes the link phase jitter carried on the radio frequency signal during round-trip transmission. The specific process is as follows: the signal returned to the transmitting end is phase-discriminated with the reference signal to obtain an error signal. Then, a phase pre-compensation signal is calculated by a preset compensator. After transmission through the optical fiber link, the phase of the above-mentioned phase pre-compensation signal cancels out the phase jitter caused by the link, so that a phase-stable compensation signal can be obtained at the receiving end.

[0061] Whether transmitted via digital or analog signals, the principle remains the same: compensating the return signal carrying complete link jitter information to offset the phase jitter introduced by the link, and then transmitting the resulting phase-stable compensated signal. The evaluation of the compensated signal is primarily achieved through Allan variance assessment of phase noise.

[0062] However, related technologies cannot effectively handle signals with large outliers. For example, in harsh communication environments, more numerous and highly variable outliers are generated. Solutions based solely on existing technologies cannot effectively address these anomalous signals, which severely impact data processing evaluation. Furthermore, this approach prevents synchronization devices between different fiber optic equipment from directly interoperating, resulting in limited scalability of the fiber optic frequency transmission system.

[0063] To this end, this application proposes a signal processing method that uses an algorithm designed at the software level to determine whether the received signal exceeds a threshold and processes abnormal signals that exceed the threshold, so as to ensure the high versatility and high scalability of the received signal.

[0064] The technical solutions of one or more embodiments of this application will be described in detail below through specific examples.

[0065] refer to Figure 1 The signal processing method of one or more embodiments of this application includes iteratively performing the following operations until a first preset condition is met:

[0066] Step S101: Acquire phase data of multiple signals.

[0067] This step first acquires phase data for multiple signals. In some embodiments, the phase data of these signals is the data after compensation by a compensation device.

[0068] In some embodiments, these signals are obtained by receiving signals sent by a transport layer hardware device.

[0069] In some embodiments, the voltage data of the system can be obtained first, and then the voltage data can be converted into phase data. The method for generating the phase data includes: acquiring voltage data of multiple signals; and calculating the phase data of the signals based on the voltage data using the following formula. Where V(t) represents the voltage data of the above signal, V Max V represents the maximum value of the voltage data for the above signal. Min This represents the minimum value among the voltage data of the above signal. This refers to the phase data. In some embodiments, the voltage data can be processed first to remove outliers before data conversion.

[0070] Step S102: Sort the phase data according to the acquisition time and calculate the phase difference between adjacent phase data; any two adjacent signals correspond to one phase difference.

[0071] In developing this application, the applicant discovered that due to interference from external factors, severe jitter may occur when transmitting signals through fiber optic links. Since the compensation capability of the compensator is limited, the compensated signal received by the receiver may still contain anomalies. Therefore, the applicant proposes the signal processing method of this application to handle abnormal signals and improve signal utilization.

[0072] The technical solution proposed in this application determines whether a signal is abnormal by judging whether the phase difference between adjacent signals meets a preset condition.

[0073] Therefore, in this step, it is necessary to obtain the phase difference between adjacent signals. In some embodiments, the adjacent signals are two signals in a signal sequence obtained by sorting according to the acquisition time, and each pair of signals corresponds to a phase difference.

[0074] Step S103: Determine at least one phase difference through a preset time window.

[0075] After the phase difference is calculated in step S102, at least one of the phase differences is determined through a preset time window.

[0076] In some embodiments, the size of the aforementioned time window is set manually.

[0077] Step S104: In response to any phase difference within the preset time window satisfying the second preset condition, update the phase data of the signals corresponding to the phase difference and all phase differences after the phase difference within the preset time window.

[0078] In some embodiments, the second preset condition is satisfied when the phase difference is within a preset threshold range.

[0079] Therefore, in some embodiments, the above-mentioned response to any phase difference within the preset time window satisfying the second preset condition, updating the phase data of the phase difference and all phase differences after the phase difference within the preset time window, includes: responding to any of the phase differences exceeding the preset threshold range, determining the phase difference and all phase differences after the phase difference within the preset time window as target phase differences; determining the target signal corresponding to the target phase difference, and updating the phase data of the target signal according to the sum of the target phase data and the target phase difference.

[0080] Taking a specific embodiment of this application as an example, in this embodiment, the preset threshold range is from 0.0002 radians to 0.0006 radians. When it is determined that the phase difference of the nth bit exceeds this threshold range, the phase data of the signals corresponding to the phase difference of the nth bit and all phase differences after the nth bit within the time window are updated. In some embodiments, the phase data of the latter of the two signals corresponding to each phase difference can be updated. In some embodiments, the update method can be to add the original phase data to the phase difference of the nth bit to obtain the updated phase data.

[0081] In some embodiments, a preset threshold can be calculated based on the Support Vector Machine (SVM). SVM is a binary classification model whose basic model is a linear classifier with the largest margin defined on the feature space; SVM also includes kernel tricks, making it a substantially non-linear classifier. The basic idea behind SVM learning is to find a separating hyperplane that correctly partitions the training dataset and has the largest geometric margin.

[0082] Therefore, in some embodiments, the method for determining the preset threshold may include: acquiring phase data of the training signal; and solving for the optimal solution α of the following objective function based on the phase data of the training signal. * : stC≥α≥0; where C represents the preset penalty factor, α represents the Lagrange operator, x represents the sample data, and i and j represent the order of the sample data; according to the optimal solution α * Determine the aforementioned preset threshold range.

[0083] According to the principle of support vector machines, their objective is to find the optimal hyperplane ω. T The problem essentially aims to solve the equation x + b = 0. The minimum value of . Support vector machines can be further solved using the Lagrange optimization method, that is, by introducing the Lagrange function into the above formula, we get the following formula:

[0084]

[0085] The Lagrange method aims to transform the problem of finding the minimum value into solving the dual problem, α i As a multiplier in the Lagrange method, the partial derivative of the function L(ω,b,α) with respect to ω is zero, as shown in the following formula:

[0086]

[0087]

[0088] α i [yi (ω T ·x i )-1]=0;

[0089] Based on the above formula, it can be understood that the parameters ω and b of the hyperplane only satisfy α. i The data ≥ 0 are relevant; these data can be used to solve for y. i (ω T ·x i +b)=1, from which we obtain the following formula:

[0090]

[0091] After finding the optimal solution as α, we know that:

[0092]

[0093] The optimal hyperplane at this point is:

[0094]

[0095] Here, b represents the data boundary, which can be solved by substituting any support vector.

[0096] In some embodiments, the kernel function can be further set to a Gaussian kernel function. The core idea of ​​the Gaussian kernel function is to map each sample point to an infinite-dimensional feature space, thereby making the originally linearly inseparable data linearly separable.

[0097] Therefore, in some embodiments, the method for determining the preset threshold may further include: acquiring phase data of the training signal; and solving for the optimal solution α of the following objective function based on the phase data of the training signal. * : stC≥α≥0; where x and y refer to time index and phase data respectively in this invention, and σ is the user-defined function arrival rate; according to the optimal solution α * The preset threshold range is determined.

[0098] In some embodiments, due to the large amount of data and the complexity of the calculation process, it is difficult to solve the preset threshold. To reduce the calculation difficulty, the training signal can be preprocessed.

[0099] When using statistical analysis to study multivariate topics, too many variables increase the complexity of the research. Naturally, one hopes for fewer variables while obtaining more information. In many cases, variables are correlated; when two variables are correlated, it can be interpreted as overlapping information they reflect about the topic. Principal component analysis removes redundant (closely related) variables from the original set, creating as few new variables as possible that are pairwise uncorrelated and retain as much of the original information as possible.

[0100] In some embodiments, the phase data of the signal can be reduced in dimensionality using principal component analysis.

[0101] Therefore, in some embodiments, after acquiring the phase data of the training signal, the process includes: obtaining standardized phase data based on the acquired phase data of the training signal using the following formula; Where x represents any of the phase data of the signal used for training mentioned above, x min x represents the minimum value among all the phase data of the signals used for training described above. max x represents the maximum value among all the phase data of the signals used for training described above. ′ The above-mentioned standardized phase data is represented; based on the above-mentioned standardized phase data, a predetermined number of eigenvectors are obtained through principal component analysis algorithm; the element values ​​in the above-mentioned predetermined number of eigenvectors are used as the phase data of the training signal.

[0102] Step S105: Move the preset time window according to the preset step size.

[0103] After judging all phase differences within the preset time window, the preset time window is moved by a preset step size.

[0104] In some embodiments, the first preset condition described above may include receiving a termination processing instruction. Signal processing is stopped upon receiving the termination processing instruction.

[0105] In some embodiments, the first preset condition may include signal transmission termination, no new signal data received, and signal processing stopped.

[0106] Figure 3 and Figure 4 This is a schematic diagram comparing the signal before and after processing by the method provided in this application. The signal processing method proposed in this application can effectively solve the problem of drastic signal shift in phase under harsh communication environments and improve the stability of the system.

[0107] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0108] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0109] Based on the same inventive concept, corresponding to any of the above embodiments, this application also provides a signal processing device.

[0110] refer to Figure 2 The signal processing device includes:

[0111] The acquisition module 11 is configured to acquire phase data of the plurality of said signals;

[0112] The first calculation module 12 is configured to sort the phase data according to the acquisition time and calculate the phase difference between adjacent phase data; any two adjacent signals correspond to one phase difference;

[0113] The determination module 13 is configured to determine at least one phase difference through a preset time window;

[0114] The second calculation module 14 is configured to update the phase data of the signals corresponding to any phase difference within the preset time window and all phase differences after the phase difference within the preset time window in response to any phase difference satisfying the second preset condition.

[0115] The moving module 15 is configured to move the preset time window according to a preset step size.

[0116] In some embodiments, the second calculation module 14 is specifically configured to, in response to any phase difference exceeding the preset threshold range, determine the phase difference and all phase differences following the phase difference within the preset time window as target phase differences; determine the target signal corresponding to the target phase difference; and update the phase data of the target signal according to the sum of the target phase data and the target phase difference.

[0117] In some embodiments, the second calculation module 14 is configured to acquire phase data of the training signal; and, based on the phase data of the training signal, solve for the optimal solution α of the following objective function. * ; stC≥α≥0; where C represents the preset penalty factor, α represents the Lagrange operator, x represents the sample data, and i and j represent the order of the sample data; according to the optimal solution α * The preset threshold range is determined.

[0118] In some embodiments, the second calculation module 14 is configured to acquire phase data of the training signal; and, based on the phase data of the training signal, solve for the optimal solution α of the following objective function. * ; stC≥α≥0; where x and y refer to time index and phase data respectively in this invention, and σ is the user-defined function arrival rate; according to the optimal solution α * The preset threshold range is determined.

[0119] In some embodiments, the signal processing apparatus further includes a third calculation module 16, configured to obtain standardized phase data based on the phase data of the acquired training signal using the following formula; Where x represents the phase data of any of the signals used for training, x min x represents the minimum value among all the phase data of the acquired training signals. max x′ represents the maximum value among all the phase data of the acquired training signal; x′ represents the standardized phase data; based on the standardized phase data, a predetermined number of feature vectors are obtained through principal component analysis algorithm; the element values ​​of the predetermined number of feature vectors are used as the phase data of the training signal.

[0120] In some embodiments, the acquisition module 11 is specifically configured to acquire voltage data of a plurality of the signals; and calculate the phase data of the signals based on the voltage data using the following formula; Where V(t) represents the voltage data of the signal, V Max V represents the maximum value in the voltage data of the signal. Min This represents the minimum value in the voltage data of the signal. This refers to the phase data.

[0121] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.

[0122] The apparatus of the above embodiments is used to implement the corresponding signal processing method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0123] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the signal processing method described in any of the above embodiments.

[0124] Figure 5 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0125] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0126] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0127] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0128] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0129] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0130] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0131] The electronic devices described above are used to implement the corresponding signal processing methods in any of the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0132] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to perform the signal processing method as described in any of the above embodiments.

[0133] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0134] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the signal processing method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0135] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0136] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0137] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0138] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A signal processing method, characterized in that, This includes iteratively performing the following operations until the first preset condition is met: Acquire phase data of multiple signals; The phase data are sorted according to the acquisition time, and the phase difference between adjacent phase data is calculated; any two adjacent signals correspond to one phase difference; At least one phase difference is determined by using a preset time window; In response to any phase difference within the preset time window satisfying the second preset condition, the phase data of the signals corresponding to the phase difference and all phase differences after the phase difference within the preset time window are updated. The preset time window is moved according to a preset step size; The second preset condition includes the phase difference exceeding a preset threshold range; The step of updating the phase data of the signals corresponding to any phase difference within the preset time window and all subsequent phase differences within the preset time window in response to any phase difference satisfying the second preset condition includes: In response to any phase difference exceeding the preset threshold range, the phase difference and all phase differences following the phase difference within the preset time window are determined as the target phase difference; Determine the target signal corresponding to the target phase difference, and update the phase data of the target signal according to the sum of the target phase data and the target phase difference.

2. The signal processing method according to claim 1, characterized in that, The method for generating the phase data includes: Acquire voltage data for multiple of the signals; Based on the voltage data, the phase data of the signal is calculated using the following formula; ； in, This represents the voltage data of the signal. This represents the maximum value in the voltage data of the signal. This represents the minimum value in the voltage data of the signal. This refers to the phase data.

3. The signal processing method according to claim 1, characterized in that, The first preset condition includes receiving a termination processing instruction.

4. A signal processing apparatus, characterized in that, Used in the signal processing method according to claims 1-3 The device includes: The acquisition module is configured to acquire phase data of multiple of the signals; The first calculation module is configured to sort the phase data according to the acquisition time and calculate the phase difference between adjacent phase data; any two adjacent signals correspond to one phase difference; The determination module is configured to determine at least one phase difference through a preset time window; The second calculation module is configured to update the phase data of the signals corresponding to any phase difference within the preset time window and all phase differences after the phase difference within the preset time window in response to any phase difference satisfying the second preset condition. The moving module is configured to move the preset time window according to a preset step size.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 3.

6. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 3.

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