A Signal Data Alignment Method, Device, Medium and Equipment

Abstract

Embodiments of the present application disclose a signal data alignment method, apparatus, medium, and device, which relate to the field of communication technologies. First, through the acquisition of periodic signals, the waveform data within a single period is analyzed. After converting the signal data into a data matrix for processing, peak search is performed to obtain the minimum value of multiple pieces of time-domain waveform data within a single period and its corresponding coordinate index value. Considering the insufficient sampling resolution and the limited number of time-domain signal points collected each time, the searched position may not be the true peak position. Therefore, based on the position corresponding to the minimum value, the optimal value is solved by constructing an objective optimization function to obtain the accurate number of shift points. Finally, alignment operations are performed based on the number of shift points, without strictly requiring a high-precision trigger position, thereby improving the effect of aligning signal data.

Description

Technical Field

[0001] This application relates to the field of communication technologies, and in particular, to a signal data alignment method, apparatus, medium, and device. Background Art

[0002] In an actual broadband acquisition system, the non-ideal characteristics of the radio frequency circuit make it difficult to achieve the conditions of flat amplitude-frequency response and linear phase-frequency response over the full bandwidth, resulting in an inability to obtain an accurately reconstructed input signal. Therefore, corresponding all-passband amplitude-frequency response and phase-frequency response compensation and calibration are required.

[0003] To reduce the influence of noise on the system frequency response characteristic estimation, the most commonly used method is to utilize the multi-frame averaging technique during data acquisition. The multi-frame averaging technique reduces the influence of noise by averaging multiple sampled waveforms, and there is no bandwidth loss. However, multi-frame averaging requires strict signal data alignment for each captured waveform at the same trigger position. Due to insufficient sampling resolution and a limited number of time-domain signal points in each acquisition, the determined trigger position is not the accurate position, and the offset of the system trigger position leads to a reduction in the effect of signal data alignment. Summary of the Invention

[0004] The main objective of this application is to provide a signal data alignment method, apparatus, medium, and device, aiming to solve the problem of poor signal data alignment effect in the prior art.

[0005] To achieve the above objective, the technical solutions adopted in the embodiments of this application are as follows:

[0006] In a first aspect, an embodiment of this application provides a signal data alignment method, including the following steps:

[0007] Obtain the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the acquired periodic signal;

[0008] Process the signal to be processed according to the number of periods, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix;

[0009] Perform peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value;

[0010] Obtain the target delay dropout number within the search range of the delay dropout number with the aim of minimizing the value of the target optimization function; wherein, the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value;

[0011] Align the signal to be processed according to the target delay dropout number.

[0012] In a possible implementation of the first aspect, the signal to be processed is processed according to the number of cycles, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix, including:

[0013] The signal to be processed is truncated to obtain an aligned signal with an integer multiple of the cycle length;

[0014] According to the number of cycles and the number of sampling points, the aligned signal is equally divided to obtain a segmented aligned signal;

[0015] The segmented aligned signal is interpolated to obtain a data matrix; wherein, the recombined size of the data matrix is the product of the number of sampling points, the number of acquisitions of the periodic signal, and the number of cycles.

[0016] In a possible implementation of the first aspect, peak search is performed on the data matrix to obtain the minimum value and the coordinate index value of the minimum value, including:

[0017] Peak search is performed on each column of the data matrix to obtain the minimum value of each column and its coordinate index value;

[0018] The sorting function is used to sort the minimum values to obtain the smallest value as the peak;

[0019] The coordinate position corresponding to the peak is saved in a row vector, and the min function is used to obtain the minimum value of the row vector and the coordinate index value of the minimum value.

[0020] In a possible implementation of the first aspect, before obtaining the target delay loss number within the search range of the delay loss number with the aim of minimizing the value of the target optimization function, the method further includes:

[0021] Based on the minimum value and the coordinate index value of the minimum value, a target optimization function is constructed.

[0022] In a possible implementation of the first aspect, based on the minimum value and the coordinate index value of the minimum value, constructing a target optimization function includes:

[0023] Based on the minimum value and the coordinate index value of the minimum value, the non-target column data is aligned with the target column signal data to obtain the number of points to be discarded at the target end for the non-target column data;

[0024] According to the data before alignment and the number of points to be discarded, the data after alignment is obtained;

[0025] Under the minimum mean square error criterion, based on the data before alignment, the data after alignment, the number of sampling points, and the delay loss number, a target optimization function is constructed.

[0026] In a possible implementation manner of the first aspect, before obtaining the target delay loss number within the search range of the delay loss number with the aim of minimizing the value of the target optimization function, the method further includes:

[0027] Determine a search threshold;

[0028] Determine the left boundary of the search range according to the difference between the number of points to be discarded and the search threshold;

[0029] Determine the right boundary of the search range according to the sum of the number of points to be discarded and the search threshold;

[0030] Determine the search range according to the left boundary and the right boundary.

[0031] In a possible implementation manner of the first aspect, before obtaining the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal, the method further includes:

[0032] Obtain the number of sampling points according to the sampling rate and the fundamental frequency of the periodic signal.

[0033] In a second aspect, an embodiment of the present application provides a signal data alignment device, including:

[0034] An obtaining module, configured to obtain the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal;

[0035] A processing module, configured to process the signal to be processed according to the number of periods, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix;

[0036] A search module, configured to perform peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value;

[0037] A target module, configured to obtain the target delay loss number within the search range of the delay loss number with the aim of minimizing the value of the target optimization function; wherein, the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value;

[0038] An alignment module, configured to align the signal to be processed according to the target delay loss number.

[0039] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, storing a computer program, which when loaded and executed by a processor, implements the signal data alignment method provided in any one of the above first aspects.

[0040] In a fourth aspect, an embodiment of the present application provides an electronic device, including a processor and a memory, wherein,

[0041] The memory is used to store computer programs;

[0042] The processor is used to load and execute the computer program, so that the electronic device executes the signal data alignment method provided in any one of the above first aspects.

[0043] Compared with the prior art, the beneficial effects of this application are:

[0044] A signal data alignment method, device, medium and device provided by an embodiment of this application. The method includes: obtaining the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal; processing the signal to be processed according to the number of periods, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix; performing peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value; obtaining the target delay loss number within the search range of the delay loss number with the aim of minimizing the value of the target optimization function; wherein the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value; aligning the signal to be processed according to the target delay loss number. This application first analyzes the waveform data within a single period by collecting periodic signals, converts the signal data into a data matrix for processing, performs peak search, and obtains the minimum value of multiple time-domain waveform data within a single period and its corresponding coordinate index value. Considering that the sampling resolution is insufficient and the number of time-domain signal points collected each time is limited, the searched position may not be the true peak position. Therefore, based on the position corresponding to the minimum value, the optimal value is solved by constructing the target optimization function to obtain the accurate shift number, and finally the alignment operation is performed based on this shift number, without strictly requiring a high-precision trigger position, improving the effect of aligning signal data. Description of the Drawings

[0045] Figure 1 It is a schematic structural diagram of an electronic device for the hardware operating environment involved in an embodiment of this application;

[0046] Figure 2 It is a schematic flowchart of the signal data alignment method provided by an embodiment of this application;

[0047] Figure 3 It is a schematic diagram of a single-period narrow pulse time-domain signal before alignment;

[0048] Figure 4 It is a schematic diagram of a single-period narrow pulse time-domain signal after rough alignment using the method of this application;

[0049] Figure 5 It is a schematic diagram of the signal after fine alignment with the accurate shift number using the method of this application;

[0050] Figure 6It is a schematic diagram of unaligned single-cycle narrow pulse time-domain signals of fast-edge signals collected multiple times by a narrow pulse fast-edge signal generator;

[0051] Figure 7 It is a schematic diagram of time-domain signals of fast-edge signals collected multiple times by a narrow pulse fast-edge signal generator and aligned by the method of this application;

[0052] Figure 8 It is a module schematic diagram of the signal data alignment device provided by an embodiment of this application;

[0053] Markings in the figure: 101 - Processor, 102 - Communication bus, 103 - Network interface, 104 - User interface, 105 - Memory. Detailed implementation manners

[0054] It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0055] Refer to the appended Figure 1 appendix Figure 1 It is a schematic diagram of the structure of an electronic device in the hardware operating environment related to the solution of an embodiment of this application. The electronic device may include: a processor 101, such as a central processing unit (CPU), a communication bus 102, a user interface 104, a network interface 103, and a memory 105. Among them, the communication bus 102 is used to realize the connection and communication between these components. The user interface 104 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 104 may further include a standard wired interface and a wireless interface. The network interface 103 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WI-FI) interface). The memory 105 may optionally be a storage device independent of the aforementioned processor 101. The memory 105 may be a high-speed random access memory (Random Access Memory, RAM) memory or a stable non-volatile memory (Non-Volatile Memory, NVM), such as at least one disk memory; the processor 101 may be a general-purpose processor, including a central processor, a network processor, etc., or may also be a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0056] Those skilled in the art can understand that the structure shown in the appended Figure 1 does not constitute a limitation on the electronic device and may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements.

[0057] As shown in the attached Figure 1 figures, the memory 105 as a storage medium may include an operating system, a network communication module, a user interface module, and a signal data alignment device.

[0058] In the attached Figure 1 figures, the network interface 103 is mainly used for data communication with a network server; the user interface 104 is mainly used for data interaction with a user; the processor 101 and the memory 105 in this application may be provided in the electronic device, and the electronic device calls the signal data alignment device stored in the memory 105 through the processor 101 and executes the signal data alignment method provided by the embodiments of this application.

[0059] In an actual broadband acquisition system, the non-ideal characteristics of the radio frequency circuit will make it difficult for the signal to achieve the conditions of flat full-band amplitude-frequency response and linear phase-frequency response, so that the input signal cannot be accurately reconstructed. Therefore, corresponding full-passband amplitude-frequency response and phase-frequency response compensation calibration are required.

[0060] In the process of actual engineering applications, generally a group of multi-frequency point sine signals are used to estimate the system amplitude-frequency response, and fast-edge pulse signals with large bandwidth and rich frequency components are used to estimate the phase-frequency response. Then, FIR filters and IIR filters are designed according to the amplitude-frequency response and phase-frequency response respectively to achieve full-pass amplitude-frequency compensation and phase-frequency compensation. However, the energy of the input signal will attenuate as the frequency increases. In other words, the higher the frequency of the signal component, the greater the impact of environmental noise on the measurement accuracy of the amplitude-frequency response and phase-frequency response. At the same time, when estimating the system phase-frequency response characteristics, the small phase changes between frequency points caused by noise will cause large fluctuations in the obtained system group delay, thus posing new challenges to the design of the phase-frequency compensation IIR filter.

[0061] To reduce the impact of noise on the estimation of the system frequency response characteristics, the most commonly used method is to use the multi-frame averaging technique during data acquisition. The multi-frame averaging technique reduces the impact of noise by averaging multiple sampled waveforms, and there is no bandwidth loss. However, multi-frame averaging requires strict signal data alignment of each captured waveform according to the same trigger position. Due to insufficient sampling resolution and limited number of time-domain signal points in each acquisition, the determined trigger position is not the accurate position, and the offset of the system trigger position reduces the effect of signal data alignment.

[0062] To solve the above problems, referring to the attached Figure 2 figures, based on the hardware device of the foregoing embodiments, the embodiments of this application provide a signal data alignment method, including the following steps:

[0063] S10: Obtain the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal.

[0064] In the specific implementation process, the periodic narrow pulse signal is collected multiple times. When the sampling rate is f s , the fast-edge signal with a fundamental frequency of f c is collected multiple times to obtain the signal matrix X RSys , with a size of N×M, where N is the number of time-domain signal points collected each time, and M is the number of times the fundamental frequency signal is collected. Since the collected signal is a periodic signal, only the signal of one period needs to be analyzed. The calculation formula for the number of sampling points N period of the narrow pulse signal within a single period is:

[0065]

[0066] That is: Before obtaining the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal, the method further includes:

[0067] Obtain the number of sampling points according to the sampling rate and fundamental frequency of the periodic signal.

[0068] Then the number of periods K included in the time-domain signal with a length of N is:

[0069]

[0070] where floor(·) represents the floor operation.

[0071] S20: Process the signal to be processed according to the number of periods, the number of sampling points, and the number of times the periodic signal is collected to obtain a data matrix.

[0072] In the specific implementation process, to find the minimum value of multiple time-domain waveform data within a single period and its corresponding coordinate index value, the signal to be processed is processed and reorganized for subsequent processing. Specifically, processing the signal to be processed according to the number of periods, the number of sampling points, and the number of times the periodic signal is collected to obtain a data matrix includes:

[0073] Clip the signal to be processed to obtain an aligned signal with an integer multiple of the period length;

[0074] Perform equal division cutting on the aligned signal according to the number of periods and the number of sampling points to obtain a cut aligned signal;

[0075] Perform interpolation processing on the cut aligned signal to obtain a data matrix; where the reorganization size of the data matrix is the product of the number of sampling points and the number of times the periodic signal is collected multiplied by the number of periods.

[0076] In the specific implementation process, calculate the number of sample points contained in K periods, that is, K*N period , and then cut off the last (N - K*Nperiod) points of each acquired signal to obtain a signal X with an integer multiple of the period length IntPeriod . For the signal X to be aligned IntPeriod , perform column cutting to cut it into K equal parts, and the length of each part is N period . Subsequently, perform interpolation processing on each column of data, and finally obtain a data matrix X' with a recombination size of N period ×L, where L = M*K, that is, the product of the number of acquisitions and the number of periods

[0077] S30: Perform peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value

[0078] In the specific implementation process, perform peak search on each column of the data matrix to find its minimum value and its coordinate index value. Specifically, performing peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value includes:

[0079] Perform peak search on each column of the data matrix to obtain the minimum value of each column and its coordinate index value

[0080] Use the sorting function to sort the minimum values to obtain the smallest value as the peak

[0081] Save the coordinate position corresponding to the peak in a row vector, and use the min function to obtain the minimum value of the row vector and the coordinate index value of the minimum value

[0082] In the specific implementation process, in the MATLAB environment, use the function findpeaks(·) to find the values pks corresponding to all the minimum values of X' and the corresponding coordinate index values locs, and then use the sorting function sort(·) to sort pks from smallest to largest. The smallest value is the peak, and save the coordinate position corresponding to this peak in the row vector V = [V1, V2,..., V i ,..., V L , where i represents the i-th column data in the matrix X', and use the function min(·) to find the minimum value of the row vector V and its coordinate index value j

[0083] S40: With the aim of minimizing the value of the objective optimization function, obtain the target delay loss points within the search interval of the delay loss points; among them, the objective optimization function is constructed based on the minimum value and the coordinate index value of the minimum value

[0084] In the specific implementation process, due to insufficient sampling resolution and a limited number of time-domain signal points collected each time, the peak positions found in the foregoing steps may not be the true waveform peak positions in the real sense. Instead, the true peak positions are near the peak coordinate index value j of the searched peak. To obtain the precise number of shifted points and conduct a more refined peak search for fine-tuning the number of shifted points, by constructing an objective optimization function and using the one-dimensional search method to solve for the optimal value, that is: with the aim of minimizing the value of the objective optimization function, before obtaining the target number of delayed dropped points within the search range of the number of delayed dropped points, the method further includes:

[0085] Based on the minimum value and the coordinate index value of the minimum value, construct an objective optimization function. Specifically: Based on the minimum value and the coordinate index value of the minimum value, constructing an objective optimization function includes:

[0086] Based on the minimum value and the coordinate index value of the minimum value, align the non-target column data with the target column signal data to obtain the number of points to be discarded at the target end for the non-target column data;

[0087] According to the data before alignment and the number of points to be discarded, obtain the data after alignment;

[0088] Under the minimum mean square error criterion, based on the data before alignment, the data after alignment, the number of sampling points, and the number of delayed dropped points, construct an objective optimization function.

[0089] In the specific implementation process, use the data in column j as the reference signal That is, the target column signal data, and align the other column data, that is, the non-target column data to it. The number of points to be discarded at the target end, that is, the left end of the other column data is:

[0090]

[0091] Let the data before alignment of the i-th column be 0≤n<N period , and the data after alignment of the i-th column be Align each column of data, and it satisfies:

[0092]

[0093] Under the minimum mean square error criterion, the constructed objective optimization function is:

[0094]

[0095] wherein, is the number of delayed dropped points. Within the search range, find the value that minimizes the objective optimization function to obtain the precise number of shifted points. The search range is based on the search threshold and the number of points to be discarded at the target end Obtained, that is, before obtaining the target delay loss number within the search range of the delay loss number with the aim of minimizing the value of the target optimization function, the method further includes:

[0096] Determine the search threshold;

[0097] Determine the left boundary of the search range according to the difference between the number of points to be discarded and the search threshold;

[0098] Determine the right boundary of the search range according to the sum of the number of points to be discarded and the search threshold;

[0099] Determine the search range according to the left boundary and the right boundary.

[0100] Let the search threshold be N th , then the search range of the delay loss number is

[0101] S50: Align the signal to be processed according to the target delay loss number.

[0102] In the specific implementation process, alignment operation is performed according to the obtained delay number, that is, the target delay loss number. Let the data after alignment in the i-th column be If It satisfies:

[0103]

[0104] If It satisfies:

[0105]

[0106] In this embodiment, first, through the acquisition of periodic signals, the waveform data within a single period is analyzed. After converting the signal data into a data matrix for processing, peak search is performed to obtain the minimum value of multiple time-domain waveform data within a single period and its corresponding coordinate index value. Considering the insufficient sampling resolution and the limited number of time-domain signal points collected each time, the searched position may not be the true peak position. Therefore, based on the position corresponding to the minimum value, the optimal value is solved by constructing a target optimization function to obtain the accurate shift number. Finally, alignment operation is performed based on this shift number, without strictly requiring a high-precision trigger position, which improves the effect of aligning signal data.

[0107] The following further illustrates the present application in combination with actual engineering tests:

[0108] Test conditions and content: The experimental equipment includes a high-speed digital storage oscilloscope with a sampling rate of 80 GSa / s and a bandwidth of 20 GHz built based on broadband interleaved sampling technology, and a comb spectrum generator that can generate narrow pulse signals with a rise time less than 20 ps. The comb spectrum generator generates narrow pulse signals and inputs them into the oscilloscope. The oscilloscope collects unaligned signals multiple times and aligns the data according to the method of this application.

[0109] Analysis of test results: As shown in the attached Figure 3 Compared with the attached Figure 4 As shown in the comparison, the attached Figure 3 shows the single-cycle narrow pulse time-domain signal before alignment, and the attached Figure 4 shows the single-cycle narrow pulse time-domain signal after alignment. It can be seen from the attached drawings that after the time-domain waveform alignment is performed by the rough alignment method of the time-domain waveform of this application, the time offset of a certain column of signals relative to the reference signal becomes larger. This is because the sample value corresponding to the signal index position 600 of a certain column is not the true peak value, and its true peak value is near the index position 600. Therefore, this application performs further fine peak search to obtain the number of sample points to be discarded for each column of data relative to the reference signal. As shown in the attached Figure 5 After the signal is aligned by adjusting the accurate shift points using the method of this application, as shown in the attached drawings, it can be seen that after alignment, the fluctuation of each column of data relative to the reference signal is almost zero.

[0110] As shown in the attached Figure 6 Compared with the attached Figure 7 As shown in the comparison, fast-edge signals are collected multiple times based on a narrow pulse fast-edge signal generator. The attached Figure 6 shows the unaligned single-cycle narrow pulse time-domain signal, and its signal fluctuation range is about 5 sampling points. The attached Figure 7 shows the time-domain signal after the time-domain waveform alignment is performed by the method of this application. Its signal fluctuation drops to about 1 sampling point. This fluctuation is mostly caused by noise, and the noise can be reduced after averaging the signal. Thus, the phase-frequency characteristics of the system can be accurately extracted. As in the above embodiment, the method proposed in this application only needs to ensure that the signal rising edge is within the acquisition window, without strict digital triggering and additional hardware circuits. By using a rough plus fine-tuning alignment method, it effectively avoids the problem of inaccurate peak positioning caused by insufficient sampling resolution and limited number of time-domain signal points collected each time, and realizes more accurate data alignment.

[0111] Referring to the attached Figure 8 , based on the same inventive concept as in the foregoing embodiments, the embodiment of this application also provides a signal data alignment device, including:

[0112] An obtaining module, which is used to obtain the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal;

[0113] A processing module, which is used to process a signal to be processed according to the number of cycles, the number of sampling points, and the number of acquisitions of the periodic signal, so as to obtain a data matrix;

[0114] A search module, which is used to perform peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value;

[0115] A target module, which is used to obtain a target delay loss number within the search range of the delay loss number with the aim of minimizing the value of the target optimization function; wherein, the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value;

[0116] An alignment module, which is used to align the signal to be processed according to the target delay loss number.

[0117] Those skilled in the art should understand that the division of each module in the embodiment is only a division of logical functions. In actual application, they can be fully or partially integrated into one or more actual carriers, and these modules can all be implemented in the form of software called by a processing unit, or all be implemented in the form of hardware, or be implemented in the form of a combination of software and hardware. It should be noted that each module in the signal data alignment device in this embodiment corresponds one by one to each step in the signal data alignment method in the foregoing embodiment. Therefore, the specific implementation manners of this embodiment can refer to the implementation manners of the foregoing signal data alignment method, and will not be elaborated here.

[0118] Based on the same inventive concept as in the foregoing embodiment, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when loaded and executed by a processor, implements the signal data alignment method provided by the embodiment of the present application.

[0119] Based on the same inventive concept as in the foregoing embodiment, an embodiment of the present application further provides an electronic device, including a processor and a memory, wherein,

[0120] The memory is used to store a computer program;

[0121] The processor is used to load and execute the computer program so that the electronic device executes the signal data alignment method provided by the embodiment of the present application.

[0122] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disc, or CD-ROM; or may be various devices including one or any combination of the foregoing memories. The computer may be various computing devices including intelligent terminals and servers.

[0123] In some embodiments, executable instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0124] As an example, executable instructions may, but need not, correspond to a file in a file system, may be stored as part of a file that stores other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0125] By way of example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0126] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0127] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0128] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a multimedia terminal device (which can be a mobile phone, a computer, a television receiver, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0129] In summary, a signal data alignment method, apparatus, medium, and device provided by the present application. The method includes: obtaining the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal; processing the signal to be processed according to the number of periods, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix; performing peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value; obtaining the target delay loss number within the search range of the delay loss number for the purpose of minimizing the value of the target optimization function; wherein the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value; aligning the signal to be processed according to the target delay loss number. The present application first analyzes the waveform data within a single period by collecting the periodic signal, converts the signal data into a data matrix for processing, performs peak search, and obtains the minimum value of multiple time-domain waveform data within a single period and its corresponding coordinate index value. Considering that the sampling resolution is insufficient and the number of time-domain signal points collected each time is limited, the searched position may not be the true peak position. Therefore, based on the position corresponding to the minimum value, the optimal value is solved by constructing the target optimization function, and the accurate shift number is obtained. Finally, the alignment operation is performed based on the shift number, without strictly requiring a high-precision trigger position, improving the effect of aligning the signal data.

[0130] The foregoing are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A signal data alignment method, characterized in that, Including the following steps: Obtain the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the collected periodic signal; Process the signal to be processed according to the number of periods, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix; Perform peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value; Aim to minimize the value of the target optimization function, and obtain the target delay dropout number within the search range of the delay dropout number; wherein, the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value; Align the signal to be processed according to the target delay dropout number.

2. The signal data alignment method according to claim 1, wherein The step of processing the signal to be processed according to the number of periods, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix includes: Clip the signal to be processed to obtain an aligned signal to be aligned with an integer multiple of the period; Equally divide the aligned signal to be aligned according to the number of periods and the number of sampling points to obtain a cut aligned signal to be aligned; Perform interpolation processing on the cut aligned signal to be aligned to obtain a data matrix; wherein, the recombined size of the data matrix is the product of the number of sampling points and the number of acquisitions of the periodic signal and the number of periods.

3. The signal data alignment method according to claim 1, wherein The step of performing peak search on the data matrix to obtain the minimum value and the coordinate index value of the minimum value includes: Perform peak search on each column of the data matrix to obtain the minimum value of each column and its coordinate index value; Use a sorting function to sort the minimum values to obtain the smallest value as the peak; Save the coordinate positions corresponding to the peak in a row vector, and use the min function to obtain the minimum value of the row vector and the coordinate index value of the minimum value.

4. The signal data alignment method according to claim 1, wherein Before aiming to minimize the value of the target optimization function and obtaining the target delay dropout number within the search range of the delay dropout number, the method further includes: Construct the target optimization function based on the minimum value and the coordinate index value of the minimum value.

5. The signal data alignment method according to claim 4, wherein The step of constructing the target optimization function based on the minimum value and the coordinate index value of the minimum value includes: Based on the minimum value and the coordinate index value of the minimum value, align the non-target column data to the target column signal data to obtain the number of points to be discarded at the target end of the non-target column data; Obtain the aligned data according to the data before alignment and the number of points to be discarded; Under the least mean square error criterion, construct the target optimization function according to the data before alignment, the aligned data, the number of sampling points, and the delay dropout number.

6. The signal data alignment method according to claim 5, wherein Before aiming to minimize the value of the target optimization function and obtaining the target delay dropout number within the search range of the delay dropout number, the method further includes: Determine the search threshold; Determine the left boundary of the search range according to the difference between the number of points to be discarded and the search threshold; Determine the right boundary of the search range according to the sum of the number of points to be discarded and the search threshold; Determine the search range according to the left boundary and the right boundary.

7. The signal data alignment method according to claim 1, wherein Before obtaining the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the acquired periodic signal, the method further includes: Obtaining the number of sampling points according to the sampling rate and the fundamental frequency of the periodic signal.

8. A signal data alignment device, characterized in that, Including: An obtaining module configured to obtain the number of periods included in the signal to be processed according to the number of sampling points of the narrow pulse signal within a single period of the acquired periodic signal; A processing module configured to process the signal to be processed according to the number of periods, the number of sampling points, and the number of acquisitions of the periodic signal to obtain a data matrix; A searching module configured to perform peak searching on the data matrix to obtain a minimum value and the coordinate index value of the minimum value; A target module configured to obtain a target delay loss number within a search range of the delay loss number for the purpose of minimizing the value of a target optimization function; wherein the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value; An alignment module configured to align the signal to be processed according to the target delay loss number.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is loaded and executed by a processor, it implements the signal data alignment method according to any one of claims 1-7.

10. An electronic device, characterized in that, Including a processor and a memory, wherein, The memory is configured to store a computer program; The processor is configured to load and execute the computer program so that the electronic device executes the signal data alignment method according to any one of claims 1-7.

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