Signal data alignment method and device, medium and equipment

Abstract

The embodiment of the invention discloses a signal data alignment method and device, a medium and equipment, and relates to the technical field of communication. The method comprises the following steps: firstly, acquiring periodic signals, analyzing waveform data in a single period, converting the signal data into a data matrix, processing, and carrying out peak value search to obtain a minimum value of multiple time domain waveform data in the single period and a coordinate index value corresponding to the minimum value, and considering that the sampling resolution is insufficient and the number of time domain signal points acquired each time is limited; the searched position may not be a real peak position, so that the optimal value is solved by constructing a target optimization function with the position reference corresponding to the minimum value to obtain the accurate shift point number, and finally the alignment operation is performed based on the shift point number without strictly requiring a high-precision trigger position. And the effect of aligning the signal data is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a signal data alignment method, device, medium and equipment. Background Art

[0002] In actual broadband acquisition systems, the irrational characteristics of RF circuits make it difficult for signals to achieve full-bandwidth amplitude-frequency response flatness and linear phase-frequency response conditions, making it impossible to obtain accurately reconstructed input signals. Therefore, corresponding full-passband amplitude-frequency response and phase-frequency response compensation calibration is required.

[0003] In order to reduce the impact of noise on the estimation of system frequency response characteristics, the most commonly used method is to use multi-frame averaging technology during data acquisition. Multi-frame averaging technology reduces the impact of noise by averaging multiple sampled waveforms without 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 the limited number of time domain signal points collected each time, the determined trigger position is not the exact position. The offset of the system trigger position reduces the effect of signal data alignment. Summary of the invention

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

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

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

[0007] According to the number of sampling points of the narrow pulse signal in a single cycle of the acquired periodic signal, the number of cycles contained in the signal to be processed is obtained;

[0008] According to the number of cycles, the number of sampling points and the number of acquisitions of the periodic signal, the signal to be processed is processed 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] The target delay point loss number is obtained within the delay point loss number search interval 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;

[0011] Align the signals to be processed according to the target delay loss point 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 acquisition times of the periodic signal to obtain a data matrix, including:

[0013] The signal to be processed is clipped to obtain a signal to be aligned whose length is an integer multiple of the period;

[0014] According to the number of cycles and the number of sampling points, the signal to be aligned is cut into equal parts to obtain the cut signal to be aligned;

[0015] The cut signals to be aligned are interpolated to obtain a data matrix; wherein the reorganized size of the data matrix is ​​the product of the number of sampling points multiplied by the number of acquisitions of the periodic signal and the number of periods.

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

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

[0018] Use the sorting function to sort the minimum values ​​and obtain the minimum value as the peak value;

[0019] The coordinate position corresponding to the peak value is saved in the 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 manner of the first aspect, with the purpose of minimizing the value of the target optimization function, before obtaining the target delay point loss number within the search interval of the delay point loss number, 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 manner of the first aspect, constructing a target optimization function based on the minimum value and the coordinate index value of the minimum value includes:

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

[0024] Obtain the data after alignment according to the data before alignment and the number of points to be discarded;

[0025] Under the minimum mean square error criterion, the target optimization function is constructed according to the data before and after alignment, the number of sampling points, and the number of delayed loss points.

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

[0027] Determine the search threshold;

[0028] Determine the left boundary of the search interval based on the difference between the number of points to be discarded and the search threshold;

[0029] Determine the right boundary of the search interval based on the sum of the number of points to be discarded and the search threshold;

[0030] Determine the search interval based on the left and right boundaries.

[0031] In a possible implementation 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 in a single period of the acquired periodic signal, the method further includes:

[0032] The number of sampling points is obtained according to the sampling rate and 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 acquisition module, which is used to obtain the number of periods contained in the signal to be processed according to the number of sampling points of the narrow pulse signal in a single period of the collected periodic signal;

[0035] The processing module is used to process the signal to be processed according to the number of cycles, the number of sampling points and the number of acquisition times of the periodic signal to obtain a data matrix;

[0036] Search module, the search module is used to search for peak values ​​in the data matrix to obtain the minimum value and the coordinate index value of the minimum value;

[0037] The target module is used to obtain a target delay point loss number within a delay point loss number search interval 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;

[0038] Alignment module,The alignment module is used to align the signals to be processed according to the target delay loss point number.

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

[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 a computer program so that the electronic device executes the signal data alignment method provided in any one of the first aspects above.

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

[0044] A signal data alignment method, device, medium and equipment proposed in the embodiments of the present application include: obtaining the number of periods contained in the signal to be processed according to the number of sampling points of the narrow pulse signal in 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 times the periodic signal is collected 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 a target delay loss point number within the search interval of the delay loss point 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; and aligning the signal to be processed according to the target delay loss point number. The present application first collects periodic signals, analyzes waveform data within a single cycle, converts the signal data into a data matrix for post-processing, performs peak search, and obtains the minimum value of multiple time-domain waveform data within a single cycle and its corresponding coordinate index value. Taking into account 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 precise number of shift points. Finally, alignment operations are performed based on the number of shift points. There is no need to strictly require a high-precision trigger position, which improves the effect of aligning the signal data. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of the structure of an electronic device of a hardware operating environment involved in an embodiment of the present application;

[0046] Figure 2 A schematic diagram of a flow chart of a signal data alignment method provided in an embodiment of the present application;

[0047] Figure 3 Schematic diagram of a single-cycle narrow pulse time domain signal before alignment;

[0048] Figure 4 A schematic diagram of a single-cycle narrow pulse time domain signal after rough alignment using the method of the present application;

[0049] Figure 5 This is a schematic diagram of the signal after fine-tuning the alignment with precise shift points using the method of the present application;

[0050] Figure 6It is a schematic diagram of the time domain signal of a non-aligned single-cycle narrow pulse based on the fast edge signal collected multiple times by the narrow pulse fast edge signal generator;

[0051] Figure 7 A schematic diagram of a time domain signal after alignment by the method of the present application based on fast edge signals collected multiple times by a narrow pulse fast edge signal generator;

[0052] Figure 8 A schematic diagram of a module of a signal data alignment device provided in an embodiment of the present application;

[0053] Markings in the figure: 101 - processor, 102 - communication bus, 103 - network interface, 104 - user interface, 105 - memory. DETAILED DESCRIPTION

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

[0055] See attached Figure 1 , attached Figure 1 This is a schematic diagram of the structure of an electronic device of the hardware operating environment involved in the embodiment of the present 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), an input unit such as a keyboard (Keyboard), and the user interface 104 may also 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 (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 (RAM) memory, or it may be a stable non-volatile memory (NVM), such as at least one disk storage; the processor 101 may be a general-purpose processor, including a central processing unit, a network processor, etc., or it may be a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component.

[0056] Those skilled in the art will appreciate that Figure 1 The structure shown in the figure does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0057] As attached Figure 1 As shown, 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 In the electronic device shown, 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 the present application can be set 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 in the embodiment of the present application.

[0059] In actual broadband acquisition systems, the irrational characteristics of RF circuits make it difficult for signals to achieve full-bandwidth amplitude-frequency response flatness and linear phase-frequency response conditions, making it impossible to obtain accurately reconstructed input signals. Therefore, corresponding full-passband amplitude-frequency response and phase-frequency response compensation calibration is required.

[0060] In actual engineering applications, a set of multi-frequency sinusoidal signals are generally used to estimate the amplitude-frequency response of the system, and a fast-edge pulse signal with large bandwidth and rich frequency components is 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 phase-frequency response characteristics of the system, the slight phase changes between frequency points caused by noise will cause the obtained system group delay to have large fluctuations, thus posing new challenges to the design of the phase-frequency compensation IIR filter.

[0061] In order to reduce the impact of noise on the estimation of system frequency response characteristics, the most commonly used method is to use multi-frame averaging technology during data acquisition. Multi-frame averaging technology reduces the impact of noise by averaging multiple sampled waveforms without 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 the limited number of time domain signal points collected each time, the determined trigger position is not the exact position. The offset of the system trigger position reduces the effect of signal data alignment.

[0062] To solve the above problems, refer to the attached Figure 2 Based on the hardware device of the foregoing embodiment, an embodiment of the present application provides a signal data alignment method, comprising the following steps:

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

[0064] In the specific implementation process, the periodic narrow pulse signal is collected multiple times, and the sampling rate is f s In the case of multiple acquisitions, the fundamental frequency is f c The fast edge signal is obtained by RSys , the size is 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 one cycle of the signal needs to be analyzed. The number of sampling points of the narrow pulse signal in a single cycle is N period The calculation formula is:

[0065]

[0066] That is, before obtaining the number of cycles contained in the signal to be processed according to the number of sampling points of the narrow pulse signal in a single cycle of the collected periodic signal, the method further includes:

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

[0068] Then the number of cycles K contained in the time domain signal of length N is:

[0069]

[0070] Wherein, floor(·) indicates the rounding down operation.

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

[0072] In the specific implementation process, in order to find the minimum value of multiple time domain waveform data in a single cycle and its corresponding coordinate index value, the signal to be processed is processed and reorganized for subsequent processing. Specifically, according to the number of cycles, the number of sampling points and the number of acquisitions of periodic signals, the signal to be processed is processed to obtain a data matrix, including:

[0073] The signal to be processed is clipped to obtain a signal to be aligned whose length is an integer multiple of the period;

[0074] According to the number of cycles and the number of sampling points, the signal to be aligned is cut into equal parts to obtain the cut signal to be aligned;

[0075] The cut signals to be aligned are interpolated to obtain a data matrix; wherein the reorganized size of the data matrix is ​​the product of the number of sampling points multiplied by the number of acquisitions of the periodic signal and the number of periods.

[0076] In the specific implementation process, the number of sample points contained in K cycles is calculated, that is, K*N period , and then cut off (NK*Nperiod) points at the end of each acquisition signal to obtain a signal X with a length of an integer multiple of the period IntPeriod . The signal to be aligned X IntPeriod Cut the column into K equal parts, each with a length of N period Then, each column of data is interpolated and the reorganized size is N. period ×L data matrix X', where L = M*K, that is, the product of the number of acquisitions and the number of cycles.

[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, a peak search is performed on each column of the data matrix to find its minimum value and its coordinate index value. Specifically, a peak search is performed on the data matrix to obtain the minimum value and the coordinate index value of the minimum value, including:

[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 ​​and obtain the minimum value as the peak value;

[0081] The coordinate position corresponding to the peak value is saved in the 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.

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

[0083] S40: with the purpose of minimizing the value of the target optimization function, obtaining a target delay point loss number within the search interval of the delay point loss number; wherein the target 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 position found in the above steps may not be the true waveform peak position, and the true peak position is near the searched peak coordinate index value j. In order to obtain an accurate number of shift points, a more refined peak search is performed, and the number of shift points is fine-tuned. By constructing a target optimization function, a one-dimensional search method is used to solve the optimal value, that is, with the purpose of minimizing the value of the target optimization function, before obtaining the target delay loss point number within the search interval of the delay loss point number, the method also includes:

[0085] Based on the minimum value and the coordinate index value of the minimum value, a target optimization function is constructed. Specifically: Based on the minimum value and the coordinate index value of the minimum value, a target optimization function is constructed, including:

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

[0087] Obtain the data after alignment according to the data before alignment and the number of points to be discarded;

[0088] Under the minimum mean square error criterion, the target optimization function is constructed according to the data before and after alignment, the number of sampling points, and the number of delayed loss points.

[0089] In the specific implementation process, the j column data is used as the reference signal That is, the target column signal data, other column data, that is, non-target column data is aligned to it, and the left end of other column data, that is, the target end, needs to lose points for:

[0090]

[0091] Suppose the data before alignment of column i is 0≤n <N period , the data after alignment in column i is Align each column of data to meet the following requirements:

[0092]

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

[0094]

[0095] in, To delay the number of lost points, find the minimum target optimization function in the search interval. The search interval is determined by the search threshold and the number of points that need to be lost on the target end. That is, with the purpose of minimizing the value of the target optimization function, before obtaining the target delay loss number within the search interval of the delay loss number, the method further includes:

[0096] Determine the search threshold;

[0097] Determine the left boundary of the search interval based on the difference between the number of points to be discarded and the search threshold;

[0098] Determine the right boundary of the search interval based on the sum of the number of points to be discarded and the search threshold;

[0099] Determine the search interval based on the left and right boundaries.

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

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

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

[0103]

[0104] like It satisfies:

[0105]

[0106] In this embodiment, firstly, by collecting periodic signals, analyzing the waveform data in a single cycle, converting the signal data into a data matrix for post-processing, and performing peak search to obtain the minimum value of multiple time-domain waveform data in a single cycle and its corresponding coordinate index value. Taking into account 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 precise number of shift points. Finally, the alignment operation is performed based on the number of shift points. There is no need to strictly require a high-precision trigger position, which improves the effect of aligning the signal data.

[0107] The following is a further explanation of this application in combination with actual engineering tests:

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

[0109] Test result analysis: as attached Figure 3 With attached Figure 4 As shown in the comparison, Figure 3 The figure shows the single-cycle narrow pulse time domain signal before alignment. Figure 4 The single-cycle narrow pulse time domain signal after alignment is shown. It can be seen from the attached figure that after the rough alignment method of the time domain waveform of the present application is used to align the time domain waveform, the time offset of a column signal relative to the reference signal is larger. This is because the sample value corresponding to the index position 600 of a column signal is not the true peak value. Its true peak value is near the index position 600. Therefore, the present application performs further refined peak search to obtain the number of sample points that need to be discarded for each column data relative to the reference signal. As shown in the attached figure Figure 5 As shown, the signal is aligned after the method of the present application is adjusted by the precise shift point number. It can be seen from the figure that after alignment, the fluctuation of each column of data relative to the reference signal is almost zero.

[0110] As attached Figure 6 With attached Figure 7 As shown in the comparison, both are based on the fast edge signal generator of narrow pulses to collect fast edge signals multiple times. Figure 6 It is a time domain signal of a single-cycle narrow pulse that is not aligned. Its signal fluctuation range is about 5 sampling points. Figure 7 For the time domain signal after the time domain waveform is aligned using the method of the present application, the signal fluctuation drops to about 1 sampling point. This fluctuation is mostly caused by noise. The noise can be weakened after averaging the signal, so that the phase-frequency characteristics of the system can be accurately extracted. As shown in the above implementation method, the method proposed in the present application only needs to ensure that the rising edge of the signal is within the acquisition window, without the need for strict digital triggering and additional hardware circuit implementation. A rough and fine-tuning alignment method is used to effectively avoid the problem of inaccurate peak positioning due to insufficient sampling resolution and a limited number of time domain signal points acquired each time, thereby achieving more accurate data alignment.

[0111] See attached Figure 8 Based on the same inventive concept as in the above-mentioned embodiment, the embodiment of the present application further provides a signal data alignment device, comprising:

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

[0113] The processing module is used to process the signal to be processed according to the number of cycles, the number of sampling points and the number of acquisition times of the periodic signal to obtain a data matrix;

[0114] Search module, the search module is used to search for peak values ​​in the data matrix to obtain the minimum value and the coordinate index value of the minimum value;

[0115] The target module is used to obtain a target delay point loss number within a delay point loss number search interval 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;

[0116] Alignment module,The alignment module is used to align the signals to be processed according to the target delay loss point number.

[0117] Those skilled in the art should understand that the division of the various modules in the embodiment is merely a division of logical functions, and in actual application, all or part of them can be integrated into one or more actual carriers, and these modules can be implemented entirely in the form of software called by a processing unit, or entirely in the form of hardware, or 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-to-one to each step in the signal data alignment method in the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned signal data alignment method, which will not be repeated here.

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

[0119] Based on the same inventive concept as in the above-mentioned 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 computer programs;

[0121] The processor is used to load and execute a computer program so that the electronic device executes the signal data alignment method provided in 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 disk, or CD-ROM; or various devices including one or any combination of the above 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, the present application provides a signal data alignment method, device, medium and equipment, the method comprising: obtaining the number of periods contained in the signal to be processed according to the number of sampling points of the narrow pulse signal in 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 times the periodic signal is collected 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 a target delay loss point number within the search interval of the delay loss point number with 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; and aligning the signal to be processed according to the target delay loss point number. The present application first collects periodic signals, analyzes waveform data within a single cycle, converts the signal data into a data matrix for post-processing, performs peak search, and obtains the minimum value of multiple time-domain waveform data within a single cycle and its corresponding coordinate index value. Taking into account 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 precise number of shift points. Finally, alignment operations are performed based on the number of shift points. There is no need to strictly require a high-precision trigger position, which improves the effect of aligning the signal data.

[0130] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A signal data alignment method, characterized in that: The following steps are involved: According to the number of sampling points of the narrow pulse signal in a single cycle of the acquired periodic signal, the number of cycles contained in the signal to be processed is obtained; Processing the signal to be processed according to the number of periods, the number of sampling points and the number of acquisition times of the periodic signal to obtain a data matrix; Performing a peak search on the data matrix to obtain a minimum value and a coordinate index value of the minimum value; With the purpose of minimizing the value of the target optimization function, a target delay point loss number is obtained within the search interval of the delay point loss number; wherein the target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value; The signal to be processed is aligned according to the target delay loss point number.

2. The signal data alignment method according to claim 1, characterized in that: The step of processing the signal to be processed according to the number of cycles, the number of sampling points and the number of acquisition times of the periodic signal to obtain a data matrix includes: The signal to be processed is clipped to obtain a signal to be aligned whose length is an integer multiple of the period; According to the number of cycles and the number of sampling points, the signal to be aligned is divided into equal parts to obtain divided signals to be aligned; Interpolation processing is performed on the cut signals to be aligned to obtain a data matrix; wherein the reorganized size of the data matrix is ​​the product of the number of sampling points multiplied by the number of acquisitions of the periodic signal and the number of periods.

3. The signal data alignment method according to claim 1, characterized in that: The step of performing a peak search on the data matrix to obtain a minimum value and a 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; The minimum values ​​are sorted by using a sorting function to obtain the minimum value as a peak value; The coordinate position corresponding to the peak value is saved in a row vector, and the minimum value of the row vector and the coordinate index value of the minimum value are obtained using a min function.

4. The signal data alignment method according to claim 1, characterized in that: The method further comprises: before obtaining a target delay point loss number within a delay point loss number search interval with the purpose of minimizing the value of the target optimization function; The target optimization function is constructed based on the minimum value and the coordinate index value of the minimum value.

5. The signal data alignment method according to claim 4, characterized in that: The 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 that need to be dropped for the non-target column data at the target end; Obtaining the aligned data according to the data before alignment and the number of points to be discarded; Under the minimum mean square error criterion, the target optimization function is constructed according to the pre-alignment data, the post-alignment data, the number of sampling points and the number of delayed lost points.

6. The signal data alignment method according to claim 5, characterized in that: The method further comprises: before obtaining a target delay point loss number within a delay point loss number search interval with the purpose of minimizing the value of the target optimization function; Determine the search threshold; Determining the left boundary of the search interval according to the difference between the number of points to be discarded and the search threshold; Determining the right boundary of the search interval according to the sum of the number of points to be discarded and the search threshold; The search interval is determined according to the left boundary and the right boundary.

7. The signal data alignment method according to claim 1, characterized in that: 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 in a single period of the collected periodic signal, the method further includes: The number of sampling points is obtained according to the sampling rate and fundamental frequency of the periodic signal.

8. A signal data alignment device, characterized in that: include: An acquisition module, the acquisition module is used to obtain the number of periods contained in the signal to be processed according to the number of sampling points of the narrow pulse signal in a single period of the collected periodic signal; A processing module, the processing module is used to process the signal to be processed according to the number of cycles, the number of sampling points and the number of times the periodic signal is collected to obtain a data matrix; A search module, the search module is used to perform peak search on the data matrix to obtain a minimum value and a coordinate index value of the minimum value; A target module, the target module is used to obtain a target delay point loss number within a delay point loss number search interval 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 is used to align the to-be-processed signal according to the target delay loss point 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, the signal data alignment method according to any one of claims 1 to 7 is implemented.

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

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