Signal processing method, apparatus, device, storage medium, and product

Abstract

The application discloses a signal processing method, device, equipment, storage medium and product, and belongs to the technical field of signal processing. The method comprises the following steps: acquiring a to-be-analyzed signal, the to-be-analyzed signal comprising a plurality of signal periods; identifying original intersection points of each signal period in the to-be-analyzed signal; performing phase binning statistics on the original intersection points based on the period phase of each original intersection point mapped in the same signal period, obtaining intersection point statistical values of each phase bin in the same signal period, and the intersection point statistical values being used for indicating the frequency of mapping of the original intersection points of the to-be-analyzed signal to the phase bin; performing weighted statistics on the binning phase values of each phase bin by taking the intersection point statistical values as weights, and obtaining phase statistical data; and determining a target intersection point phase of the to-be-analyzed signal based on the phase statistical data, the target intersection point phase being used for indicating the statistical position of each original intersection point in the same signal period. The application can improve the accuracy of intersection point estimation.

Description

Technical Field

[0001] This application relates to the field of signal processing technology, and in particular to a signal processing method, apparatus, device, storage medium and product. Background Technology

[0002] Eye diagram crossover point localization is a key technology for analyzing and correcting high-speed digital signals. It can be used to quantify signal symmetry, evaluate timing jitter, diagnose duty cycle distortion, and restore signal clock. Existing eye diagram crossover point phase estimation techniques typically employ a hard-decision histogram statistical method. This method folds the interpolated and refined eye diagram crossover phase and directly assigns it to the corresponding bin. Then, the crossover point phase is determined by peak search to locate the main lobe. However, this approach cannot adapt to the phase ring characteristics of the signal, is prone to statistical discontinuities, and is susceptible to misjudging the main lobe, resulting in poor crossover point localization accuracy. Summary of the Invention

[0003] This application provides a signal processing method, apparatus, device, storage medium, and product, the specific technical solutions of which are as follows.

[0004] According to one aspect of the embodiments of this application, a signal processing method is provided, the method comprising: Acquire the signal to be analyzed, wherein the signal to be analyzed includes multiple signal periods; Identify the original crossover points of each signal period in the signal to be analyzed; Based on the periodic phase mapped by each of the original cross points within the same signal period, phase bin statistics are performed on each of the original cross points to obtain the cross point statistics value of each phase bin in the same signal period. The cross point statistics value is used to indicate the frequency with which the original cross points of the signal to be analyzed are mapped to the phase bins. Using the intersection statistics as weights, the phase values ​​of each phase bin are weighted and statistically analyzed to obtain phase statistics data. The target crossover phase of the signal to be analyzed is determined based on the phase statistics data. The target crossover phase is used to indicate the statistical position of each of the original crossover points in the same signal period.

[0005] According to another aspect of the embodiments of this application, a signal processing apparatus is provided, the apparatus comprising: The acquisition module is used to acquire the signal to be analyzed, which includes multiple signal periods; The identification module is used to identify the original crossover points of each signal period in the signal to be analyzed; The binning statistics module is used to perform phase binning statistics on each of the original cross points based on the periodic phase mapped by each of the original cross points in the same signal period, and to obtain the cross point statistics value of each phase bin in the same signal period. The cross point statistics value is used to indicate the frequency with which the original cross points of the signal to be analyzed are mapped to the phase bins. The weighted statistics module is used to perform weighted statistics on the phase values ​​of each phase bin, using the intersection statistics value as the weight, to obtain phase statistics data; The determination module is used to determine the target intersection phase of the signal to be analyzed based on the phase statistics data, wherein the target intersection phase is used to indicate the statistical position of each of the original intersections in the same signal period.

[0006] In an exemplary embodiment, the signal to be analyzed includes multiple signal sampling points, and the identification module includes: The threshold acquisition submodule is used to acquire the detection threshold of the signal to be analyzed, and the detection threshold is used to indicate the theoretical crossover point amplitude of the signal period; The identification submodule is used to traverse the sampling amplitude of the multiple signal sampling points and identify adjacent signal sampling point pairs whose previous sampling amplitude and current sampling amplitude are located on both sides of the detection threshold. The estimation submodule is used to estimate the intersection point position based on the corresponding previous sampling amplitude and current sampling amplitude of each pair of adjacent signal sampling points, so as to obtain the original intersection point of each signal period.

[0007] In an exemplary implementation, the estimation submodule is specifically used for: If either the preceding sampling amplitude or the current sampling amplitude is infinite, the midpoint between the positions of the two signal sampling points in the adjacent signal sampling point pair is determined as the original intersection point.

[0008] In an exemplary embodiment, the estimation submodule is further specifically used for: If the previous sample amplitude and the current sample amplitude are not infinite, interpolation is performed on the previous sample amplitude and the current sample amplitude to obtain the amplitude interpolation result; The position point corresponding to the detection threshold in the amplitude interpolation result is determined as the original intersection point.

[0009] In an exemplary embodiment, the bin sorting and statistics module includes: The modulus submodule is used to perform modulus operations on the point positions of each of the original intersection points based on the signal period of the signal to be analyzed, so as to obtain the periodic phase mapped by each of the original intersection points within the same signal period; The index mapping submodule is used to map the periodic phase to a target bin index value for each original intersection point based on the number of bins in the signal period, wherein the integer part of the target bin index value indicates the first phase bin mapped to the current original intersection point. The counting and allocation submodule is used to count the intersection points corresponding to each original intersection point based on the target bin index value and allocate them to the corresponding first phase bin and the second phase bin adjacent to the first phase bin. The accumulation submodule is used to accumulate the count values ​​assigned to each phase sub-bin to obtain the intersection statistics of each phase sub-bin.

[0010] In an exemplary implementation, the counting allocation submodule is specifically used for: For each of the original intersection points, determine the decimal value of the target bin index and the normalized complement of the decimal value; The decimal value of the target bin index is assigned to the second phase bin corresponding to the current original crossover point, and the normalized complement is assigned to the first phase bin corresponding to the current original crossover point.

[0011] In an exemplary embodiment, the device further includes a binning module for: Based on the signal period and sampling time interval of the signal to be analyzed, the number of bins for the signal period is adaptively determined. The sampling time interval is used to indicate the time interval between adjacent signal sampling point pairs, and the number of bins is within a preset bin range.

[0012] In an exemplary embodiment, the statistical values ​​of each phase bin corresponding to the signal period and the intersection points of the phase bins form a ring-shaped phase histogram, and the weighted statistical module includes: The shift traversal submodule is used to perform a full-offset cyclic shift traversal of the annular phase histogram with the phase width of the phase bin as the shift step size and the number of bins as the shift number, so as to obtain the shift phase histogram corresponding to each shift offset. The weighted statistics submodule is used to perform weighted statistics on the bin phase values ​​of each phase bin of the shift phase histogram for each shift phase histogram, using the cross-point statistical value as the weight, so as to obtain the corresponding phase statistics data for each shift phase histogram.

[0013] In an exemplary implementation, the weighted statistics submodule is specifically used for: For each shifted phase histogram, the weighted phase mean and weighted phase standard deviation of the phase bin values ​​are calculated using the crossover point statistics as weights. The weighted phase mean and the weighted phase standard deviation are determined as the phase statistics of the shifted phase histogram.

[0014] In an exemplary embodiment, the phase statistics include the weighted phase mean and the weighted phase standard deviation, and the determining module is specifically used for: Among all the shift phase histograms, the shift phase histogram with the smallest weighted phase standard deviation is determined as the target histogram; The weighted average phase value corresponding to the target histogram is normalized to obtain the target intersection phase.

[0015] According to another aspect of the embodiments of this application, a computing device is provided, the computing device including a processor and a memory for storing at least one computer program, the at least one computer program being loaded and executed by the processor to implement the signal processing method provided as described in the first aspect or any possible implementation of the first aspect.

[0016] According to another aspect of the embodiments of this application, a computer-readable storage medium is provided, which stores at least one computer program, which is loaded and executed by a processor to implement the signal processing method provided as described in the first aspect or any possible implementation thereof.

[0017] According to another aspect of the embodiments of this application, a computer program product is provided, characterized in that the computer program product includes at least one computer program, which is loaded and executed by a processor to implement the signal processing method provided as described in the first aspect or any possible implementation thereof.

[0018] The signal processing solution of this application has at least the following technical effects: The technical solution of this application first identifies the original crossover points of each signal period in the signal to be analyzed. Based on the periodic phase mapped by each original crossover point within the same signal period, phase binning statistics are performed on each original crossover point to obtain the crossover point statistical value of each phase bin in the same signal period. This indicates the frequency of the original crossover point mapping to the phase bin and adapts to the phase ring characteristics of the signal being analyzed, avoiding signal boundary discontinuity problems. Furthermore, using the crossover point statistical value as a weight, the binning phase values ​​of each phase bin are weighted and statistically analyzed to obtain phase statistical data, thereby determining the phase of the target crossover point. Compared with the peak search scheme, the weighted statistical method of this application can improve the accuracy of main lobe localization, thereby improving the accuracy and localization precision of crossover point estimation.

[0019] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this application. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the hardware implementation environment of a signal processing method provided in an embodiment of this application; Figure 2 This is a flowchart of a signal processing method provided in an embodiment of this application; Figure 3 This is a flowchart of another signal processing method provided in an embodiment of this application; Figure 4 This is a flowchart of another signal processing method provided in an embodiment of this application; Figure 5 This is a flowchart of another signal processing method provided in an embodiment of this application; Figure 6 This is a flowchart of another signal processing method provided in an embodiment of this application; Figure 7 This is a structural block diagram of a signal processing device provided in an embodiment of this application; Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of this application; Figure 9 This is a structural block diagram of another electronic device provided in the embodiments of this application. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0023] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or at least two processors or memory) can be used to implement one or at least two modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0024] Various exemplary embodiments, features, and aspects of this application will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0025] The term “exemplary” as used herein means “serving as an example, embodiment”. Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0026] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more of a plurality of elements. For example, including at least one of A, B, and C can mean including any one or at least two elements selected from the set consisting of A, B, and C. Additionally, "multiple" means two or more.

[0027] Furthermore, to better illustrate this application, numerous specific details are provided in the following detailed description. Those skilled in the art should understand that this application can be implemented without certain specific details. In some instances, methods, means, components, and circuits well-known to those skilled in the art have not been described in detail in order to highlight the main points of this application.

[0028] It should be noted that the information (including but not limited to signals to be analyzed), data (including but not limited to data used for analysis, stored data, and displayed data), and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the information involved in this application was obtained under full authorization. In some embodiments, this application provides a permission inquiry page, which is used to inquire whether to grant permission to obtain the above information or data. The permission inquiry page displays an authorization consent control and an authorization denial control. When a trigger operation of the authorization consent control is detected, the signal processing method provided in this application is used to obtain the above information.

[0029] The following explains the relevant terms used in the embodiments of this application.

[0030] An eye diagram is a graphical representation of a series of digital signals accumulated on an oscilloscope. It contains a wealth of information, allowing observation of intersymbol interference (ISI) and noise effects, reflecting the overall characteristics of the digital signal, and thus estimating the system's performance. Therefore, eye diagram analysis is central to signal integrity analysis in high-speed interconnect systems. The signal to be analyzed in this application is periodically folded to form the corresponding eye diagram.

[0031] Eye diagram crossover point: refers to the position where the rising edge and falling edge of a signal meet in the eye diagram, mainly reflecting the timing symmetry and duty cycle distortion of the signal. The original crossover point in this application corresponds to the actual crossover point of each cycle of the signal to be analyzed, and the target crossover point refers to the statistical average crossover point of each cycle of the signal in the eye diagram corresponding to the signal to be analyzed.

[0032] The hardware implementation environment of this application embodiment is described below.

[0033] The signal processing method provided in this application can be implemented in various computer system environments. The following description of a general hardware implementation environment is merely an example and does not constitute a limitation of this application.

[0034] Figure 1 This is a schematic diagram of the hardware implementation environment of a signal processing method provided in an embodiment of this application. For example... Figure 1As shown, the system of this hardware implementation environment may include a signal generating device 01 and a signal processing device 02. The signal generating device 01 and the signal processing device 02 can be integrated into the same device, such as the same terminal device, or they can be independently located in different devices, such as different terminals. Alternatively, the signal generating device 01 can be located in a terminal, and the signal processing device 02 in a server. The signal generating device 01 and the signal processing device 02 can communicate via wired or wireless communication networks to form a collaborative computing environment.

[0035] Specifically, the signal generating device 01 is used to generate the signal to be analyzed, and the signal processing device 02 is used to receive the signal to be analyzed and perform signal processing to determine the phase of the target intersection point.

[0036] It should be understood that the above-described hardware implementation environment is merely an example. Those skilled in the art can adjust or replace the number, deployment method, and computing task allocation method of the signal generating device 01 and the signal processing device 02 without departing from the essence of the technical solution of this application, and all such adjustments or replacements should fall within the protection scope of this application.

[0037] Understandably, the above-described hardware implementation environment is merely illustrative, and in actual applications, more or fewer tools and functional modules may be running, without being limited to the above example.

[0038] The implementation environment of the embodiments of this application has been described above. The signal processing method provided by the embodiments of this application is described below. Figure 2 This is a flowchart of a signal processing method provided in an embodiment of this application, such as... Figure 2 As shown, taking the method executed by the server as an example, it includes the following steps S201-S209.

[0039] S201: Acquire the signal to be analyzed, which includes multiple signal cycles.

[0040] Specifically, the signal to be analyzed is a periodic digital signal that can be used for eye diagram crossover analysis, such as NRZ (Non-Return-to-Zero), PAM (Pulse Amplitude Modulation), RZ (Return-to-Zero), and other periodic binary level-hopping signals.

[0041] In some implementations, the signal to be analyzed is a segment of the valid analysis interval in the original sampled signal data. The original sampled signal data and the corresponding valid analysis interval can be obtained, and the signal segment within the valid analysis interval of the original sampled signal data is determined as the signal to be analyzed. Understandably, the original sampled signal data can be one-dimensional signal data.

[0042] Specifically, the signal period of the signal to be analyzed refers to the shortest time required for the waveform of the signal to be analyzed to complete one complete repeating change, and each signal period includes multiple signal sampling points.

[0043] In some implementations, the symbol rate of the signal to be analyzed can be obtained. The symbol rate refers to the number of symbols transmitted per second, measured in Baud (baud rate), and the signal period = 1.0 / symbol rate. Understandably, the symbol rate of the signal to be analyzed is consistent with the symbol rate of the original sampled signal data.

[0044] In a possible implementation, the method may further include S301: adaptively determining the number of bins for the signal period based on the signal period and sampling time interval of the signal to be analyzed, wherein the sampling time interval is used to indicate the time interval between adjacent signal sampling point pairs, and the number of bins is within a preset bin range.

[0045] Specifically, within a preset binning range, the bin count is negatively correlated with the sampling time interval. A shorter sampling time interval results in more signal sampling points and a larger bin count, and vice versa. The preset binning range includes an upper and lower limit. If the calculated bin count exceeds the upper limit, the upper limit is used as the bin count; if the calculated bin count is lower than the lower limit, the lower limit is used as the bin count. In some implementations, the signal bin count = signal period / sampling time interval. The binning phase width of the phase binning = signal period / bin count.

[0046] In this embodiment, the number of bins is adaptively calculated by the sampling time interval and signal period, which helps to balance the accuracy of crosspoint estimation and the complexity of the algorithm. Furthermore, by using a preset bin range as a limit, the calculation accuracy is avoided from being too low or the computational resources are consumed too much, thus further ensuring the accuracy of crosspoint positioning and the computational efficiency.

[0047] It should be noted that, based on the signal period, the number of bins, and the phase width, an initial ring phase histogram corresponding to the signal to be analyzed can be constructed. Understandably, the initial ring phase histogram is a one-dimensional zero vector with the dimension being the number of bins; that is, the initial ring phase histogram includes a number of phase intervals, each corresponding to one phase bin.

[0048] S203: Identify the original crossover points of each signal period in the signal to be analyzed.

[0049] Specifically, the original crossover point refers to the moment when the signal to be analyzed crosses the threshold, such as the moment when the signal crosses the threshold on the rising edge or the moment when the signal crosses the threshold on the falling edge. In essence, it refers to the point in time when the signal crosses the threshold. Understandably, each signal cycle of the signal to be analyzed has at least one moment when it crosses the threshold, and correspondingly, at least one original crossover point.

[0050] In a possible implementation, the signal to be analyzed includes multiple signal sampling points, as referenced. Figure 3 S203 may include S401-S405: S2031: Obtain the detection threshold of the signal to be analyzed. The detection threshold is used to indicate the theoretical crossover amplitude of the signal period. S2032: Traverse the sampling amplitude of multiple signal sampling points and identify adjacent signal sampling point pairs whose previous sampling amplitude and current sampling amplitude are located on both sides of the detection threshold; S2033: Based on the identified previous sampling amplitude and current sampling amplitude of each pair of adjacent signal sampling points, the crossover point position is estimated to obtain the original crossover point of each signal period.

[0051] Specifically, the detection threshold is an amplitude threshold used to determine the original crossover point of the signal to be analyzed. In some embodiments, the detection threshold is the median of the signal amplitude (e.g., 50%).

[0052] Specifically, using the sampling time interval as the step size, all signal sampling points in the signal to be analyzed are traversed to obtain the point index and sampling amplitude of each signal sampling point. The point index is used to indicate the sampling sequence number of the signal sampling point, and the sampling amplitude is the amplitude value of the signal sampling point, such as voltage value, level value, etc.

[0053] In some implementations, the original indexes of the first and last sampling points of the signal to be analyzed are determined from the original sampled signal data. This determines the range of signal sampling points between the original indices of the first and last sampling points as the traversed sampling point data range. If the original indices in the original sampled signal data start from 0 (i.e., the original index of the first sampling point is 0), then during the traversal of the signal sampling points of the signal to be analyzed, the point index of the signal to be analyzed is set to the original index in the original sampled signal data + 1, thereby matching the signal length (number of sampling points) with the point index order.

[0054] Specifically, the traversal step size can be set to n (n is greater than or equal to 1), and the signal sampling points of the signal to be analyzed can be traversed based on the natural order of the signal sampling points. During the traversal, the original index of the previous signal sampling point in the original sampled signal data is set as the starting index. If the starting index + 1 exceeds the data length of the original sampled signal data (i.e., there is no current signal sampling point), it is set to invalid (NaN). If the starting index + 1 does not exceed the data length of the original sampled signal data (i.e., there is a current signal sampling point), the sampling amplitude of the previous signal sampling point is associated with the point index "starting index + 1" and stored. That is, while traversing the sampling amplitude of each signal sampling point, the point index of all valid signal sampling points is set to the original index + 1, thereby updating the "point index - sampling amplitude" pair of the signal to be analyzed and forming adjacent signal sampling point pairs of the previous signal sampling point / the current signal sampling point, so as to facilitate threshold detection. In this way, by combining the characteristic of MATLAB arrays starting with 1, the point index is matched with the signal length value, thereby initializing the sampling amplitude of the signal sampling points that traverse the signal to be analyzed, simplifying the boundary processing of the signal, and avoiding over-threshold detection errors caused by insufficient signal length.

[0055] Specifically, for each pair of adjacent signal sampling points, including the preceding signal sampling point and the current signal sampling point, it is determined whether the preceding sampling amplitude of the preceding signal sampling point and the current sampling amplitude of the current sampling point are located on both sides of the detection threshold. Located on both sides of the detection threshold means that one of the preceding sampling amplitude and the current sampling amplitude is greater than the detection threshold, while the other is less than the detection threshold. If it is determined that they are located on both sides of the detection threshold, then a threshold-crossing event has occurred between the preceding signal sampling point and the current signal sampling point, i.e., an original intersection point exists. If it is determined that the preceding sampling amplitude and the current sampling amplitude are located on the same side of the detection threshold, i.e., both are less than the detection threshold or both are greater than the detection threshold, then a threshold-crossing event has not occurred between the preceding signal sampling point and the current signal sampling point, and no original intersection point exists.

[0056] In one embodiment, determining whether the previous sampling amplitude of the preceding signal sampling point and the current sampling amplitude of the current sampling point are located on both sides of the detection threshold can specifically include: obtaining the difference between the previous sampling amplitude (prevVal) and the detection threshold (threshold) (prevVal - threshold), and the difference between the current sampling amplitude (currVal) and the detection threshold (currVal - threshold). If the two have opposite signs (or their product is less than 0), it is determined that they are located on both sides of the detection threshold, and then the position estimation of the original intersection point is performed.

[0057] Thus, by determining the detection threshold and traversing the amplitude of the sampling points, adjacent signal sampling point pairs that may have exceeded the threshold can be identified, thereby achieving the estimation of the original intersection point. This can extend the positioning of the actual intersection point to the sub-precision level of the sampling time interval, improve the positioning accuracy of the original intersection point, and benefit the accuracy of the phase of the subsequent target intersection point.

[0058] In some implementations, S2033 may specifically include S20331-S20333: S20331: If either the previous sampling amplitude or the current sampling amplitude is an infinite value, the midpoint between the positions of the two adjacent signal sampling points is determined as the original intersection point; S20332: If the amplitude of the previous sample and the amplitude of the current sample are not infinite, perform interpolation on the amplitude of the previous sample and the amplitude of the current sample to obtain the amplitude interpolation result; S20333: In the amplitude interpolation result, the position point corresponding to the detection threshold is determined as the original intersection point.

[0059] Understandably, either the preceding sample amplitude or the current sample amplitude may be infinite (infinitely large or infinitely small). Here, infinite means exceeding the amplitude detection limit, such as in ADC saturation (the signal amplitude exceeds the range of the analog-to-digital converter (ADC)). In scenarios where infinite values ​​exist, the midpoint between the preceding and current signal sampling points is determined at the threshold time, i.e., the original intersection point. If the amplitude value is on the vertical axis, then the midpoint is the midpoint on the horizontal axis.

[0060] Specifically, if neither the preceding sample amplitude nor the current sample amplitude is infinite (i.e., both are valid amplitude values), an interpolation algorithm is used to generate a simulated signal segment between the preceding and current signal sampling points to obtain the amplitude interpolation result. Then, the location point (e.g., a time point) in this simulated signal segment that crosses the detection threshold is determined as the original intersection point. The interpolation method here can employ existing difference algorithms, including but not limited to linear interpolation, cubic spline interpolation, or polynomial fitting.

[0061] In this embodiment, different cross-point estimation strategies are adapted for infinite quantity and effective amplitude scenarios, thereby avoiding invalid positioning and ensuring the accuracy of cross-point positioning, providing an accurate data foundation for subsequent weighted statistical calculations.

[0062] S205: Based on the periodic phase mapped by each original crossover point within the same signal period, perform phase bin statistics on each original crossover point to obtain the crossover point statistics of each phase bin within the same signal period.

[0063] Specifically, the original crossover points determined in S203 can be mapped to phases within the same signal period, thereby obtaining the periodic phase of each original crossover point. Understandably, the signal to be analyzed is a cyclic signal based on a signal period, so signal folding can be performed based on the signal period, thereby mapping the signal segments of each signal period to the same signal period, forming a signal eye diagram. Ideally, original crossover points of the same transition type (such as rising edge transitions or falling edge transitions) will be mapped to the same periodic phase. However, due to signal jitter and errors, each original crossover point will be mapped to different periodic phases within a phase interval. Therefore, eye diagram crossover point estimation needs to be performed based on the periodic phase of the original crossover points to obtain the target crossover point phase of this embodiment.

[0064] Specifically, the crossover statistics are used to indicate how frequently the original crossover points of the signal being analyzed are mapped to the phase bins, that is, to reflect the probability density of the original crossover points falling into the phase bins.

[0065] In a possible implementation, the cross-point statistics are obtained by performing soft-assignment binning mapping on the original cross-points through fractional weighted statistics, thus avoiding the accuracy loss caused by hard decision.

[0066] In some implementations, reference is made to Figure 4 S205 can specifically include S2051-S2054: S2051: Based on the signal period of the signal to be analyzed, perform modulo operation on the point positions of each original intersection point to obtain the periodic phase mapped by each original intersection point within the same signal period; S2052: For each original intersection, based on the number of bins in the signal period, map the periodic phase to the target bin index value; S2053: Based on the target bin index value, the cross point count corresponding to each original cross point is assigned to the corresponding first phase bin and the second phase bin adjacent to the first phase bin; S2054: Accumulate the count values ​​assigned to each phase sub-box to obtain the cross-point statistics of each phase sub-box.

[0067] Specifically, the position of each original intersection point is modulo-operated, that is, the position is divided by the signal period and the remainder is taken. This remainder is determined as the period phase of the original intersection point. This is to map and fold each original intersection point to a phase interval of the same signal period, where 0 ≤ <T sym T sym 0 and 0 are the boundary of the signal period, and the two are equivalent, that is =0 is equivalent to = T symThis ensures the histogram's circular properties and adapts to the phase periodicity.

[0068] In some implementations, before the modulo operation, the point position (horizontal coordinate position) of the original intersection is converted into absolute time. Then, the modulo operation is performed on the converted absolute time based on the signal period to obtain the periodic phase.

[0069] Specifically, the signal period includes bins (binCount) of phase bins, each phase bin having a unique bin index, such as bin index [0, binCount), and sorted by timing.

[0070] Specifically, mapping the periodic phase to the target bin index value means performing a bin index conversion calculation on the periodic phase to obtain a target bin index value of continuous index type. It can be understood that each phase bin is obtained by dividing the phase interval of the signal period into bins. Each phase bin is equivalent to a phase sub-interval. By performing a mapping operation on the periodic phase based on the phase width, the target bin index value mapped to the periodic phase can be obtained. The target bin index value can be a floating-point number.

[0071] In one embodiment, the target bin index value idx float = / Container phase width, Container phase width = T sym / binCount, then idx float = * binCount / T sym .

[0072] Specifically, the integer part of the target bin index value indicates the first phase bin mapped to the current original crossover point. Understandably, when the target bin index value is an integer, it indicates that the first phase bin is the only phase bin the current original crossover point may fall into, and the count value of the first phase bin is incremented by 1, meaning the entire crossover point count (1) of the current original crossover point is allocated to the first phase bin. If the target bin index value is a floating-point number, i.e., a real number with decimal places, it indicates that the current original crossover point may partially fall into the first phase bin, and the next phase bin adjacent to the first bin is determined as the second phase bin corresponding to the current original crossover point. Based on a fractional weighted statistical method, its crossover point count is soft-allocated to the first and second phase bins, thereby preserving subsampling precision.

[0073] In some implementations, S2053 may specifically include S20531-S20532: S20531: For each original intersection point, determine the decimal value of the target bin index and the normalized complement of the decimal value; S20532: Assign the decimal value of the target bin index to the second phase bin corresponding to the current original crossover point, and assign the normalized complement to the first phase bin corresponding to the current original crossover point.

[0074] Specifically, the normalized complement of the decimal value refers to 1 minus the decimal value. After calculating the normalized target bin index value corresponding to the periodic phase, its integer value and decimal value are separated. The integer value serves as the integer bin index (i.e., the bin index of the first phase bin), and the decimal value is the decimal weight. A fractional weighting method is used to statistically represent this phase in the aforementioned initialized circular phase histogram. That is, the current count value of the first phase bin is accumulated with a weight of 1 minus the decimal value, and the current count value of the second phase bin is accumulated with a decimal weight. In this way, the cross-point count is softly distributed to two adjacent phase bins through a fractional weighting statistical method, thereby preserving subsampling accuracy, avoiding the accuracy loss caused by hard decision, and effectively improving the accuracy and precision of cross-point statistical calculation.

[0075] Specifically, after assigning the crosspoint count of each original crosspoint to its corresponding phase bin, the crosspoint statistics of each phase bin are obtained. These statistics are the sum of the counts assigned to that phase bin. For example, if the target bin index values ​​for original crosspoints 1, 5, and 7 are 4.4, 4.8, and 4.2, respectively, then phase bin 4 is the first phase bin, and phase bin 5 is the second phase bin. The crosspoint count weights assigned to phase bin 4 for original crosspoints 1, 5, and 7 are 0.6, 0.2, and 0.8, respectively, and their crosspoint statistics are 1.6. The crosspoint count weights assigned to phase bin 5 are 0.4, 0.8, and 0.2, respectively, and their crosspoint statistics are 1.4.

[0076] It should be noted that if the first phase bin corresponding to the current original intersection point is the last phase bin, then the second phase bin is the first phase bin, in order to adapt to the periodic ring characteristics.

[0077] In this embodiment, the original cross points are mapped and folded to the same period based on the modulo operation to ensure the ring characteristics of the phase. The target bin index value of the floating point is used to represent the bin assignment of the original cross points. The soft allocator cross points are counted based on the fractional weighting method, thereby ensuring the subsampling accuracy of the bin statistics, improving the accuracy of the cross point statistics, and thus improving the accuracy of the eye diagram cross point position estimation.

[0078] S207: Using the cross-point statistical value as the weight, perform weighted statistics on the phase values ​​of each phase bin to obtain phase statistics data.

[0079] Specifically, the phase statistics can include the weighted phase mean and the weighted phase standard deviation. The weighted phase mean represents the weighted sum of the phase values ​​of each phase bin, which indicates the center of the main lobe of the annular phase histogram. The weighted phase standard deviation represents the degree of dispersion of the phase values ​​of each phase bin relative to the weighted phase mean.

[0080] In some implementations, a cyclic shift traversal is performed based on the number of phase bins and the phase width of the bins, so that each phase bin is used as the first phase bin in turn, thereby calculating the corresponding phase statistics and determining the target intersection phase.

[0081] As mentioned above, the statistical values ​​of each phase bin and the intersection of the phase bins corresponding to the signal period form a ring-shaped phase histogram. Accordingly, S207 may include S2071-S2072: S2071: Using the phase width of the phase bin as the shift step size and the number of bins as the shift number, perform a full offset cyclic shift traversal on the annular phase histogram to obtain the shift phase histogram corresponding to each shift offset. S2072: For each shift phase histogram, the phase values ​​of each phase bin of the shift phase histogram are weighted and statistically analyzed using the cross-point statistical value as the weight, to obtain the corresponding phase statistical data for each shift phase histogram.

[0082] Specifically, the annular phase histogram includes the statistics of each phase bin and the intersection points of each phase bin. Each phase bin in the histogram is rotated and shifted k bin phase widths to the left or right, where k = 0, 1, ..., binCount. 1) After the rotation offset, the phase zero point is essentially redefined, moving from the original starting phase bin bin0 to the phase bin k corresponding to the current shift offset k. Understandably, each shift yields an updated annular phase histogram, which serves as the shift phase histogram corresponding to the current offset.

[0083] Specifically, for each shifted phase histogram, the corresponding weighted phase mean and weighted phase standard deviation are calculated to serve as the phase statistics data corresponding to that shift.

[0084] Thus, by adapting the phase periodicity to the ring histogram, boundary faults are eliminated, and a full offset shift traversal is performed using the phase width of the phase bin as the unit, so that each phase bin is used as the phase zero point in turn to calculate the phase statistics after each offset. This eliminates the arbitrariness of the absolute phase, which is conducive to determining the histogram reference system with optimal distribution and improving the accuracy of eye diagram intersection location.

[0085] In some implementations, S2072 may specifically include: for each shift phase histogram, calculating the weighted phase mean and weighted phase standard deviation of the phase values ​​of each phase bin with the cross-point statistics as weights; and determining the weighted phase mean and weighted phase standard deviation as the phase statistics data of the shift phase histogram.

[0086] Specifically, the bin phase value The statistical phase used to indicate phase bin i can be specifically the center phase of phase bin i. The crossover point statistics are weighted coefficients calculated using weighted averages.

[0087] In one embodiment, the formula for calculating the weighted phase mean is as follows:

[0088] in, It is the weighted phase mean of the current offset k (shifted by k bin phase widths). The intersection statistics of phase bin i are given. Let i be the phase value of the phase bin.

[0089] In one embodiment, the weighted phase standard deviation The calculation formula is as follows:

[0090] S209: Determine the target intersection phase of the signal to be analyzed based on phase statistics.

[0091] Specifically, the target crossover phase is used to indicate the statistical position of each original crossover point in the same signal period, which can be the phase of the eye diagram crossover point of the signal eye diagram.

[0092] In this embodiment, the original crossover points of each signal period in the signal to be analyzed are first identified. Based on the periodic phase mapped by each original crossover point within the same signal period, phase binning statistics are performed on each original crossover point to obtain the crossover point statistical value of each phase bin in the same signal period. This indicates the frequency of the original crossover point mapping to the phase bin and adapts to the phase ring characteristics of the signal being analyzed, avoiding signal boundary discontinuity problems. Furthermore, the phase binning phase values ​​of each phase bin are weighted using the crossover point statistical value as a weight to obtain phase statistical data, thereby determining the phase of the target crossover point. Compared with the peak search scheme, the weighted statistical method of this application can improve the accuracy of main lobe localization, thereby improving the accuracy and localization precision of crossover point estimation.

[0093] In a possible implementation, the target intersection phase is determined based on the weighted phase mean and weighted phase standard deviation in the phase statistics data.

[0094] In some implementations, S209 may include S2091-S2092: S2091: Among all the shift phase histograms, the shift phase histogram with the smallest weighted phase standard deviation is determined as the target histogram; S2092: Normalize the weighted average phase value corresponding to the target histogram to obtain the target intersection phase.

[0095] Specifically, by iterating through the weighted phase standard deviations of all shift offsets k, the smallest weighted phase standard deviation is determined. The corresponding shifted phase histogram is then the target histogram. The phase center of this target histogram is the main lobe center with the most concentrated in-situ crossover points and the least jitter. The corresponding weighted phase mean is the main lobe center phase in the corresponding shift coordinate system. Further, this weighted phase mean is normalized, and the normalized value is determined as the target crossover point phase, which serves as the phase estimation result for the eye diagram crossover point.

[0096] In this embodiment, the center of the main lobe with the most concentrated phase distribution and the least jitter is located by using the minimum variance criterion, and thus it is used as the center of the eye diagram crossover point. This replaces the traditional peak search, effectively avoiding misjudgment of the main lobe caused by false spectral peaks and multi-peak distribution, avoiding inter-symbol interference, improving robustness in low signal-to-noise ratio and high jitter scenarios, and thus ensuring the accuracy of the eye diagram crossover point estimation results. In one embodiment, reference Figure 6 The signal processing method of this application may include: S1, acquire wavetable data to obtain the original sampled signal data; S2, calculate the initial parameters of the signal, including the effective analysis interval, sampling time interval, symbol rate and detection threshold, etc., to obtain the signal to be analyzed; S3, Initialize the point index and sampling amplitude of the traversed signal sampling points; S4, determine whether the current pair of adjacent signal sampling points crosses the detection threshold. If yes, execute S5; otherwise, execute S9. S5, interpolation is used to determine the threshold time to obtain the in-situ intersection point; S6, based on the signal period, maps the in-situ intersection point to a single signal period to obtain the periodic phase; S7, map the periodic phase to the target bin weight index, and determine its integer and decimal values; S8, Weighting: Determine the current first phase bin and second phase bin based on integer values, assign smaller values ​​to the second phase bin, and assign 1 to smaller values ​​to the first phase bin; S9 updates the signal sampling points before and after; S10, determine whether the sampling point traversal is complete. If not, execute S4; if yes, execute S11. S11, calculate the weighted phase mean and weighted phase standard deviation; S12, Select the weighted phase mean corresponding to the shift offset with the smallest weighted phase standard deviation; S13, normalize the weighted phase mean of step S12 to obtain the target intersection phase, and end the calculation.

[0097] In summary, the signal processing method of this application can be used for phase estimation of eye diagram intersections. It can solve the defects of existing technologies such as low phase statistical accuracy of intersections, poor robustness of main lobe localization, and inability to adapt to real-time requirements. It can achieve accurate and efficient phase estimation of eye diagram intersections in low signal-to-noise ratio and high jitter scenarios. The whole method is an open-loop design, which does not require iteration and loop parameters. The estimation can be completed in one traversal. The algorithm has low complexity, adapts to real-time analysis requirements, and can be directly applied to scenarios such as high-speed serial communication and signal integrity testing.

[0098] The signal processing method provided in this application is particularly suitable for eye diagram crossover phase estimation scenarios. Specifically, it can be applied to scenarios such as high-speed serial communication and signal integrity testing to accurately estimate the normalized eye diagram crossover phase within the signal period, such as the zero-crossing phase, from the original sampled signal. This provides support for the selection of the optimal sampling time and clockless data recovery, ensuring signal transmission stability and test accuracy.

[0099] It should be noted that the above descriptions of application scenarios are merely illustrative, and the application scenarios of this application are not limited thereto. In different product forms, the specific form of signal processing can be adjusted according to business needs, while the signal processing solution proposed in this application can ensure efficient, accurate, reliable, and low-overhead signal processing, thereby providing unified technical support for a variety of application scenarios.

[0100] Based on the signal processing method proposed in this application, its technical solution can be packaged or integrated into various product forms to provide users with signal processing services based on this application.

[0101] In some product forms, the signal processing device of this application can be deployed in terminal equipment, such as oscilloscopes, signal processors or signal generators, to provide users with efficient signal processing services.

[0102] In some product forms, the signal processing device of this application can also be deployed on a server. Such products can typically provide a client deployed on a terminal and implement signal processing services through communication between the backend and the terminal, making them suitable for various signal processing scenarios.

[0103] In some product configurations, the signal processing method of this application can be deployed in a distributed storage system to provide users with efficient distributed signal processing services. The signal processing system is deployed on nodes of the distributed system to achieve efficient service.

[0104] In some product forms, the signal processing method of this application can be encapsulated as a plugin, component, or service interface for third-party applications or systems to call. These product forms perform signal processing through standardized interfaces and return the corresponding signal processing results, facilitating the rapid reuse of the technical solution of this application in different applications.

[0105] In some product forms, the signal processing method of this application can be provided externally as a background service or platform capability, supporting invocation by multiple applications and business scenarios. These products typically provide signal processing capabilities through service invocation, facilitating elastic scaling based on invocation scale and business needs.

[0106] It should be noted that the above description of the product form corresponding to the embodiments of this application is merely exemplary, and the product form corresponding to the embodiments of this application is not limited thereto. The signal processing solution of this application can be flexibly packaged into an independent product, system module, plug-in component, or backend service, and can be deployed in a terminal-server collaborative architecture to adapt to product forms under different scales and different business needs.

[0107] This application also provides a signal processing device. Figure 7 This is a structural block diagram of a signal processing device 800 provided in an embodiment of this application. The device includes: Acquisition module 10 is used to acquire the signal to be analyzed, which includes multiple signal cycles; The identification module 20 is used to identify the original crossover points of each signal period in the signal to be analyzed; The binning statistics module 30 is used to perform phase binning statistics on each original crossover point based on the periodic phase mapped by each original crossover point within the same signal period, and to obtain the crossover point statistics value of each phase bin in the same signal period. The crossover point statistics value is used to indicate the frequency of the original crossover point of the signal to be analyzed being mapped to the phase bin. The weighted statistics module 40 is used to perform weighted statistics on the phase values ​​of each phase bin, using the intersection statistical value as the weight, to obtain phase statistics data. The determination module 50 is used to determine the target intersection phase of the signal to be analyzed based on phase statistics data. The target intersection phase is used to indicate the statistical position of each original intersection point in the same signal period.

[0108] In a possible implementation, the signal to be analyzed includes multiple signal sampling points, and the identification module 20 includes: The threshold acquisition submodule is used to acquire the detection threshold of the signal to be analyzed. The detection threshold is used to indicate the theoretical crossover point amplitude of the signal period. The identification submodule is used to traverse the sampling amplitude of multiple signal sampling points and identify adjacent signal sampling point pairs whose previous sampling amplitude and current sampling amplitude are located on both sides of the detection threshold. The estimation submodule is used to estimate the intersection position based on the previous sampling amplitude and the current sampling amplitude of each pair of adjacent signal sampling points, so as to obtain the original intersection point of each signal period.

[0109] In a possible implementation, the estimation submodule is specifically used for: If either the previous sampling amplitude or the current sampling amplitude is infinite, the midpoint between the positions of the two adjacent signal sampling points is determined as the original intersection point.

[0110] In a possible implementation, the estimation submodule is further specifically used for: If the amplitude of the previous sample and the amplitude of the current sample are not infinite, interpolation is performed on the amplitude of the previous sample and the amplitude of the current sample to obtain the amplitude interpolation result; The location point corresponding to the detection threshold in the amplitude interpolation result is determined as the original intersection point.

[0111] In a possible implementation, the bin sorting and statistics module 30 includes: The modulus submodule is used to perform modulus operations on the point positions of each original intersection point based on the signal period of the signal to be analyzed, so as to obtain the periodic phase mapped by each original intersection point within the same signal period; The index mapping submodule is used to map the periodic phase to a target bin index value for each original intersection point based on the number of bins in the signal period. The integer bits of the target bin index value indicate the first phase bin mapped to the current original intersection point. The counting and allocation submodule is used to count the intersection points corresponding to each original intersection point based on the target bin index value and allocate them to the corresponding first phase bin and the second phase bin adjacent to the first phase bin. The accumulation submodule is used to accumulate the count values ​​assigned to each phase sub-bin to obtain the cross-point statistics of each phase sub-bin.

[0112] In a possible implementation, the counting allocation submodule is specifically used for: For each original intersection, determine the decimal value of the target bin index and the normalized complement of the decimal value; The decimal value of the target bin index is assigned to the second phase bin corresponding to the current original crossover point, and the normalized complement is assigned to the first phase bin corresponding to the current original crossover point.

[0113] In a possible implementation, the device further includes a compartmentation module for: Based on the signal period and sampling time interval of the signal to be analyzed, the number of bins for the signal period is adaptively determined. The sampling time interval is used to indicate the time interval between adjacent signal sampling point pairs, and the number of bins is within a preset bin range.

[0114] In a possible implementation, the statistical values ​​of each phase bin and the intersection points of the phase bins corresponding to the signal period form a ring-shaped phase histogram. The weighted statistical module 40 includes: The shift traversal submodule is used to perform a full-offset cyclic shift traversal of the circular phase histogram with the phase width of the phase bin as the shift step size and the number of bins as the shift number, so as to obtain the shift phase histogram corresponding to each shift offset. The weighted statistics submodule is used to perform weighted statistics on the phase values ​​of each phase bin of the shift phase histogram, using the cross-point statistical value as the weight, to obtain the corresponding phase statistics data for each shift phase histogram.

[0115] In a possible implementation, the weighted statistics submodule is specifically used for: For each shift phase histogram, the weighted mean phase value and weighted standard deviation of the phase values ​​of each phase bin are calculated using the cross-point statistics as weights. The weighted phase mean and weighted phase standard deviation are used to determine the phase statistics of the shifted phase histogram.

[0116] In a possible implementation, the phase statistics include the weighted phase mean and the weighted phase standard deviation. The determination module 50 is specifically used for: The shift phase histogram with the smallest weighted phase standard deviation among all shift phase histograms is determined as the target histogram. The weighted average phase value corresponding to the target histogram is normalized to obtain the target intersection phase.

[0117] It should be noted that the signal processing device provided in the above embodiments is only illustrated by the division of the above functional modules when performing the corresponding steps. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the signal processing device and the signal processing method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0118] Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of this application, used to execute the above-described signal processing method. The electronic device may be a server. Specifically: Electronic device 900 includes a central processing unit (CPU) 901, a system memory 904 including random access memory (RAM) 902 and read-only memory (ROM) 903, and a system bus 905 connecting the system memory 904 and the CPU 901. Electronic device 900 also includes a basic input / output system (I / O system) 906 that facilitates the transfer of information between various devices within the computer, and a mass storage device 907 for storing the operating system 913, application programs 914, and other program modules 915.

[0119] The basic input / output system 906 includes a display 908 for displaying information and an input device 909 for user input, such as a mouse or keyboard. Both the display 908 and the input device 909 are connected to the central processing unit 901 via an input / output controller 910 connected to the system bus 905. The basic input / output system 906 may also include the input / output controller 910 for receiving and processing input from multiple other devices such as a keyboard, mouse, or electronic stylus. Similarly, the input / output controller 910 also provides output to a display screen, printer, or other types of output devices.

[0120] Mass storage device 907 is connected to central processing unit 901 via a mass storage controller (not shown) connected to system bus 905. Mass storage device 907 and its associated computer-readable media provide non-volatile storage for electronic device 900. That is, mass storage device 907 may include computer-readable media (not shown) such as hard disk or CD-ROM (CompactDisc Read-Only Memory) drive.

[0121] Without loss of generality, computer-readable media can include computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes RAM, ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash memory or other solid-state storage technologies, CD-ROM, DVD (Digital Video Disc) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that computer storage media are not limited to the above-mentioned types. The system memory 904 and mass storage device 907 described above can be collectively referred to as memory.

[0122] According to various embodiments of this application, the electronic device 900 can also be connected to a remote computer on a network, such as the Internet. That is, the electronic device 900 can be connected to the network 910 via a network interface unit 911 connected to the system bus 905, or the network interface unit 911 can be used to connect to other types of networks or remote computer systems (not shown).

[0123] In some embodiments, the electronic device may be a terminal. Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of this application, such as... Figure 9 As shown, electronic device 1000 can be: a laptop computer, desktop computer, high-performance terminal, privately deployed edge device, local gateway, etc. Electronic device 1000 may also be referred to as user equipment, portable terminal, laptop terminal, desktop terminal, or other names. Electronic device 1000, as an edge node, local proxy, or debugging or testing environment, can support proxy server functions.

[0124] Typically, electronic device 1000 includes a processor 1001 and a memory 1002.

[0125] Processor 1001 may include one or more processing cores, such as a quad-core processor or a 100-core processor. Processor 1001 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 1001 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 1001 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 1001 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0126] The memory 1002 may include one or more computer-readable storage media, which may be non-transitory. The memory 1002 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 1002 are used to store at least one computer program, which is executed by the processor 1001 to implement the terminal execution process in the tabular data display method provided in the method embodiments of this disclosure.

[0127] In some embodiments, the electronic device 10000 may optionally include: a peripheral device interface 1003 and at least one peripheral device. The processor 1001, memory 1002, and peripheral device interface 1003 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 1003 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of: a radio frequency circuit 1004, a display screen 1005, a camera assembly 1006, an audio circuit 1007, and a power supply 1008.

[0128] Peripheral device interface 1003 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 1001 and memory 1002. In some embodiments, processor 1001, memory 1002 and peripheral device interface 1003 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 1001, memory 1002 and peripheral device interface 1003 can be implemented on separate chips or circuit boards, which is not limited in this disclosure.

[0129] The radio frequency (RF) circuit 1004 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 1004 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 1004 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. In some embodiments, the RF circuit 1004 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 1004 can communicate with other terminals via at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: metropolitan area networks (MANs), various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks (WLANs), and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 1004 may also include circuitry related to NFC (Near Field Communication), which is not limited herein.

[0130] Display screen 1005 is used to display a user interface (UI). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 1005 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 1001 for processing. In this case, display screen 1005 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 1005, disposed on the front panel of electronic device 1000; in other embodiments, there may be at least two display screens, disposed on different surfaces of electronic device 1000 or in a folded design; in still other embodiments, display screen 1005 may be a flexible display screen, disposed on a curved or folded surface of electronic device 1000. Furthermore, display screen 1005 may be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. The display screen 1005 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0131] The camera assembly 1006 is used to acquire images or videos. In some embodiments, the camera assembly 1006 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 1006 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash is a combination of a warm-light flash and a cool-light flash, which can be used for light compensation at different color temperatures.

[0132] The audio circuit 1007 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 1001 for processing, or input to the radio frequency circuit 1004 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each located at a different part of the electronic device 1000. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 1001 or the radio frequency circuit 1004 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 1007 may also include a headphone jack.

[0133] The power supply 1008 is used to supply power to the various components in the electronic device 1000. The power supply 1008 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When the power supply 1008 includes a rechargeable battery, the rechargeable battery can support wired or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0134] In some embodiments, the electronic device 1000 further includes one or more sensors 1009. The one or more sensors 1009 include, but are not limited to: an acceleration sensor 1010, a gyroscope sensor 1011, a pressure sensor 1012, an optical sensor 1013, and a proximity sensor 1014.

[0135] Accelerometer 1010 can detect the magnitude of acceleration on the three coordinate axes of a coordinate system established by electronic device 1000. For example, accelerometer 1010 can be used to detect the components of gravitational acceleration on the three coordinate axes. Processor 1001 can control display screen 1005 to display the user page in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 1010. Accelerometer 1010 can also be used for collecting game or user motion data.

[0136] The gyroscope sensor 1011 can detect the orientation and rotation angle of the electronic device 1000. The gyroscope sensor 1011 can work in conjunction with the accelerometer sensor 1010 to acquire the user's 3D movements on the electronic device 1000. Based on the data acquired by the gyroscope sensor 1011, the processor 1001 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0137] The pressure sensor 1012 can be disposed on the side bezel of the electronic device 1000 and / or on the lower layer of the display screen 1005. When the pressure sensor 1012 is disposed on the side bezel of the electronic device 1000, it can detect the user's grip signal on the electronic device 1000, and the processor 1001 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 1012. When the pressure sensor 1012 is disposed on the lower layer of the display screen 1005, the processor 1001 can control the operable controls on the UI page based on the user's pressure operation on the display screen 1005. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0138] An optical sensor 1013 is used to collect ambient light intensity. In one embodiment, the processor 1001 can control the display brightness of the display screen 1005 based on the ambient light intensity collected by the optical sensor 1013. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1005 is increased; when the ambient light intensity is low, the display brightness of the display screen 1005 is decreased. In another embodiment, the processor 1001 can also dynamically adjust the shooting parameters of the camera assembly 1006 based on the ambient light intensity collected by the optical sensor 1013.

[0139] The proximity sensor 1014, also known as a distance sensor, is typically installed on the front panel of the electronic device 1000. The proximity sensor 1014 is used to detect the distance between the user and the front of the electronic device 1000. In one embodiment, when the proximity sensor 1014 detects that the distance between the user and the front of the electronic device 1000 is gradually decreasing, the processor 1001 controls the display screen 1005 to switch from a screen-on state to a screen-off state; when the proximity sensor 1014 detects that the distance between the user and the front of the electronic device 1000 is gradually increasing, the processor 1001 controls the display screen 1005 to switch from a screen-off state to a screen-on state.

[0140] Those skilled in the art will understand that Figure 9 The structure shown does not constitute a limitation on the electronic device 1000, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0141] In this application embodiment, a computer-readable storage medium is also provided, wherein at least one instruction is stored in the storage medium, and the at least one instruction, the at least one program segment, the code set, or the instruction set is executed by a processor to implement the signal processing method.

[0142] Optionally, the computer-readable storage medium may include: ROM (Read Only Memory), RAM (Random Access Memory), SSD (Solid State Drives), or optical disc, etc. The random access memory may include ReRAM (Resistance Random Access Memory) and DRAM (Dynamic Random Access Memory).

[0143] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the signal processing method described above.

[0144] In some embodiments, the computer program involved in the present application embodiments may be deployed and executed on a computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed in multiple locations and interconnected through a communication network. Multiple computing devices distributed in multiple locations and interconnected through a communication network may constitute a blockchain system.

[0145] It should be understood that "multiple" as used herein refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. Furthermore, the step numbers described herein are merely illustrative of one possible execution order. In some other embodiments, the steps may not be executed in numerical order, such as two steps with different numbers being executed simultaneously, or two steps with different numbers being executed in the reverse order of the illustration. This application does not limit this.

[0146] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0147] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A signal processing method, characterized in that, The method includes: Acquire the signal to be analyzed, wherein the signal to be analyzed includes multiple signal periods; Identify the original crossover points of each signal period in the signal to be analyzed; Based on the periodic phase mapped by each of the original cross points within the same signal period, phase bin statistics are performed on each of the original cross points to obtain the cross point statistics value of each phase bin in the same signal period. The cross point statistics value is used to indicate the frequency with which the original cross points of the signal to be analyzed are mapped to the phase bins. Using the intersection statistics as weights, the phase values ​​of each phase bin are weighted and statistically analyzed to obtain phase statistics data. The target crossover phase of the signal to be analyzed is determined based on the phase statistics data. The target crossover phase is used to indicate the statistical position of each of the original crossover points in the same signal period.

2. The method according to claim 1, characterized in that, The signal to be analyzed includes multiple signal sampling points, and identifying the original crossover points of each signal period in the signal to be analyzed includes: Obtain the detection threshold of the signal to be analyzed, the detection threshold being used to indicate the theoretical crossover point amplitude of the signal period; Traverse the sampling amplitudes of the multiple signal sampling points and identify adjacent signal sampling point pairs whose previous sampling amplitude and current sampling amplitude are located on both sides of the detection threshold; Based on the identified previous and current sampling amplitudes of each pair of adjacent signal sampling points, the crossover point position is estimated to obtain the original crossover point of each signal period.

3. The method according to claim 2, characterized in that, The method of estimating the intersection point position based on the identified preceding and current sampling amplitudes of each pair of adjacent signal sampling points to obtain the original intersection point for each signal period includes: If either the preceding sampling amplitude or the current sampling amplitude is infinite, the midpoint between the positions of the two signal sampling points in the adjacent signal sampling point pair is determined as the original intersection point.

4. The method according to claim 2, characterized in that, The method further includes: If the previous sample amplitude and the current sample amplitude are not infinite, interpolation is performed on the previous sample amplitude and the current sample amplitude to obtain the amplitude interpolation result; The position point corresponding to the detection threshold in the amplitude interpolation result is determined as the original intersection point.

5. The method according to claim 1, characterized in that, The step of performing phase binning statistics on each of the original crossover points based on the periodic phase mapped within the same signal period, to obtain the crossover point statistics for each phase bin within the same signal period, includes: Based on the signal period of the signal to be analyzed, the point positions of each original intersection point are moduloed to obtain the periodic phase mapped by each original intersection point within the same signal period; For each of the original crossover points, based on the number of bins in the signal period, the periodic phase is mapped to a target bin index value, where the integer part of the target bin index value indicates the first phase bin mapped to the current original crossover point. Based on the target bin index value, the crosspoint count corresponding to each original crosspoint is assigned to the corresponding first phase bin and the second phase bin adjacent to the first phase bin; The count values ​​assigned to each phase sub-box are accumulated to obtain the intersection statistics of each phase sub-box.

6. The method according to any one of claims 5, characterized in that, The step of assigning the crosspoint count corresponding to each original crosspoint to the corresponding first phase bin and the second phase bin adjacent to the first phase bin, based on the target bin index value, includes: For each of the original intersection points, determine the decimal value of the target bin index and the normalized complement of the decimal value; The decimal value of the target bin index is assigned to the second phase bin corresponding to the current original crossover point, and the normalized complement is assigned to the first phase bin corresponding to the current original crossover point.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: Based on the signal period and sampling time interval of the signal to be analyzed, the number of bins for the signal period is adaptively determined. The sampling time interval is used to indicate the time interval between adjacent signal sampling point pairs, and the number of bins is within a preset bin range.

8. The method according to any one of claims 1-6, characterized in that, The statistical values ​​of each phase bin corresponding to the signal period and the intersection points of the phase bins form a ring-shaped phase histogram. The phase values ​​of each phase bin are weighted and statistically analyzed using the intersection point statistical values ​​to obtain phase statistical data, including: Using the phase width of the phase bin as the shift step size and the number of bins as the shift count, the annular phase histogram is cyclically shifted with full offset to obtain the shifted phase histogram corresponding to each shift offset. For each shifted phase histogram, the phase values ​​of each phase bin in the shifted phase histogram are weighted and statistically analyzed using the cross-point statistical value as the weight, to obtain the phase statistical data corresponding to each shifted phase histogram.

9. The method according to claim 8, characterized in that, For each shift phase histogram, the phase values ​​of each phase bin in the shift phase histogram are weighted and statistically analyzed using the crossover point statistical value as the weight, to obtain the phase statistical data corresponding to each shift phase histogram, including: For each shifted phase histogram, the weighted phase mean and weighted phase standard deviation of the phase bin values ​​are calculated using the crossover point statistics as weights. The weighted phase mean and the weighted phase standard deviation are determined as the phase statistics of the shifted phase histogram.

10. The method according to claim 8, characterized in that, The phase statistics include a weighted phase mean and a weighted phase standard deviation. Determining the target intersection phase of the signal to be analyzed based on the phase statistics includes: Among all the shift phase histograms, the shift phase histogram with the smallest weighted phase standard deviation is determined as the target histogram; The weighted average phase value corresponding to the target histogram is normalized to obtain the target intersection phase.

11. A signal processing apparatus, characterized in that, The device includes: The acquisition module is used to acquire the signal to be analyzed, which includes multiple signal periods; The identification module is used to identify the original crossover points of each signal period in the signal to be analyzed; The binning statistics module is used to perform phase binning statistics on each of the original cross points based on the periodic phase mapped by each of the original cross points in the same signal period, and to obtain the cross point statistics value of each phase bin in the same signal period. The cross point statistics value is used to indicate the frequency with which the original cross points of the signal to be analyzed are mapped to the phase bins. The weighted statistics module is used to perform weighted statistics on the phase values ​​of each phase bin, using the intersection statistics value as the weight, to obtain phase statistics data; The determination module is used to determine the target intersection phase of the signal to be analyzed based on the phase statistics data, wherein the target intersection phase is used to indicate the statistical position of each of the original intersections in the same signal period.

12. An electronic device, characterized in that, The electronic device includes a memory and a processor, wherein the memory stores a computer program, which is loaded and executed by the processor to implement the signal processing method as described in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is loaded and executed by a processor to implement the signal processing method as described in any one of claims 1 to 10.

14. A computer program product, characterized in that, The computer program product includes a computer program that is loaded and executed by a processor to implement the signal processing method as described in any one of claims 1 to 10.

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