CN115204202A - Data processing method and device, electronic equipment and storage medium - Google Patents
Data processing method and device, electronic equipment and storage medium Download PDFInfo
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- CN115204202A CN115204202A CN202210896185.3A CN202210896185A CN115204202A CN 115204202 A CN115204202 A CN 115204202A CN 202210896185 A CN202210896185 A CN 202210896185A CN 115204202 A CN115204202 A CN 115204202A
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- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
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- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
- G06K7/10118—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves the sensing being preceded by at least one preliminary step
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Abstract
The application provides a data processing method, a data processing device, an electronic device and a storage medium, wherein the method comprises the following steps: firstly, acquiring sampling data of an original signal, secondly, intercepting analysis data from the sampling data, detecting and processing the analysis data to obtain a sampling data signal frequency, and finally, decoding the sampling data based on the signal frequency to obtain decoding data. The method and the device can solve the problem of poor reading precision caused by the fact that the current decoding frequency is not matched with the fluctuated original signal frequency, and improve the reading precision of the non-contact card reader.
Description
Technical Field
The present application relates to the field of signal processing technologies, and in particular, to a data processing method and apparatus, an electronic device, and a storage medium.
Background
The principle of Radio Frequency Identification (RFID) is that a reader and a tag perform non-contact data communication to achieve the purpose of identifying a target. Applications of radio frequency identification are very wide, such as contactless card readers, near Field Communication (NFC), animal wafers, automobile wafer burglar alarms, access control, parking lot control, production line automation, and material management.
For a contactless card reader to which an RFID is applied, an existing contactless card reader generally reads data by acquiring an original signal and decoding the original signal based on a decoding frequency matching the original signal; however, since the contactless card reader is affected by the accuracy of the system clock, the accuracy of the input signal conditioning circuit, and the rate of the Analog to Digital converter (ADC) in the process of acquiring the original signal, the frequency of the acquired original signal fluctuates, which causes a problem that the current decoding frequency is not matched with the fluctuated original signal frequency to cause poor reading accuracy when the original signal is decoded, and finally the efficiency of reading data is low. Based on this, there is a lack in the prior art of a solution to improve the reading accuracy of contactless readers.
Disclosure of Invention
In view of this, embodiments of the present application provide a data processing method and apparatus, an electronic device, and a storage medium, which enable a current decoding frequency to match a fluctuating original signal frequency when a contactless card reader decodes the original signal, thereby improving reading accuracy.
The technical scheme of the embodiment of the application is realized as follows:
in a first aspect, an embodiment of the present application provides a data processing method, including the following steps:
acquiring sampling data of an original signal, wherein the capacity of the sampling data is a first data capacity;
intercepting analysis data of a second data capacity from the sampling data, and detecting and processing the analysis data to obtain the signal frequency of the sampling data, wherein the second data capacity is smaller than the first data capacity;
and decoding the sampling data based on the signal frequency to obtain the decoded data.
In one possible embodiment, the original signal comprises one or more sampled data; when the original signal includes a plurality of sampling data, a signal frequency of each sampling data is fixed; the fixed signal frequencies of at least two of the plurality of sample data are different;
the acquiring of the sampling data of the original signal comprises:
sampling the original signal at a preset sampling rate to obtain original sampling data which is an analog signal;
and performing analog-to-digital conversion on the original sampling data of the analog signal to obtain sampling data of a digital signal.
In a possible embodiment, the intercepting analysis data of a second data volume from the sampling data and performing detection processing on the analysis data to obtain a signal frequency of the sampling data includes:
performing first conversion processing on the analysis data to obtain first spectrum data corresponding to the analysis data, wherein the resolution capability of the first conversion processing is matched with the length of the analysis data;
acquiring a frequency maximum value in the first spectrum data based on the first spectrum data, determining a main lobe where the frequency maximum value is located according to the frequency maximum value, and calculating the width of the main lobe to obtain the width of the main lobe;
performing second conversion processing on the sampling data to obtain second spectrum data corresponding to the sampling data, wherein the resolution capability of the second conversion processing is matched with the length of the sampling data, and the precision of the second conversion processing is greater than that of the first conversion processing;
determining a main lobe range of the main lobe in the second spectral data based on the main lobe width;
and acquiring a central point of the main lobe, and taking the central point as the signal frequency of the second spectrum data.
In a possible implementation, the calculating the width of the main lobe to obtain the main lobe width includes:
subtracting a first fixed value from the maximum frequency value to obtain a main lobe left boundary, and adding the first fixed value to the maximum frequency value to obtain a main lobe right boundary;
and determining the width of the main lobe according to the left boundary and the right boundary of the main lobe.
In a possible implementation manner, the decoding the sampled data based on the signal frequency to obtain the decoded data includes:
filtering the sampling data to obtain filtering data;
constructing a target square wave based on the signal frequency, wherein the period of the target square wave is matched with the signal frequency;
and performing convolution processing on the target square wave and the filtering data to obtain the decoding data.
In a possible implementation manner, the convolving the target square wave with the sampled signal to obtain the decoded data includes:
averaging the sampled signals in a sliding window by taking the sum of the period and the variation of the period as the sliding window, wherein each average comprises a confidence coefficient;
and taking the average value of which the confidence coefficient is greater than the confidence coefficient threshold value as decoding data.
In one possible embodiment, the method further comprises:
when the sliding window slides, updating the variation according to a difference value between a second time and a first time, wherein the second time represents a time difference between the sliding window passing through a third transition edge of the sampled signal and the sliding window passing through a second transition edge of the sampled signal, the first time represents a time difference between the sliding window passing through the second transition edge of the sampled signal and the sliding window passing through a first transition edge of the sampled signal, a generation time of the first transition edge is earlier than a generation time of the second transition edge, and a generation time of the second transition edge is earlier than a generation time of the third transition edge.
In a second aspect, an embodiment of the present application further provides a data processing apparatus, where the apparatus includes:
the device comprises a sampling module, a data processing module and a data processing module, wherein the sampling module is used for acquiring sampling data of an original signal, and the capacity of the sampling data is a first data capacity;
the detection module is used for intercepting analysis data of a second data capacity from the sampling data and detecting and processing the analysis data to obtain the signal frequency of the sampling data, wherein the second data capacity is smaller than the first data capacity;
and the decoding module is used for decoding the sampling data based on the signal frequency to obtain the decoding data.
In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, when the electronic device runs, the processor and the storage medium communicate with each other through the bus, and the processor executes the machine-readable instructions to execute the steps of the data processing method according to any one of the first aspect.
In a fourth aspect, this application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps of the data processing method according to any one of the first aspect.
The embodiment of the application has the following beneficial effects:
in the data acquisition stage, sampling data of an original signal is acquired to obtain sampling data of a first data volume, analysis data of a second data volume is intercepted from the sampling data, and the analysis data is detected, so that the signal frequency of the sampling data can be quickly detected with a lower data volume, and the real signal frequency of the sampling data is obtained; in the data decoding stage, the obtained real signal frequency is utilized to decode the sampled data, so that the decoding process can be matched with the real signal frequency, and the reading precision of the non-contact card reader is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is a schematic flow chart of steps S101-S103 provided in an embodiment of the present application;
FIG. 2 is a schematic flowchart of steps S201-S205 provided in an embodiment of the present application;
FIG. 3 is a schematic flow chart of steps S301-S303 provided in an embodiment of the present application;
FIG. 4 is a flowchart illustrating steps S401-S402 according to an embodiment of the present disclosure;
FIG. 5 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of protection of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In the following description, references to the terms "first \ second \ third" are only to distinguish similar objects and do not denote a particular order or importance, but rather "first \ second \ third" may, where permissible, be interchanged in a particular order or sequence so that embodiments of the present application described herein can be practiced in other than the order shown or described herein.
It should be noted that in the embodiments of the present application, the term "comprising" is used to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the application and is not intended to be limiting of the application.
Referring to fig. 1, fig. 1 is a schematic flow chart of steps S101 to S103 of a data processing method provided in an embodiment of the present application, and will be described with reference to steps S101 to S103 shown in fig. 1.
Step S101, acquiring sampling data of an original signal, wherein the capacity of the sampling data is a first data capacity;
step S102, intercepting analysis data of a second data capacity from the sampling data, and detecting and processing the analysis data to obtain a signal frequency of the sampling data, wherein the second data capacity is smaller than the first data capacity;
and step S103, decoding the sampling data based on the signal frequency to obtain the decoding data.
According to the data processing method, in the data acquisition stage, the sampling data of the original signal is acquired to obtain the sampling data of the first data capacity, the analysis data of the second data capacity is intercepted from the sampling data, and the analysis data is detected, so that the signal frequency of the sampling data can be quickly detected with lower data volume, and the real signal frequency of the sampling data is obtained; in the data decoding stage, the obtained real signal frequency is utilized to decode the sampled data, so that the decoding process can be matched with the real signal frequency, and the reading precision of the non-contact card reader is improved.
The above exemplary steps of the embodiments of the present application are described below.
In step S101, sample data of an original signal is acquired, wherein the volume of the sample data is a first data volume.
Here, the contactless reader samples the original signal through the ADC to obtain sampling data of a first data capacity, which may be preset, and in this embodiment, the first data capacity is 16K, where 1K is equal to 1024B.
In step 102, analysis data of a second data capacity is intercepted from the sampling data, and the analysis data is detected to obtain a signal frequency of the sampling data, wherein the second data capacity is smaller than the first data capacity.
In some embodiments, after the sample data is acquired, a signal frequency of the sample data is detected, wherein the signal frequency represents a real signal frequency of the sample data. In order to improve the analysis efficiency, a section of continuous analysis data is intercepted from the sampling data, and the signal frequency of the analysis data represents the signal frequency of the sampling data.
As an example, the analysis data with the length of 1K is cut from the sampling data with the length of 16K, the signal frequency of the analysis data with the length of 1K is detected, and the signal frequency of the analysis data is obtained and is taken as the signal frequency of the sampling data.
In the mode, the analysis data is intercepted from the sampling data and is detected, so that the signal frequency of the sampling data can be quickly detected with lower data volume, and the real signal frequency of the sampling data is obtained.
In step S103, the sampled data is decoded based on the signal frequency, so as to obtain the decoded data.
Here, after the true signal frequency of the sampled data is obtained, the sampled data may be decoded, and since the signal frequency is calculated after sampling by the ADC, the sampled data is decoded in a decoding manner that matches the signal frequency without being affected by the accuracy of the system clock, the accuracy of the input signal conditioning circuit, and the sampling rate of the ADC.
In some embodiments, the raw signal comprises one or more sampled data; when the original signal includes a plurality of sampling data, a signal frequency of each sampling data is fixed; the fixed signal frequencies of at least two of the plurality of sample data are different.
It should be noted that the original signal may include one or more sampling data, a complete target data may be composed of one sampling data, or may be composed of a plurality of sampling data, each sampling data has a fixed signal frequency, the signal frequency is affected by the accuracy of the system clock, the accuracy of the input signal conditioning circuit, and the ADC sampling rate, and may be any value within the fluctuation interval, and the fixed signal frequencies of at least two sampling data in the plurality of sampling data are different due to the effects of the accuracy of the system clock, the accuracy of the input signal conditioning circuit, and the ADC sampling rate.
In some embodiments, the obtaining of the sampled data of the raw signal comprises:
sampling the original signal at a preset sampling rate to obtain original sampling data which is an analog signal;
and carrying out analog-to-digital conversion processing on the original sampling data of the analog signal to obtain sampling data which is a digital signal.
As an example, the original signal is usually an analog signal, for example, when a bus card, an entrance guard card, or a meal card approaches a corresponding contactless card reader, the read/write operation of data is completed through the transmission of radio waves, and the original signal is transmitted in the form of an analog signal, so that the type of the original signal needs to be converted into a digital signal, so as to be able to detect and process the digital signal, and further obtain the signal frequency of the sampled data of the digital signal.
In some embodiments, referring to fig. 2, fig. 2 is a schematic flowchart of steps S201 to S205 provided in an embodiment of the present application, where the analysis data of the second data volume is intercepted from the sampling data, and the analysis data is subjected to detection processing, so as to obtain the signal frequency of the sampling data, which can be implemented by steps S201 to S205, and the steps are collected for description.
In step S201, a first conversion process is performed on the analysis data to obtain first spectrum data corresponding to the analysis data, where a resolution of the first conversion process matches a length of the analysis data.
In some embodiments, the analysis data cut out from the sampling data needs to be converted into the first spectrum data through the first conversion process, so that the frequency of the first spectrum data can be maximized based on the first spectrum data, and in the conversion process, in order to improve the conversion efficiency, the resolution of the first conversion process is matched with the length of the analysis data.
As an example, a fourier transform (FFT) is performed on the analysis data with a length of 1K, and here, an FFT with a length of 1K is used, and since the length of the analysis data is 1K, it is meaningless to use an FFT with an excessively high length, and after the fourier transform, the first spectrum data is obtained.
In the above manner, the analysis data is converted to obtain the first spectrum data of the analysis data, and a basis is provided for subsequently solving the frequency maximum value of the first spectrum data.
In step S202, a frequency maximum value in the first spectrum data is obtained based on the first spectrum data, a main lobe where the frequency maximum value is located is determined according to the frequency maximum value, and a width of the main lobe is calculated to obtain a main lobe width.
Here, after obtaining the first spectrum data, the frequency maximum of the first spectrum data may be directly obtained based on the first spectrum data, and the main lobe where the frequency maximum is located may be determined.
In step S203, performing a second conversion process on the sample data to obtain second spectrum data corresponding to the sample data, where a resolution of the second conversion process matches a length of the sample data, and a precision of the second conversion process is greater than a precision of the first conversion process.
In some embodiments, after obtaining the main lobe width, the main lobe width needs to be applied to the sampled data to determine the main lobe range in the sampled data. Therefore, the second conversion processing needs to be performed on the sample data to obtain second spectrum data corresponding to the sample data. Since the analysis data is cut out from the sample data, the accuracy of the second conversion process is greater than that of the first conversion process, and the resolving power of the second conversion process is matched with the length of the sample data.
As an example, a fourier transform (FFT) is performed on the sample data with the length of 16K, and since the length of the sample data is 16K, the FFT with the length of 16K is adopted here, and after the fourier transform, the second spectrum data is obtained.
In the manner, the sampling data is converted to obtain the second spectrum data of the sampling data, and a basis is provided for solving the main lobe range in the second spectrum data corresponding to the sampling data through the main lobe width.
In step S204, a main lobe range of the main lobe in the second spectral data is determined based on the main lobe width.
Here, since the above-described embodiment obtains the main lobe and the main lobe width, the main lobe range of the second spectral data is easily determined in the second spectral data.
In step S205, a central point of the main lobe is obtained, and the central point is used as a signal frequency of the second spectrum data.
Here, a central point of the main lobe, that is, an inflection point of the main lobe, may be determined according to the main lobe range of the second spectrum data, and the inflection point represents a signal frequency of the second spectrum data, that is, a true signal frequency of the sample data.
In some embodiments, the calculating the width of the main lobe to obtain the main lobe width includes:
subtracting a first fixed value from the maximum frequency value to obtain a main lobe left boundary, and adding the first fixed value to the maximum frequency value to obtain a main lobe right boundary;
and determining the width of the main lobe according to the left boundary and the right boundary of the main lobe.
As an example, the left/right boundary of the main lobe is obtained by adding/subtracting a first fixed value to/from the frequency maximum Fmax. In the embodiment of the present application, the first fixed value is set to 100, and the width of the frequency maximum value Fmax is [ Fmax-100, fmax +100].
In some embodiments, referring to fig. 3, fig. 3 is a schematic flowchart of steps S301 to S303 provided in an embodiment of the present application, where the decoding processing is performed on the sampled data based on the signal frequency, and obtaining the decoded data may be implemented by steps S301 to S303, and the steps will be described in a set.
In step S301, the sampled data is filtered to obtain filtered data.
Before decoding the sampled data, filtering the sampled data to obtain filtered data is required, so that any amplitude-frequency characteristic in the filtered data is guaranteed and the filtered data has strict linear phase-frequency characteristics.
In step S302, a target square wave is constructed based on the signal frequency, wherein the period of the target square wave matches the signal frequency.
Here, a target square wave is constructed from the obtained signal frequency representing the true of the sampled data for decoding the filtered data. The period T of the constructed target square wave matches the signal frequency, i.e., T =1/f, where f represents the signal frequency, so that the accuracy of decoding can be improved.
In step S303, performing convolution processing on the target square wave and the filtered data to obtain the decoded data.
Here, the target square wave is convolved with the filtered data, the filtered data is slid through a sliding window, classification operation and regression operation are performed on the data in each window, the classification operation obtains different confidence degrees, the regression operation returns values above the confidence degree, and finally decoded data is obtained.
In the mode, the square wave with the period matched with the signal frequency is constructed through the true signal frequency of the acquired sampling data, and the filtering data is decoded in a self-adaptive manner through convolution of the square wave and the filtering data, so that the decoding precision is improved.
In some embodiments, referring to fig. 4, fig. 4 is a schematic flowchart of steps S401 to S402 provided in this embodiment, where the convolving process is performed on the target square wave and the sampling signal, and the obtaining of the decoded data may be implemented by steps S401 to S402, which will be described with reference to the steps.
In step S401, averaging the sampled signals in a sliding window, where the sliding window is the sum of the period and the variation of the period, and each average includes a confidence level;
as an example, a sliding window is set to T + Δ, where Δ is the amount of change, and when the window slides, the data in this window is averaged, with confidence set to 1 if greater than 0.5 and 0 if less than 0.5.
In step S402, the average value of which the confidence is greater than the confidence threshold is taken as the decoded data.
As an example, the confidence threshold here may be set flexibly, and in the embodiment of the present application, an average value with confidence of 1 is returned as the decoded data.
In some embodiments, the method further comprises:
when the sliding window slides, updating the variation according to a difference value between a second time and a first time, wherein the second time represents a time difference between the sliding window passing through a third transition edge of the sampling signal and the sliding window passing through a second transition edge of the sampling signal, the first time represents a time difference between the sliding window passing through the second transition edge of the sampling signal and the sliding window passing through a first transition edge of the sampling signal, the generation time of the first transition edge is earlier than that of the second transition edge, and the generation time of the second transition edge is earlier than that of the third transition edge.
As an example, Δ in the sliding window needs to be updated according to the transition edge of the convolved data, specifically, when the sliding window passes through the sampling signal, the sliding window passes through the transition edge y1 of the sampling signal, at time t1, the sliding window passes through the transition edge y2, at the second time, the sliding window passes through the transition edge y2, and at time t3, the sliding window passes through the transition edge y3, so at time t3, we need to update Δ = (t 3-t 2) - (t 2-t 1).
In summary, the embodiments of the present application have the following beneficial effects:
in the data acquisition stage, sampling data of an original signal is acquired to obtain sampling data of a first data volume, analysis data of a second data volume is intercepted from the sampling data, and the analysis data is detected, so that the signal frequency of the sampling data can be quickly detected with a lower data volume, and the real signal frequency of the sampling data is obtained; in the data decoding stage, the obtained real signal frequency is utilized to decode the sampled data, so that the decoding process can be matched with the real signal frequency, and the reading precision of the non-contact card reader is improved.
Based on the same inventive concept, the embodiment of the present application further provides a data processing apparatus corresponding to the data processing method in the first embodiment, and since the principle of the apparatus in the embodiment of the present application for solving the problem is similar to that of the data processing method, the implementation of the apparatus may refer to the implementation of the method, and repeated details are not repeated.
As shown in fig. 5, fig. 5 is a schematic structural diagram of a data processing apparatus 500 according to an embodiment of the present application. The data processing apparatus 500 includes:
a sampling module 501, configured to obtain sampling data of an original signal, where a capacity of the sampling data is a first data capacity;
a detection module 502, configured to intercept analysis data of a second data capacity from the sampled data, and perform detection processing on the analysis data to obtain a signal frequency of the sampled data, where the second data capacity is smaller than the first data capacity;
a decoding module 503, configured to perform decoding processing on the sampled data based on the signal frequency to obtain the decoded data.
Those skilled in the art will understand that the functions implemented by the units in the data processing apparatus 500 shown in fig. 5 can be understood by referring to the related description of the data processing method. The functions of the units in the data processing apparatus 500 shown in fig. 5 can be implemented by a program running on a processor, and can also be implemented by specific logic circuits.
In one possible implementation, the sampling module 501 obtains sampling data of an original signal, including:
sampling the original signal at a preset sampling rate to obtain original sampling data which is an analog signal;
and performing analog-to-digital conversion on the original sampling data of the analog signal to obtain sampling data of a digital signal.
In a possible implementation, the detecting module 502 intercepts, from the sampled data, analysis data of a second data volume, and performs a detection process on the analysis data to obtain a signal frequency of the sampled data, including:
performing first conversion processing on the analysis data to obtain first spectrum data corresponding to the analysis data, wherein the resolution capacity of the first conversion processing is matched with the length of the analysis data;
acquiring a frequency maximum value in the first spectrum data based on the first spectrum data, determining a main lobe where the frequency maximum value is located according to the frequency maximum value, and calculating the width of the main lobe to obtain the width of the main lobe;
performing second conversion processing on the sampling data to obtain second spectrum data corresponding to the sampling data, wherein the resolution capability of the second conversion processing is matched with the length of the sampling data, and the precision of the second conversion processing is greater than that of the first conversion processing;
determining a main lobe range of the main lobe in the second spectral data based on the main lobe width;
and acquiring a central point of the main lobe, and taking the central point as the signal frequency of the second spectrum data.
In a possible implementation, the detecting module 502 calculates the width of the main lobe to obtain the main lobe width, including:
subtracting a first fixed value from the maximum frequency value to obtain a main lobe left boundary, and adding the first fixed value to the maximum frequency value to obtain a main lobe right boundary;
and determining the width of the main lobe according to the left boundary and the right boundary of the main lobe.
In a possible implementation manner, the decoding module 503 performs a decoding process on the sampled data based on the signal frequency to obtain the decoded data, and includes:
filtering the sampling data to obtain filtering data;
constructing a target square wave based on the signal frequency, wherein the period of the target square wave is matched with the signal frequency;
and carrying out convolution processing on the target square wave and the filtering data to obtain the decoding data.
In a possible implementation manner, the performing, by the decoding module 503, a convolution process on the target square wave and the sampling signal to obtain the decoded data includes:
averaging the sampled signals in a sliding window by taking the sum of the period and the variation of the period as the sliding window, wherein each average comprises a confidence coefficient;
and taking the average value of which the confidence coefficient is greater than the confidence coefficient as decoding data.
In a possible implementation, the decoding module 503 further includes:
when the sliding window slides, updating the variation according to a difference value between a second time and a first time, wherein the second time represents a time difference between the sliding window passing through a third transition edge of the sampling signal and the sliding window passing through a second transition edge of the sampling signal, the first time represents a time difference between the sliding window passing through the second transition edge of the sampling signal and the sliding window passing through a first transition edge of the sampling signal, the generation time of the first transition edge is earlier than that of the second transition edge, and the generation time of the second transition edge is earlier than that of the third transition edge.
The data processing device acquires the sampling data of the original signal to obtain the sampling data of a first data capacity, intercepts the analysis data of a second data capacity from the sampling data, and detects the analysis data, so that the signal frequency of the sampling data can be quickly detected with a lower data volume to obtain the real signal frequency of the sampling data; in the data decoding stage, the obtained real signal frequency is utilized to decode the sampled data, so that the decoding process can be matched with the real signal frequency, and the reading precision of the non-contact card reader is improved.
As shown in fig. 6, fig. 6 is a schematic view of a composition structure of an electronic device 600 provided in an embodiment of the present application, where the electronic device 600 includes:
the data processing system comprises a processor 601, a storage medium 602 and a bus 603, wherein the storage medium 602 stores machine-readable instructions executable by the processor 601, when the electronic device 600 runs, the processor 601 and the storage medium 602 communicate through the bus 603, and the processor 601 executes the machine-readable instructions to perform the steps of the data processing method according to the embodiment of the present application.
In practice, the various components in the electronic device 600 are coupled together by a bus 603. It is understood that the bus 603 is used to enable communications among the components. The bus 603 includes a power bus, a control bus, and a status signal bus, in addition to a data bus. But for clarity of illustration the various busses are labeled as bus 603 in figure 6.
The electronic equipment acquires the sampling data of the original signal to obtain the sampling data of a first data capacity, intercepts the analysis data of a second data capacity from the sampling data, and detects the analysis data, so that the signal frequency of the sampling data can be quickly detected with a lower data volume to obtain the real signal frequency of the sampling data; in the data decoding stage, the obtained real signal frequency is utilized to decode the sampled data, so that the decoding process can be matched with the real signal frequency, and the reading precision of the non-contact card reader is improved.
The embodiment of the present application further provides a computer-readable storage medium, where the storage medium stores executable instructions, and when the executable instructions are executed by at least one processor 601, the data processing method according to the embodiment of the present application is implemented.
In some embodiments, the storage medium may be a Memory such as a magnetic random Access Memory (FRAM), a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read-Only Memory (CD-ROM); or may be various devices including one or any combination of the above memories.
In some embodiments, executable instructions may be written in any form of programming language (including compiled or interpreted languages), in the form of programs, software modules, scripts or code, and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
By way of example, executable instructions may correspond, but do not necessarily have to correspond, to files in a file system, and may be stored in a portion of a file that holds other programs or data, such as in one or more scripts stored in a hypertext markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code).
By way of example, executable instructions may be deployed to be executed on one computing device or on multiple computing devices at one site or distributed across multiple sites and interconnected by a communication network.
The computer-readable storage medium acquires the sampling data of the original signal to obtain the sampling data of a first data volume, intercepts the analysis data of a second data volume from the sampling data, and detects the analysis data, so that the signal frequency of the sampling data can be quickly detected with a lower data volume to obtain the real signal frequency of the sampling data; in the data decoding stage, the obtained real signal frequency is utilized to decode the sampled data, so that the decoding process can be matched with the real signal frequency, and the reading precision of the non-contact card reader is improved.
In the several embodiments provided in the present application, it should be understood that the disclosed method and electronic device may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a platform server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A data processing method, characterized by comprising the steps of:
acquiring sampling data of an original signal, wherein the capacity of the sampling data is a first data capacity;
intercepting analysis data of a second data capacity from the sampling data, and detecting and processing the analysis data to obtain the signal frequency of the sampling data, wherein the second data capacity is smaller than the first data capacity;
and decoding the sampling data based on the signal frequency to obtain the decoded data.
2. The method of claim 1, wherein the original signal comprises one or more sampled data; when the original signal includes a plurality of sampling data, a signal frequency of each sampling data is fixed; the fixed signal frequencies of at least two of the plurality of sampling data are different;
the acquiring of the sampling data of the original signal includes:
sampling the original signal at a preset sampling rate to obtain original sampling data which is an analog signal;
and carrying out analog-to-digital conversion processing on the original sampling data of the analog signal to obtain sampling data which is a digital signal.
3. The method of claim 1, wherein intercepting the analysis data of the second data volume from the sampling data and performing detection processing on the analysis data to obtain the signal frequency of the sampling data comprises:
performing first conversion processing on the analysis data to obtain first spectrum data corresponding to the analysis data, wherein the resolution capacity of the first conversion processing is matched with the length of the analysis data;
acquiring a frequency maximum value in the first spectrum data based on the first spectrum data, determining a main lobe where the frequency maximum value is located according to the frequency maximum value, and calculating the width of the main lobe to obtain the width of the main lobe;
performing second conversion processing on the sampling data to obtain second spectrum data corresponding to the sampling data, wherein the resolution capability of the second conversion processing is matched with the length of the sampling data, and the precision of the second conversion processing is greater than that of the first conversion processing;
determining a main lobe range of the main lobe in the second spectral data based on the main lobe width;
and acquiring a central point of the main lobe, and taking the central point as the signal frequency of the second spectrum data.
4. The method of claim 3, wherein said calculating the width of the main lobe to obtain a main lobe width comprises:
subtracting a first fixed value from the maximum frequency value to obtain a main lobe left boundary, and adding the first fixed value to the maximum frequency value to obtain a main lobe right boundary;
and determining the width of the main lobe according to the left boundary and the right boundary of the main lobe.
5. The method of claim 1, wherein the decoding the sampled data based on the signal frequency to obtain the decoded data comprises:
filtering the sampling data to obtain filtered data;
constructing a target square wave based on the signal frequency, wherein the period of the target square wave is matched with the signal frequency;
and performing convolution processing on the target square wave and the filtering data to obtain the decoding data.
6. The method of claim 5, wherein the convolving the target square wave with the sampled signal to obtain the decoded data comprises:
averaging the sampled signals in a sliding window by taking the sum of the period and the variation of the period as the sliding window, wherein each average comprises a confidence coefficient;
and taking the average value of which the confidence coefficient is greater than the confidence coefficient as decoding data.
7. The method of claim 6, further comprising:
when the sliding window slides, updating the variation according to a difference value between a second time and a first time, wherein the second time represents a time difference between the sliding window passing through a third transition edge of the sampled signal and the sliding window passing through a second transition edge of the sampled signal, the first time represents a time difference between the sliding window passing through the second transition edge of the sampled signal and the sliding window passing through a first transition edge of the sampled signal, a generation time of the first transition edge is earlier than a generation time of the second transition edge, and a generation time of the second transition edge is earlier than a generation time of the third transition edge.
8. A data processing apparatus, characterized in that the apparatus comprises:
the device comprises a sampling module, a data processing module and a data processing module, wherein the sampling module is used for acquiring sampling data of an original signal, and the capacity of the sampling data is a first data capacity;
the detection module is used for intercepting analysis data of a second data capacity from the sampling data and detecting and processing the analysis data to obtain the signal frequency of the sampling data, wherein the second data capacity is smaller than the first data capacity;
and the decoding module is used for decoding the sampling data based on the signal frequency to obtain the decoding data.
9. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the electronic device is operating, the processor executing the machine-readable instructions to perform the steps of the data processing method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, performs the steps of the data processing method according to any one of claims 1 to 7.
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| CN117614607B (en) * | 2024-01-18 | 2024-04-12 | 深圳市海域达赫科技有限公司 | Information security transmission system and method based on block chain |
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