Method and system for accurate payment positioning matching based on communication technology
By analyzing the fluctuation characteristics and evaluating the trend of communication payment signals, dynamically adjusting the adaptive filtering step factor, the problems of attenuation and delay effects of payment signal in urban environments are solved, and the accuracy of payment accuracy and signal authenticity are improved.
Patent Information
- Application Number
- CN202410779230.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-06-17
- Publication Date
- 2024-12-10
- Estimated Expiration
- 2044-06-17
AI Technical Summary
In complex urban environments, building occlusion and electromagnetic noise lead to signal attenuation and delay of communication payment signals, affecting the accuracy of payment precise positioning. The existing adaptive filtering algorithm is limited in the fluctuation period, resulting in poor positioning accuracy .
By obtaining the subsequence of the mutation point segmentation of the communication payment signal, the fluctuation characteristic coefficient, the jitter intensity evaluation quantity and the data fluctuation degree coefficient are calculated, the adaptive step factor is dynamically adjusted, and the filtering process is performed to improve positioning accuracy.
By analyzing the fluctuation characteristics and trend changes of communication payment signals, the step size factor of the adaptive filtering algorithm is optimized, signal authenticity is enhanced, positioning accuracy of mobile payment devices is improved, and noise impact is reduced.
Smart Images
Figure CN118741415B_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of communication signal positioning technology, and in particular to a method and system for precise payment positioning matching based on communication technology. Background Art
[0002] In recent years, with the rapid development of communication technology and the Internet, mobile payment has become an indispensable part of daily life. With the diversification and intelligence of payment methods, ensuring the authenticity and security of the payment process has become a core issue in the development of payment technology. Accurate positioning of QR code payment is one of the important criteria for judging the authenticity and security of payment. Accurate positioning of payment usually adopts triangulation of LTE / 5G networks or base station positioning technology based on signal arrival time difference. Although it can cover a wide area, in complex urban environments, building occlusion, multipath reflection and electromagnetic noise will cause signal attenuation and delay, thus affecting the accuracy of positioning results.
[0003] At present, adaptive filtering is often used to enhance the transmitted signal and increase the real strength of the signal. However, since the communication payment signal in the urban environment will fluctuate to varying degrees in a continuous period of time, the filtering effect of the communication payment signal is limited by the step size factor of the adaptive filtering algorithm, resulting in poor positioning accuracy. Summary of the invention
[0004] In order to solve the above technical problems, the purpose of this application is to provide a method and system for accurate payment positioning matching based on communication technology. The technical solutions adopted are as follows:
[0005] In a first aspect, an embodiment of the present application provides a method for accurate positioning and matching of payment based on communication technology, the method comprising the following steps:
[0006] S1, obtaining a communication payment signal sent by a mobile payment device, segmenting the communication payment signal by mutation points, and obtaining each communication payment subsequence;
[0007] S2, based on the differences in the numerical distribution and trend changes among all the communication payment subsequences, obtain the adaptive step size factor, which specifically includes:
[0008] S21, obtaining the fluctuation characteristic coefficient of each communication payment subsequence according to the numerical distribution of elements in each communication payment subsequence;
[0009] S22, updating the volatility characteristic coefficient according to the difference between the volatility characteristic coefficients of all communication payment subsequences to obtain an updated volatility characteristic coefficient of each communication payment subsequence;
[0010] S23, obtaining a jitter intensity assessment value according to the trend change of each communication payment subsequence;
[0011] S24, obtaining a data fluctuation coefficient of the communication payment signal according to the jitter intensity evaluation amount of all communication payment subsequences and the updated fluctuation characteristic coefficient;
[0012] S25, calculating an adaptive step size factor according to a data fluctuation coefficient of the communication payment signal;
[0013] S3, filtering the communication payment signal according to the adaptive step size factor; performing positioning calculation on the filtered communication payment signal to obtain a positioning result of the mobile payment device.
[0014] Further, the fluctuation characteristic coefficient of each communication payment subsequence is obtained according to the numerical distribution of elements in each communication payment subsequence, including:
[0015] Obtaining the first-order difference sequence of each communication payment subsequence, and calculating the mean of the first-order difference sequence; obtaining the range of all elements in each communication payment subsequence;
[0016] The fluctuation characteristic coefficient of each communication payment subsequence is determined according to the range and the mean; the fluctuation characteristic coefficient is a positive fusion of the range and the mean.
[0017] Furthermore, the method for obtaining the update fluctuation characteristic coefficient of each communication payment subsequence includes:
[0018] Calculate the error elimination value based on the differences in the fluctuation characteristic coefficients of all communication payment subsequences;
[0019] Calculate the absolute value of the difference between the fluctuation characteristic coefficients of any two communication payment subsequences; record the two communication payment subsequences whose absolute value of the difference is less than the error elimination value as the same fluctuation class; calculate the average value of the fluctuation characteristic coefficients of the communication payment subsequences contained in each fluctuation class, and record it as the fluctuation characteristic value of each fluctuation class;
[0020] The updated fluctuation characteristic coefficient of each communication payment subsequence is the fluctuation characteristic value of the fluctuation class to which each communication payment subsequence belongs.
[0021] Furthermore, the process of obtaining the error elimination value includes:
[0022] Arrange the volatility coefficients of all communication payment subsequences in ascending order to form a volatility coefficient sequence; record the first preset number of elements in the first-order difference sequence of the volatility coefficient sequence as error values; record the error values with the same value as one category to obtain various error categories; and take the average of the error values corresponding to all error categories as the error elimination value.
[0023] Further, obtaining the jitter intensity evaluation amount according to the trend change of each communication payment subsequence includes:
[0024] Record any element in the first-order difference sequence of each communication payment subsequence as a target element, and obtain the numerical sign of the target element;
[0025] According to the difference in numerical signs between the target element and its previous element, the sign-changed value of the target element is obtained;
[0026] Obtaining the cumulative sum of the sign change values of all elements contained in the first-order difference sequence, and recording it as the number of sign changes of each communication payment subsequence;
[0027] Obtain the variance of the first-order difference sequence of each communication payment subsequence; and use the product of the number of sign changes of each communication payment subsequence and the variance as the jitter strength evaluation amount of each communication payment signal subsequence.
[0028] Furthermore, the method for obtaining the sign change value of the target element includes: if the target element has the same numerical sign as the previous element, the sign change value of the target element is 0; otherwise, the sign change value of the target element is 1.
[0029] Furthermore, the method for obtaining the data fluctuation coefficient of the communication payment signal includes:
[0030] The forward fusion result of the jitter intensity evaluation amount of each communication payment subsequence and the updated volatility characteristic coefficient is used as the data volatility degree of each communication payment subsequence;
[0031] The sum of the data fluctuation levels of all communication payment subsequences is taken as the data fluctuation coefficient of the communication payment signal.
[0032] Further, the calculation of the adaptive step size factor according to the data fluctuation coefficient of the communication payment signal specifically includes:
[0033] The communication payment signal is filtered by an adaptive filtering algorithm to obtain the original step factor; the normalized value of the data fluctuation coefficient of the communication payment signal is calculated and recorded as the modification coefficient; the product of the modification coefficient and the original step factor is used as the adaptive step factor of the communication payment signal.
[0034] Further, filtering the communication payment signal according to the adaptive step size factor; performing positioning calculation on the filtered communication payment signal to obtain a positioning result of the mobile payment device includes:
[0035] The adaptive step factor is used to replace the step factor in the adaptive filtering algorithm, and the communication payment signal is filtered to obtain a filtered communication payment signal; the filtered communication payment signal is solved by a positioning algorithm to obtain the coordinates of the mobile payment device.
[0036] In a second aspect, an embodiment of the present application also provides a payment precise positioning and matching system based on communication technology, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above methods when executing the computer program.
[0037] This application has at least the following beneficial effects:
[0038] The present application analyzes the fluctuation characteristics of the communication payment signal. First, the fluctuation conditions of different communication payment subsequences are analyzed, and the fluctuation characteristic coefficients of the communication payment subsequences are calculated to reflect the significant fluctuations of the communication payment signal within a certain time range, so as to divide the signal waves with the same fluctuation characteristics under different waveforms; further, the influence of noise on the calculation of the fluctuation characteristics of the communication payment subsequences is eliminated through the differences between the fluctuation characteristic coefficients; through the analysis of the trend changes of the communication subsequences, the jitter strength assessment amount is calculated to reflect the quality status of the signal, and the jitter strength assessment amount is used as the weight value for updating the fluctuation characteristic coefficient to calculate the data fluctuation degree coefficient of the communication payment sequence, reflecting the fluctuation characteristics and jitter characteristics of the communication payment sequence. When the fluctuation characteristics and jitter characteristics of the communication payment sequence are stronger, the adaptive filtering should adopt a smaller step size factor to make it adapt to the changes in the data more smoothly; further, the adaptive step size factor is calculated through the data fluctuation degree coefficient, and the communication payment signal is enhanced by substituting it into the adaptive filtering algorithm, so that the enhanced communication payment signal has better authenticity, thereby improving the positioning accuracy of the mobile payment device. BRIEF DESCRIPTION OF THE DRAWINGS
[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0040] Figure 1 A flowchart of the steps of a method for precise positioning and matching of payment based on communication technology provided in one embodiment of the present application;
[0041] Figure 2 It is a block diagram for obtaining the adaptive step size factor;
[0042] Figure 3 This is a schematic diagram of the principle of triangulation positioning. DETAILED DESCRIPTION
[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0044] 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.
[0045] The specific scheme of the method and system for precise payment positioning matching based on communication technology provided by the present application is described in detail below with reference to the accompanying drawings.
[0046] See also Figure 1 , which shows a flowchart of a method for precise positioning and matching of payment based on communication technology provided by an embodiment of the present application, the method comprising the following steps:
[0047] S1, obtaining a communication payment signal sent by a mobile payment device, segmenting the communication payment signal by mutation points, and obtaining each communication payment subsequence.
[0048] During the payment positioning process, the mobile payment device sends out a communication payment signal and transmits the signal to the signal base station through the operator network or wireless network. The signal base station transmits the communication payment signal and evenly collects the payment signal during the transmission process. The sampling frequency is 3500MHz, and the number of samples collected is N, where N takes an empirical value of 1000.
[0049] Since the communication payment signal has a signal segmentation phenomenon, when analyzing the signal fluctuation of the communication payment signal, using the overall mean or variance can easily cause the fluctuation data to lose its local characteristics. Therefore, this embodiment first uses the BG segmentation algorithm to segment the communication payment signal to obtain each communication payment subsequence. Among them, the BG segmentation algorithm only provides an algorithm for segmenting the communication payment signal for this embodiment. The specific implementation process of the BG segmentation algorithm is a well-known technology and will not be repeated. Under the premise that the purpose of segmentation can be achieved, as other implementation methods, the implementer can also use other feasible signal segmentation algorithms in the prior art that segmentation is performed according to the mutation characteristics of the data.
[0050] S2, obtains the adaptive step size factor based on the differences in numerical distribution and trend changes among all communication payment subsequences.
[0051] S21, obtaining the fluctuation characteristic coefficient of each communication payment subsequence according to the numerical distribution of the elements in each communication payment subsequence.
[0052] When analyzing the local fluctuation characteristics of each communication payment subsequence, different communication payment subsequences have the same numerical distribution characteristics. For example, the two data curves of sin(x) and 2sin(x / 2) are different but their unit fluctuation characteristics are the same. The fluctuation characteristic coefficient of the subsequence is calculated based on the numerical distribution characteristics within the subsequence.
[0053] Obtain the first-order difference sequence of each communication payment subsequence, calculate the mean of the first-order difference sequence, and represent the variation range of the communication payment subsequence; obtain the range of all elements in each communication payment subsequence;
[0054] The fluctuation characteristic coefficient of each communication payment subsequence is determined according to the range and the mean; the fluctuation characteristic coefficient is a positive fusion of the range and the mean.
[0055] It should be noted that forward fusion means that the fused data and the fused result have a same-direction changing relationship, where the larger the fused data, the larger the fused result. Forward fusion can specifically be a multiplication relationship, an addition relationship, etc., which is determined by the actual application and this application does not impose any special restrictions.
[0056] As an embodiment of the present application, the fluctuation characteristic coefficient is the product of the range and the mean.
[0057] When the volatility characteristic coefficient is large, this usually indicates that the communication payment subsequence has experienced significant fluctuations within a certain time range, that is, the signal exhibits large dynamic changes in this subsequence, indicating that the communication payment signal has a higher intensity in this communication payment subsequence.
[0058] S22, updating the fluctuation characteristic coefficient according to the difference between the fluctuation characteristic coefficients of all communication payment subsequences to obtain the updated fluctuation characteristic coefficient of each communication payment subsequence.
[0059] According to the differences between the fluctuation characteristic coefficients of all communication payment subsequences, the fluctuation characteristic coefficient is updated to obtain the updated fluctuation characteristic coefficient of each communication payment subsequence.
[0060] For the fluctuation characteristic coefficient of the above communication payment subsequence, under normal circumstances, the fluctuation characteristic coefficients calculated for the communication payment subsequences with the same fluctuation characteristic are the same. Due to the possibility of noise in the data, there may be slight differences in the fluctuation characteristic coefficients calculated in the actual communication payment subsequence. In order to eliminate the influence of noise on the fluctuation characteristics and characterize the true fluctuation characteristics of the communication subsequence, the error elimination value is calculated according to the differences in the fluctuation characteristic coefficients of all communication payment subsequences:
[0061] Arrange the volatility coefficients of all communication payment subsequences in ascending order to form a volatility coefficient sequence; record the first preset number of elements in the first-order difference sequence of the volatility coefficient sequence as error values; record the error values with the same value as one category to obtain various error categories; and take the average of the error values corresponding to all error categories as the error elimination value.
[0062] For example, a set of error values is 2, 1, 1, 1, 3, 3, 4. There are 4 categories in this set of error values, and the corresponding error values are 2, 1, 3, 4. Then the error elimination value is the average of the four values 2, 1, 3, 4.
[0063] In this embodiment, the error value is taken as the first 50% of the elements of the first-order difference sequence of the fluctuation characteristic coefficient sequence. As other implementation methods, the implementer can select the number of error values at will.
[0064] Furthermore, the error elimination value is used to eliminate the fluctuation characteristic coefficient of the communication payment subsequence, and the elimination method is:
[0065] Calculate the absolute value of the difference between the fluctuation characteristic coefficients of any two communication payment subsequences; record the two communication payment subsequences whose absolute value of the difference is less than the error elimination value as the same fluctuation class; calculate the mean value of the fluctuation characteristic coefficients of the communication payment subsequences contained in each fluctuation class, and record it as the fluctuation characteristic value of each fluctuation class; the updated fluctuation characteristic coefficient of each communication payment subsequence is the fluctuation characteristic value of the fluctuation class to which each communication payment subsequence belongs. In this way, the influence of noise on the calculation of the fluctuation characteristic coefficient of the communication payment subsequence is eliminated.
[0066] When the error elimination value is smaller, it usually means that the noise has less impact on the calculation of the fluctuation characteristic coefficient of the communication payment subsequence. It means that the calculated fluctuation characteristic coefficient is closer to the real fluctuation characteristic. A smaller error elimination value enables more accurate capture of the fluctuation characteristics of the signal data in the communication payment subsequence, and thus makes the data value obtained more accurate when the fluctuation characteristic coefficient is updated by the error elimination value. Such accuracy is crucial for the enhancement of the communication payment signal because it ensures a more accurate understanding of the fluctuation in the communication payment signal.
[0067] S23, obtaining a jitter intensity assessment value according to the trend change of each communication payment subsequence.
[0068] When performing signal enhancement on the communication payment subsequence through adaptive filtering, the algorithm step factor needs to be considered to adapt to the volatility of the data. Communication payment signals are usually smoother and have a strong local trend, so the trend characteristics of the data can be used to estimate the jitter intensity. The specific process includes:
[0069] For any element in the first-order difference sequence of each communication payment subsequence, obtain the numerical sign of the element; wherein, the numerical sign of the element is obtained in the following manner: if the element is a positive number or the number 0, the numerical sign of the element is a positive sign; if the element is a negative number, the numerical sign of the element is a negative sign.
[0070] If the target element has the same numerical sign as the previous element, the sign change value of the target element is 0; otherwise, the sign change value of the target element is 1; the cumulative sum of the sign change values of all elements contained in the first-order difference sequence is obtained, and recorded as the number of sign changes of each communication payment subsequence.
[0071] For example, if a set of data is -1, 1, 1, then the number of times the sign of this set of data changes is 1; if a set of data is -1, 1, -1, then the number of times the sign of this set of data changes is 2.
[0072] Obtain the variance of the first-order difference sequence of each communication payment subsequence; and use the product of the number of sign changes of each communication payment subsequence and the variance as the jitter strength evaluation amount of each communication payment signal subsequence.
[0073] The larger the jitter intensity assessment, the worse the data stability and the greater the local jitter of the data, which indicates that the communication payment signal is subject to more external influences or interference during the transmission process. Such external influences may come from factors such as noise, interference, and signal attenuation in the communication channel, or may be caused by jitter, clock deviation, or data processing delay within the system. Communication payment signals with large local jitter may cause difficulties in data analysis and processing.
[0074] S24, obtaining the data fluctuation coefficient of the communication payment signal according to the jitter intensity evaluation amount of all communication payment subsequences and the updated fluctuation characteristic coefficient.
[0075] The degree of data fluctuation of the communication payment subsequence can be further determined by the jitter intensity assessment amount and the update fluctuation characteristic coefficient, mapping the data parsing and processing difficulty of the communication payment subsequence.
[0076] Specifically, the data fluctuation degree is obtained according to the jitter strength evaluation amount and the updated fluctuation characteristic coefficient of each communication payment subsequence; the data fluctuation degree of each communication payment subsequence is the forward fusion of the jitter strength evaluation amount and the updated fluctuation characteristic coefficient of each communication payment subsequence.
[0077] As an embodiment of the present application, the data fluctuation degree of each communication payment subsequence is the product of the jitter intensity evaluation amount of each communication payment subsequence and the update fluctuation characteristic coefficient.
[0078] The sum of the data fluctuation levels of all communication payment subsequences is taken as the data fluctuation coefficient of the communication payment signal.
[0079] S25, calculating the adaptive step size factor according to the data fluctuation coefficient of the communication payment signal.
[0080] When the jitter intensity and data fluctuation intensity in the communication payment signal are greater, using a smaller step size factor in the adaptive filtering algorithm can slow down the update speed and make it adapt to data changes more smoothly. The adaptive step size factor of the adaptive filtering algorithm is calculated by the data fluctuation coefficient of the communication payment sequence, specifically:
[0081] The communication payment signal is filtered using an adaptive filtering algorithm to obtain the original step factor; wherein, the calculation of the original step factor in the adaptive filtering algorithm filtering process is a well-known technique and will not be described in detail. The normalized value of the data fluctuation coefficient of the communication payment signal is calculated and recorded as the modification coefficient; the product of the modification coefficient and the original step factor is used as the adaptive step factor of the communication payment signal.
[0082] The block diagram for obtaining the adaptive step size factor is as follows: Figure 2 shown.
[0083] S3, filtering the communication payment signal according to the adaptive step size factor, performing positioning calculation on the filtered communication payment signal, and obtaining the positioning result of the mobile payment device.
[0084] The adaptive filtering algorithm is improved by the adaptive step size factor, and the communication payment signal is used as the input of the improved adaptive filtering algorithm, and the output result is the filtered communication payment signal. The RSSI positioning method is used to calculate the coordinates of the mobile payment device for the filtered communication payment signal. This method uses the change in signal strength to achieve accurate measurement of the distance between the payment mobile terminal and the base station. The triangulation positioning method can accurately locate the position of the mobile terminal in space. The triangulation positioning method in the RSSI positioning method is further used to locate the position of the mobile payment terminal.
[0085] The principle of triangulation positioning is as follows Figure 3 As shown, circles are drawn with the location of base station A as the center and the distance between mobile payment terminal B and the base station as the radius, and the intersection of the three circles is the location of the mobile payment terminal. RSSI and triangulation positioning are known technologies and their specific calculation processes are not described in detail.
[0086] Based on the same inventive concept as the above method, an embodiment of the present application also provides a payment precise positioning matching system based on communication technology, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the methods for payment precise positioning matching based on communication technology are implemented.
[0087] Through the above description of the implementation method in combination with the accompanying drawings, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned 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.
[0088] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
Claims
1. A payment precise positioning matching method based on communication technology, characterized in that: The method comprises the following steps: S1, obtaining a communication payment signal sent by a mobile payment device, segmenting the communication payment signal by mutation points, and obtaining each communication payment subsequence; S2, based on the differences in the numerical distribution and trend changes among all the communication payment subsequences, obtain the adaptive step size factor, which specifically includes: S21, obtaining the fluctuation characteristic coefficient of each communication payment subsequence according to the numerical distribution of elements in each communication payment subsequence; S22, updating the volatility characteristic coefficient according to the difference between the volatility characteristic coefficients of all communication payment subsequences to obtain an updated volatility characteristic coefficient of each communication payment subsequence; S23, obtaining a jitter intensity assessment value according to the trend change of each communication payment subsequence; S24, obtaining a data fluctuation coefficient of the communication payment signal according to the jitter intensity evaluation amount of all communication payment subsequences and the updated fluctuation characteristic coefficient; S25, calculating an adaptive step size factor according to a data fluctuation coefficient of the communication payment signal; S3, filtering the communication payment signal according to the adaptive step size factor; performing positioning calculation on the filtered communication payment signal to obtain a positioning result of the mobile payment device.
2. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 1, characterized in that: The step of obtaining the fluctuation characteristic coefficient of each communication payment subsequence according to the numerical distribution of elements in each communication payment subsequence includes: Obtaining the first-order difference sequence of each communication payment subsequence, and calculating the mean of the first-order difference sequence; obtaining the range of all elements in each communication payment subsequence; The fluctuation characteristic coefficient of each communication payment subsequence is determined according to the range and the mean; the fluctuation characteristic coefficient is a positive fusion of the range and the mean.
3. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 1, characterized in that: The method for obtaining the update fluctuation characteristic coefficient of each communication payment subsequence includes: Calculate the error elimination value based on the differences in the fluctuation characteristic coefficients of all communication payment subsequences; Calculate the absolute value of the difference between the fluctuation characteristic coefficients of any two communication payment subsequences; record the two communication payment subsequences whose absolute value of the difference is less than the error elimination value as the same fluctuation class; calculate the average value of the fluctuation characteristic coefficients of the communication payment subsequences contained in each fluctuation class, and record it as the fluctuation characteristic value of each fluctuation class; The updated fluctuation characteristic coefficient of each communication payment subsequence is the fluctuation characteristic value of the fluctuation class to which each communication payment subsequence belongs.
4. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 3, characterized in that: The process of obtaining the error elimination value includes: Arrange the volatility coefficients of all communication payment subsequences in ascending order to form a volatility coefficient sequence; record the first preset number of elements in the first-order difference sequence of the volatility coefficient sequence as error values; record the error values with the same value as one category to obtain various error categories; and take the average of the error values corresponding to all error categories as the error elimination value.
5. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 1, characterized in that: The jitter intensity evaluation amount is obtained according to the trend change of each communication payment subsequence, including: Record any element in the first-order difference sequence of each communication payment subsequence as a target element, and obtain the numerical sign of the target element; According to the difference in numerical signs between the target element and its previous element, the sign-changed value of the target element is obtained; Obtaining the cumulative sum of the sign change values of all elements contained in the first-order difference sequence, and recording it as the number of sign changes of each communication payment subsequence; Obtain the variance of the first-order difference sequence of each communication payment subsequence; and use the product of the number of sign changes of each communication payment subsequence and the variance as the jitter strength evaluation amount of each communication payment signal subsequence.
6. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 5, characterized in that: The method for obtaining the sign change value of the target element includes: if the target element has the same numerical sign as the previous element, the sign change value of the target element is 0; otherwise, the sign change value of the target element is 1.
7. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 1, characterized in that: The method for obtaining the data fluctuation coefficient of the communication payment signal includes: The forward fusion result of the jitter intensity evaluation amount of each communication payment subsequence and the updated volatility characteristic coefficient is used as the data volatility degree of each communication payment subsequence; The sum of the data fluctuation levels of all communication payment subsequences is taken as the data fluctuation coefficient of the communication payment signal.
8. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 1, characterized in that: The step of calculating the adaptive step size factor according to the data fluctuation coefficient of the communication payment signal specifically includes: The communication payment signal is filtered by an adaptive filtering algorithm to obtain the original step factor; the normalized value of the data fluctuation coefficient of the communication payment signal is calculated and recorded as the modification coefficient; the product of the modification coefficient and the original step factor is used as the adaptive step factor of the communication payment signal.
9. The method for accurate positioning and matching of payment based on communication technology as claimed in claim 1, characterized in that: The communication payment signal is filtered according to the adaptive step size factor; Perform positioning calculation on the filtered communication payment signal to obtain the positioning result of the mobile payment device, including: The adaptive step factor is used to replace the step factor in the adaptive filtering algorithm, and the communication payment signal is filtered to obtain a filtered communication payment signal; The filtered communication payment signal is solved using a positioning algorithm to obtain the coordinates of the mobile payment device.
10. A payment precise positioning matching system based on communication technology, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.