Wireless MR data fingerprint positioning method based on 5G

Abstract

The invention discloses a wireless MR data fingerprint positioning method based on 5G, and relates to the technical field of 5G communication wireless fingerprint positioning, and the method comprises the steps: associating 4G / 5G MR data with signaling data, and backfilling a user identity identifier, and through setting a data fingerprint positioning system, AGPS appointment of 4G wireless MR data and 5G wireless MR data reported in adjacent time points, etc. AGPS data reported by 4G are assigned to 5G wireless MR data, so that the AGPS data of 5G wireless MR are ingeniously obtained, a grid fingerprint database is generated according to wireless index information of the 5G wireless MR data, wireless indexes of other 5G wireless MR data are matched by using the wireless index information in the grid fingerprint database, and the longitude and latitude of the 5G wireless MR data are positioned. The wireless MR data fingerprint data and the corresponding analysis result are managed, visualized and stored, wireless MR data fingerprint positioning management can be achieved through cloud management and control of the Internet of Things, and the intelligent level of wireless MR data fingerprint positioning management is improved.

Description

Technical field:

[0001] The present invention relates to the technical field of 5G communication wireless fingerprint positioning, and specifically to a 5G-based wireless MR data fingerprint positioning method. Background technology:

[0002] With the rapid development of 5G communication technology and the widespread adoption of wireless networks, positioning technology has become a key technology in a variety of wireless applications, particularly in areas such as augmented reality (AR), virtual reality (VR), and mixed reality (MR). Traditional positioning methods, such as those based on the Global Positioning System (GPS), are ineffective indoors or in densely populated urban environments. Therefore, indoor positioning systems have become a key research area in wireless communication technology.

[0003] In indoor positioning technology, methods based on wireless signal fingerprints have been widely researched and applied. Wireless signal fingerprint positioning utilizes the differences in the propagation characteristics of wireless signals (such as Wi-Fi, Bluetooth, and Zigbee) at different locations to build a fingerprint database. Location is then estimated by matching the real-time signal characteristics received with the fingerprint database. However, traditional wireless fingerprint positioning methods often lack the required accuracy in complex environments, such as those affected by multipath effects, signal attenuation, and significant environmental fluctuations.

[0004] In recent years, the introduction of 5G communication technology has brought new opportunities to wireless positioning technology. 5G networks offer advantages such as high bandwidth, low latency, and high-density connectivity, significantly improving the performance of positioning systems. However, the complex signal propagation characteristics of 5G networks and the integration of multiple wireless access technologies present new challenges to traditional positioning methods based on a single technology.

[0005] Conventional 4G fingerprint positioning relies on AGPS information in MR data to build a fingerprint database. However, 5G MR data no longer reports AGPS, rendering existing methods ineffective. Existing alternatives, such as base station triangulation, lack accuracy (error > 100 meters), while deploying dedicated positioning base stations is expensive. A low-cost, high-precision 5G MR positioning solution is urgently needed. Therefore, this paper proposes a 5G-based wireless MR data fingerprint positioning method to address these issues. Summary of the invention: The purpose of the present invention is to provide a 5G-based wireless MR data fingerprint positioning method to solve the above problems, thereby solving the problems mentioned in the background technology.

[0006] In order to solve the above problems, the present invention provides a technical solution: A 5G-based wireless MR data fingerprint positioning method includes the following specific steps: S1. Associate 4G / 5G MR data with signaling data and backfill user identity; S2: Filter out trajectory points with speeds > 10 m / s in 4G MR, retain low-speed data containing AGPS, and migrate the AGPS data of 4G MR to the 5G MR within the ±10s time window of the same user. S3: Build a geographic grid fingerprint library based on 5G MR with AGPS and calculate the weighted mean of wireless indicators within the grid; S4. Match the 5G MR without AGPS with the grid fingerprint, and output the positioning coordinates by weighting the inverse of the difference value.

[0007] As a preferred embodiment of the present invention, step S1 includes the following specific steps: S101, first use 4G MR data as the main table and 4G signaling data as the secondary table; S102, generating a quadruple for association, wherein the quadruple is endbid, mmecode, mmes1apid, and mmegroupid; S103: Backfill user information such as IMSI, MDN, and IMEI into the 4G wireless MR data. Similarly, backfill user information into the 5G wireless MR data. This allows accurate positioning of a single user's signaling session at a specific time point, similar to a joint primary key in a database.

[0008] As a preferred embodiment of the present invention, step S2 includes the following specific steps: S201. 2%-5% of 4G wireless MR data reports AGP data. Since the MR data reporting cycle is 10 seconds, to ensure that the time and location errors are less than 100 meters, the user's movement speed needs to be limited to within 10 meters / second to obtain more accurate time and space information of the user. The speed threshold can be adjusted according to the required accuracy. S202: According to the above principles, the user trajectory points of high-speed movement are filtered, and only the 4G wireless MR data of the user trajectory points of low-speed movement are retained.

[0009] As a preferred embodiment of the present invention, step S3 includes the following specific steps: S301: If the same user reports 4G and 5G data at the same time or adjacent to each other, and if the 4G reports AGPS data, then the latitude and longitude of the 5G wireless MR data reported by the user at the same or adjacent time is equal to the AGPS data reported by the 4G wireless MR; S302, according to the above principle, taking 5G wireless MR data as the main table and 4G wireless MR data as the auxiliary table, associating through the datetime and imsi binary tuple, backfilling the AGPS data into the 5G wireless MR data, and thus obtaining the 5G wireless MR fingerprint data.

[0010] As a preferred embodiment of the present application, the step S4 comprises the following specific steps: S401, calculating the grid where the 5G wireless MR data with backfilled AGPS data is located, and calculating the grid where the MR data with known longitude and latitude is located; S402, there are multiple 5G wireless MR data in the same grid, if there are three or more, the three 5G wireless MR data closest to the center point of the grid are selected as the input data for fingerprint library calculation, and if there are less than three, no filtering is performed; S403, calculating the weighted average of the Ta, rsrp, rsrq, sinr and aoa infinite indicators of the 5G wireless MR data after screening under each 5G base station, and using the reciprocal of the distance of the MR from the center point of the grid as the weighted value, the closer to the center point, the more representative of the wireless indicator value of the grid, and according to this method, the wireless indicator values of the grids covered by all base stations are calculated, which are used as the matching data, the 5G wireless MR data without AGPS data is matched with the wireless indicators of the grids covered by each base station calculated above, the first three grids that best match the MR wireless indicators are matched out, the weighted average is calculated according to the grid center longitude and latitude, and the weighted value is the reciprocal of the wireless indicator matching difference value, the closer the MR wireless indicator to the grid wireless indicator, the more likely the MR is in the grid, and the longitude and latitude information of the MR is calculated according to this method.

[0011] As a preferred embodiment of the present application, the data fingerprint positioning system generated before the user association in step S1 comprises a user association module, a data filtering module, an AGPS association module and a fingerprint library generation port, the output end of the user association module is in communication connection with the input end of the data filtering module, the output end of the data filtering module is in communication connection with the input end of the AGPS association module, and the output end of the AGPS association module is in communication connection with the input end of the fingerprint library generation port.

[0012] As a preferred embodiment of the present application, the user association module comprises a user association unit, a four-tuple generation unit and a data backfilling unit, the output end of the four-tuple generation unit is in communication connection with the input end of the data backfilling unit, and the output end of the data backfilling unit is in communication connection with the input end of the user association unit. The user association unit is used for taking the MR data of 4G as a main table, taking the signaling data of 4G as a secondary table, associating the 4G / 5G MR data with the signaling data, and backfilling the user identity identification; The four-tuple generation unit is used for generating four-tuples for association, and the four-tuples are endbid, mmecode, mmes1apid and mmegroupid. The endbid is a 4G base station identification, which is used for identifying the 4G base station currently connected by the user. The mmecode is a mobile management entity code, which is used for identifying the core network equipment MME for managing the mobility of the user. The mmes1apid is an S1 interface application protocol identification, which is used for uniquely identifying the control plane connection of the user equipment between the MME and the base station. The mmegroupid is a mobile management entity group identification, which is used for identifying the logical group of the MME and is used for cross-MME addressing. The data backfilling unit is used for backfilling the user information such as imsi, mdn and imei into the 4G wireless MR data, and the user information of the 5G wireless MR data is backfilled in the same way, so that the signaling session of a single user can be accurately positioned at a specific time point, which is similar to the joint primary key of the database.

[0013] As a preferred embodiment of the application, the data filtering module comprises a data filtering unit and a threshold preset adjustment unit, and the output end of the threshold preset adjustment unit is in communication connection with the input end of the data filtering unit. The data filtering unit is used for reporting the agps data on 2%-5% of the data in the 4G wireless MR data, filtering the user trajectory points of high-speed motion, and only retaining the user trajectory points of low-speed motion in the 4G wireless MR data. The threshold preset adjustment unit is used for adjusting the speed threshold according to the different required accuracy when the user obtains more accurate space-time information.

[0014] As a preferred embodiment of the application, the AGPS association module comprises an AGPS association unit and a two-tuple generation unit, The AGPS association unit is used for associating the two-tuple and backfilling the AGPS data into the 5G wireless MR data, so as to obtain the 5G wireless MR fingerprint data. The two-tuple generation unit is used for generating datetime and imsi two-tuples.

[0015] As a preferred embodiment of the present invention, the fingerprint library generation port includes a visual operation port, a fingerprint library data center and a fingerprint library generation module, the output end of the fingerprint library generation module is communicatively connected to the input end of the fingerprint library data center, and the visual operation port is bidirectionally communicatively connected to the fingerprint library data center; The visual operation port is used to facilitate interaction between users and the system, providing an intuitive interface for users to operate, view positioning results, and monitor system status. Positioning data is presented through a graphical interface, which may be presented in the form of maps, heat maps, 3D models, or other visual forms to help users understand positioning accuracy and results; The fingerprint database data center is used to store and manage fingerprint data. Fingerprint data is a set of location features established by measuring wireless signals multiple times. It provides query and analysis functions based on historical fingerprint data, such as analyzing signal change trends and positioning accuracy in certain areas, to optimize positioning algorithms and improve system performance. The fingerprint library generation module is used to collect, process and store a large amount of wireless signal data, thereby creating a comprehensive and accurate fingerprint library for subsequent positioning matching and accuracy optimization.

[0016] The beneficial effects of the present invention are as follows: by setting up a data fingerprint positioning system, the present invention associates 4G / 5G MR data with signaling data, backfills the user identity, filters the trajectory points with a speed greater than 10m / s in the 4G MR, retains the low-speed data containing AGPS, and migrates the AGPS data of the 4G MR to the 5G MR with a ±10s time window of the same user. At the same time, a geographic grid fingerprint library is constructed based on the 5G MR with AGPS, and the weighted average of the wireless indicators in the grid is calculated to match the 5G MR without AGPS. MR and grid fingerprints are weighted by the inverse of the difference value to output positioning coordinates. This solution mainly utilizes the approximate AGPS of 4G wireless MR data and 5G wireless MR data reported by the same user at adjacent time points during low-speed movement. This part of the AGPS data reported by 4G is assigned to the 5G wireless MR data, thereby cleverly obtaining the AGPS data of 5G wireless MR. A grid fingerprint library is generated based on the wireless indicator information of this part of 5G wireless MR data. The wireless indicator information in the grid fingerprint library is used to match the wireless indicators of other 5G wireless MR data to locate its longitude and latitude. The wireless MR data fingerprint data and corresponding analysis results are managed, visualized, and stored, which helps to realize wireless MR data fingerprint positioning management through IoT cloud management and control, and improve the intelligence level of wireless MR data fingerprint positioning management. Description of the drawings: For ease of explanation, the present invention is described in detail with reference to the following specific implementations and accompanying drawings.

[0017] Figure 1This is an overall flow chart of a 5G-based wireless MR data fingerprint positioning method of the present invention; Figure 2 This is a schematic diagram of 5G wireless MR fingerprint data of a 5G-based wireless MR data fingerprint positioning method of the present invention; Figure 3 This is a schematic diagram of a grid where MR data with known longitude and latitude are located in a 5G-based wireless MR data fingerprint positioning method of the present invention; Figure 4 It is a wireless index value data graph of the grid covered by the base station of the 5G-based wireless MR data fingerprint positioning method of the present invention; Figure 5 This is a MR latitude and longitude information data diagram of a 5G-based wireless MR data fingerprint positioning method of the present invention. Specific implementation method: like Figure 1-Figure 5 As shown, this specific embodiment adopts the following technical solutions: A 5G-based wireless MR data fingerprint positioning method includes the following specific steps: S1. Associate 4G / 5G MR data with signaling data and backfill user identity; S2: Filter out trajectory points with speeds > 10 m / s in 4G MR, retain low-speed data containing AGPS, and migrate the AGPS data of 4G MR to the 5G MR within the ±10s time window of the same user. S3: Build a geographic grid fingerprint library based on 5G MR with AGPS and calculate the weighted mean of wireless indicators within the grid; S4. Match the 5G MR without AGPS with the grid fingerprint, and output the positioning coordinates by weighting the inverse of the difference value.

[0018] As a preferred embodiment of the present invention, step S1 includes the following specific steps: S101, first use 4G MR data as the main table and 4G signaling data as the secondary table; S102, generating a quadruple for association, wherein the quadruple is endbid, mmecode, mmes1apid, and mmegroupid; S103: Backfill user information such as IMSI, MDN, and IMEI into the 4G wireless MR data. Similarly, backfill user information into the 5G wireless MR data. This allows accurate positioning of a single user's signaling session at a specific time point, similar to a joint primary key in a database.

[0019] As a preferred embodiment of the present invention, step S2 includes the following specific steps: S201, 2%-5% of the data in the 4G wireless MR data reports agps data, because the MR data reporting period is 10S, in order to guarantee that the time and position error is less than 100M, the user's moving speed needs to be limited within 10m / s, so as to obtain the user's relatively accurate space-time information, according to the different required accuracy, the speed threshold can be adjusted; S202, according to the above principle, the trajectory points of the high-speed moving user are filtered, and only the trajectory points of the low-speed moving user 4G wireless MR data are reserved.

[0020] As a preferred embodiment of the application, the step S3 comprises the following specific steps: S301, the same user reports 4G and 5G data at the same time or adjacent time, if 4G reports AGPS data, then the longitude and latitude of the 5G wireless MR data reported by the user in the same or adjacent time is equal to the AGPS data reported by the 4G wireless MR; S302, according to the above principle, taking the 5G wireless MR data as the main table and the 4G wireless MR data as the secondary table, the AGPS data is backfilled into the 5G wireless MR data through the datetime and imsi binary tuple, so as to obtain the 5G wireless MR fingerprint data.

[0021] As a preferred embodiment of the application, the step S4 comprises the following specific steps: S401, according to the 5G wireless MR data with backfilled AGPS data, the grid where the data is located is calculated, and the grid where the MR data with known longitude and latitude is located is calculated; S402, there are multiple 5G wireless MR data in the same grid, if there are three or more, the three 5G wireless MR data closest to the center point of the grid are selected as the input data for fingerprint library calculation, and if there are less than three, no filtering is performed; S403, according to the filtered 5G wireless MR data, the weighted average of the Ta, rsrp, rsrq, sinr and aoa infinite indicators of these MR data under each 5G base station is calculated, the weighted value uses the reciprocal of the distance of the MR from the center point of the grid, the closer to the center point, the more it represents the wireless indicator value of the grid, according to this method, the wireless indicator values of the grids covered by all base stations are calculated, which are used as matching data, the 5G wireless MR data without agps data is matched with the wireless indicators of the grids covered by each base station calculated above, the first three grids that best match the MR wireless indicators are matched out, the weighted average is calculated according to the grid center longitude and latitude, the weighted value is the reciprocal of the wireless indicator matching difference value, the closer the MR wireless indicator to the grid wireless indicator, the more likely the MR is in the grid, and the MR's longitude and latitude information is calculated according to this method.

[0022] Further, the data fingerprint positioning system before the user association in step S1 is generated, the data fingerprint positioning system includes a user association module, a data filtering module, an AGPS association module and a fingerprint library generation port, the output end of the user association module is in communication connection with the input end of the data filtering module, the output end of the data filtering module is in communication connection with the input end of the AGPS association module, and the output end of the AGPS association module is in communication connection with the input end of the fingerprint library generation port.

[0023] Further, the user association module includes a user association unit, a four tuple generation unit and a data backfill unit, the output end of the four tuple generation unit is in communication connection with the input end of the data backfill unit, and the output end of the data backfill unit is in communication connection with the input end of the user association unit; the user association unit is used for taking the 4G MR data as a main table, the 4G signaling data as a secondary table, backfilling the user identity by associating the 4G / 5G MR data and the signaling data; the four tuple generation unit is used for generating a four tuple for association, and the four tuple is endbid, mmecode, mmes1apid and mmegroupid; endbid is a 4G base station identifier, used for identifying the 4G base station currently connected by the user; mmecode is a mobile management entity code, used for identifying the core network equipment MME for managing the mobility of the user; mmes1apid is an S1 interface application protocol identifier, used for uniquely identifying the control plane connection of the user equipment between the MME and the base station; mmegroupid is a mobile management entity group identifier, used for identifying the logical group of the MME, and used for cross-MME addressing; The data backfill unit is used for backfilling the user imsi, mdn, imei and other user information into the 4G wireless MR data, and the user information of the 5G wireless MR data is backfilled in the same way, so that the signaling session of a single user can be accurately positioned at a specific time point, which is similar to the joint primary key of the database; imsi is a core association key, used for realizing the space-time alignment of the 4G / 5G MR data of the same user; mdn is a device fingerprint, used for excluding the interference of the user changing the SIM card; imei is a business outlet, used for converting the latitude and longitude of the positioning result into operable business data.

[0024] Furthermore, the data filtering module includes a data filtering unit and a threshold preset adjustment unit. The data filtering unit is used to filter out high-speed moving user trajectory points when 2%-5% of the data in the 4G wireless MR data reports AGPs data, and only retain the 4G wireless MR data of low-speed moving user trajectory points; the threshold preset adjustment unit is used when the user obtains more accurate spatiotemporal information, and its speed threshold can be adjusted according to the required accuracy.

[0025] Furthermore, the AGPS association module includes an AGPS association unit and a tuple generation unit. The AGPS association unit is used to associate the tuple and backfill the AGPS data into the 5G wireless MR data to obtain the 5G wireless MR fingerprint data. The tuple generation unit is used to generate the datetime and imsi tuples. datetime is a timestamp used to ensure that 4G AGPS and 5G MR data are aligned on the physical time axis.

[0026] As a preferred embodiment of the present invention, the fingerprint library generation port includes a visualization operation port, a fingerprint library data center and a fingerprint library generation module. The output end of the fingerprint library generation module is communicatively connected to the input end of the fingerprint library data center, and the visualization operation port is bidirectionally communicatively connected to the fingerprint library data center; the visualization operation port is used to provide interaction between the user and the system, providing an intuitive interface for the user to operate, view positioning results and monitor the system status; the positioning data is presented through a graphical interface, which may be presented in the form of a map, heat map, 3D model or other visual form to help the user understand the positioning accuracy and effect; the fingerprint library data center is used to store and manage fingerprint data, which is a location feature set established by multiple measurements of wireless signals, and provides query and analysis functions based on historical fingerprint data, such as analyzing signal change trends and positioning accuracy in certain areas, so as to optimize the positioning algorithm and improve system performance; the fingerprint library generation module is used to collect, process and store a large amount of wireless signal data, thereby creating a comprehensive and accurate fingerprint library for subsequent positioning matching and accuracy optimization. When the fingerprint library is constructed: The grid size is 10m×10m; When there are ≥3 data items in the same grid, only the 3 items closest to the center are selected.

[0027] Specifically: In actual applications, there are multiple fingerprint library generation ports, which are respectively used in conjunction with the user association module, the data filtering module, and the AGPS association module. The multiple fingerprint library generation ports are located in different geographical locations. The present invention sets a data fingerprint positioning system. When in use, it associates 4G / 5G MR data with signaling data, backfills the user identity, filters the trajectory points with a speed of >10m / s in the 4G MR, retains the low-speed data containing AGPS, and migrates the AGPS data of the 4G MR to the 5G MR with the same user ±10s time window. At the same time, a geographic grid fingerprint library is constructed based on the 5G MR with AGPS, and the weighted average of the wireless indicators in the grid is calculated to match the 5G without AGPS. MR and grid fingerprints are weighted by the inverse of the difference value to output positioning coordinates. This solution mainly utilizes the approximate AGPS of 4G wireless MR data and 5G wireless MR data reported by the same user at adjacent time points during low-speed movement. This part of the AGPS data reported by 4G is assigned to the 5G wireless MR data, thereby cleverly obtaining the AGPS data of 5G wireless MR. A grid fingerprint library is generated based on the wireless indicator information of this part of 5G wireless MR data. The wireless indicator information in the grid fingerprint library is used to match the wireless indicators of other 5G wireless MR data to locate its longitude and latitude. The wireless MR data fingerprint data and corresponding analysis results are managed, visualized, and stored, which helps to realize wireless MR data fingerprint positioning management through IoT cloud management and control, and improve the intelligence level of wireless MR data fingerprint positioning management.

[0028] Those skilled in the art will appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0029] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices, equipment and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0030] In the several embodiments provided in this application, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or units can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or equipment, which can be electrical, mechanical or other forms.

[0031] The modules serving as user association, data filtering, AGPS association, and fingerprint library generation ports may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the objectives of this embodiment.

[0032] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0033] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program instructions, such as a USB flash drive, a mobile hard disk, a read-only storage server, a random access storage server, a magnetic disk, or an optical disk.

[0034] In addition, it should be noted that the combination of the various technical features in this case is not limited to the combination described in the claims of this case or the combination described in the specific embodiments. All technical features recorded in this case can be freely combined or combined in any way unless there is a contradiction between them.

[0035] It should be noted that the above examples are merely specific embodiments of the present invention. Obviously, the present invention is not limited to the above examples, and many similar variations are possible. All variations directly derived from or associating with the present invention by those skilled in the art are intended to fall within the scope of protection of the present invention.

[0036] The above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A 5G-based wireless MR data fingerprint positioning method, characterized in that: The specific steps include: S1. Associate 4G / 5G MR data with signaling data and backfill user identity; S2: Filter out trajectory points with speeds > 10 m / s in 4G MR, retain low-speed data containing AGPS, and migrate the AGPS data of 4G MR to the 5G MR within the ±10s time window of the same user. S3: Build a geographic grid fingerprint library based on 5G MR with AGPS and calculate the weighted mean of wireless indicators within the grid; S4. Match the 5G MR without AGPS with the grid fingerprint, and output the positioning coordinates by weighting the inverse of the difference value.

2. The 5G-based wireless MR data fingerprint positioning method according to claim 1, characterized in that: The step S1 includes the following specific steps: S101, first use 4G MR data as the main table and 4G signaling data as the secondary table; S102, generating a quadruple for association, wherein the quadruple is endbid, mmecode, mmes1apid, and mmegroupid; S103: Backfill user information such as IMSI, MDN, and IMEI into the 4G wireless MR data. Similarly, backfill user information into the 5G wireless MR data. This allows accurate positioning of a single user's signaling session at a specific time point, similar to a joint primary key in a database.

3. The 5G-based wireless MR data fingerprint positioning method according to claim 1, characterized in that: The step S2 includes the following specific steps: S201. 2%-5% of 4G wireless MR data reports AGP data. Since the MR data reporting cycle is 10 seconds, to ensure that the time and location errors are less than 100 meters, the user's movement speed needs to be limited to within 10 meters / second to obtain more accurate time and space information of the user. The speed threshold can be adjusted according to the required accuracy. S202: According to the above principles, the user trajectory points of high-speed movement are filtered, and only the 4G wireless MR data of the user trajectory points of low-speed movement are retained.

4. The 5G-based wireless MR data fingerprint positioning method according to claim 3, characterized in that: The step S3 includes the following specific steps: S301: If the same user reports 4G and 5G data at the same time or adjacent to each other, and if the 4G reports AGPS data, then the latitude and longitude of the 5G wireless MR data reported by the user at the same or adjacent time is equal to the AGPS data reported by the 4G wireless MR; S302. Based on the above principles, 5G wireless MR data is used as the main table and 4G wireless MR data as the secondary table. The data is associated with each other through the datetime and imsi tuples, and the AGPS data is backfilled into the 5G wireless MR data to obtain the 5G wireless MR fingerprint data.

5. The 5G-based wireless MR data fingerprint positioning method according to claim 1, characterized in that: The step S4 includes the following specific steps: S401, calculating the grid where the 5G wireless MR data is located based on the backfilled AGPS data, and calculating the grid where the MR data with known longitude and latitude are located; S402: If there are multiple 5G wireless MR data in the same grid, and there are three or more of them, the three 5G wireless MR data closest to the center of the grid are selected as the input data for fingerprint library calculation; if there are less than three, no filtering is performed; S403. Calculate the weighted average of the Ta, rsrp, rsrq, sinr, and aoa indicators of the filtered 5G wireless MR data at each 5G base station. The weighted value uses the inverse of the distance of the MR from the center point of the grid. The closer to the center point, the more representative the wireless indicator value of the grid. Based on this method, calculate the wireless indicator values ​​of all grids covered by base stations as the data to be matched.

6. The 5G-based wireless MR data fingerprint positioning method according to claim 5, characterized in that: The data fingerprint positioning system is generated before user association in step S1. The data fingerprint positioning system includes a user association module, a data filtering module, an AGPS association module and a fingerprint library generation port. The output end of the user association module is communicatively connected to the input end of the data filtering module, the output end of the data filtering module is communicatively connected to the input end of the AGPS association module, and the output end of the AGPS association module is communicatively connected to the input end of the fingerprint library generation port.

7. The 5G-based wireless MR data fingerprint positioning method according to claim 6, characterized in that: The user association module includes a user association unit, a four-tuple generation unit and a data backfill unit, wherein the output end of the four-tuple generation unit is communicatively connected to the input end of the data backfill unit, and the output end of the data backfill unit is communicatively connected to the input end of the user association unit; The user association unit is used to use 4G MR data as the main table and 4G signaling data as the secondary table, and backfill the user identity by associating 4G / 5G MR data with signaling data; The quadruple generation unit is used to generate a quadruple for association, wherein the quadruple is endbid, mmecode, mmes1apid, and mmegroupid; The data backfill unit is used to backfill user information such as user imsi, mdn, imei into 4G wireless MR data, and similarly backfill user information of 5G wireless MR data.

8. The 5G-based wireless MR data fingerprint positioning method according to claim 6, characterized in that: The data filtering module includes a data filtering unit and a threshold preset adjustment unit, wherein the output end of the threshold preset adjustment unit is communicatively connected to the input end of the data filtering unit; The data filtering unit is used to filter out high-speed moving user trajectory points, in which 2%-5% of the data in the 4G wireless MR data is reported as AGPs data; The threshold preset adjustment unit is used when the user obtains more accurate spatiotemporal information, and its speed threshold can be adjusted according to different required accuracy.

9. The 5G-based wireless MR data fingerprint positioning method according to claim 6, characterized in that: The AGPS association module includes an AGPS association unit and a two-tuple generation unit, wherein the output end of the two-tuple generation unit is communicatively connected to the input end of the AGPS association unit; The AGPS association unit is used to associate the tuples and backfill the AGPS data into the 5G wireless MR data; The two-tuple generating unit is used to generate the datetime and imsi two-tuples.

10. The 5G-based wireless MR data fingerprint positioning method according to claim 6, characterized in that: The fingerprint database generation port includes a visual operation port, a fingerprint database data center and a fingerprint database generation module, the output end of the fingerprint database generation module is communicatively connected to the input end of the fingerprint database data center, and the visual operation port is bidirectionally communicatively connected to the fingerprint database data center; The visual operation port is used to provide interaction between the user and the system, providing an intuitive interface for the user to operate, view positioning results and monitor the system status through a graphical interface to present positioning data; The fingerprint database data center is used to store and manage fingerprint data. Fingerprint data is a location feature set established by measuring wireless signals multiple times, and provides query and analysis functions based on historical fingerprint data. The fingerprint library generation module is used to collect, process and store a large amount of wireless signal data, thereby creating a comprehensive and accurate fingerprint library.

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