Terminal positioning method and device, equipment, storage medium and program product

Abstract

The invention discloses a terminal positioning method and device, equipment, a storage medium and a program product, and the specific technical scheme comprises the steps: obtaining terminal positioning data, the terminal positioning data comprising a plurality of measurement report data corresponding to a terminal; the distance between the fingerprint data in a preset fingerprint database and the terminal positioning data is calculated by means of the multiple feature data of the fingerprint data in the preset fingerprint database and the multiple measurement report data corresponding to the terminal, and the fingerprint data in the preset fingerprint database is used for representing the corresponding relation between the terminal position information and the measurement report data; obtaining a preset number of fingerprint data with the minimum distance according to the distance; and calculating terminal position information corresponding to the terminal positioning data based on a preset algorithm and the preset number of fingerprint data. In this way, the terminal position information is obtained through calculation of the multiple pieces of feature data, and the accuracy of terminal positioning can be improved.

Description

Technical Field

[0001] The present application belongs to the field of wireless technology, and in particular, relates to a method, device, equipment, storage medium and program product for terminal positioning. Background Art

[0002] With the popularization of technologies such as big data, cloud computing, and artificial intelligence, among many Internet big data applications, more and more applications need to determine the location of the terminal and provide corresponding services to users based on the terminal location information.

[0003] At present, when determining the location of a terminal, the electronic device matches the measurement report without longitude and latitude information returned by the terminal in a pre-built fingerprint library, and determines the location of the terminal according to the location information corresponding to the matched fingerprint. Among them, the fingerprint library is a reference signal receiving power (RSRP) fingerprint library pre-built by the application server using the measurement report data with longitude and latitude information. In this way, using the RSRP fingerprint library to locate the terminal has the problem of insufficient positioning accuracy. Summary of the invention

[0004] The embodiments of the present application provide a terminal positioning method, device, equipment, storage medium and program product, which can improve the accuracy of terminal positioning.

[0005] In a first aspect, an embodiment of the present application provides a method for locating a terminal, including:

[0006] Acquire terminal positioning data, where the terminal positioning data includes a plurality of measurement report data corresponding to the terminal;

[0007] Calculate the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data by using multiple feature data of the fingerprint data in the preset fingerprint library and multiple measurement report data corresponding to the terminal, wherein the fingerprint data in the preset fingerprint library is used to represent the corresponding relationship between the terminal location information and the measurement report data;

[0008] According to the size of the distance, a preset number of fingerprint data with the smallest distance is obtained;

[0009] Based on a preset algorithm and the preset number of fingerprint data, the terminal location information corresponding to the terminal positioning data is calculated.

[0010] In a possible implementation, each feature data corresponds to a preset weight; and the calculating the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data includes:

[0011] For each fingerprint data, calculating the target distance between each feature data and the corresponding measurement report data in the terminal positioning data;

[0012] Calculating the product of the target distance and the preset weight corresponding to the feature data to obtain a first product;

[0013] The sum of the first products corresponding to each feature data is calculated to obtain the distance.

[0014] In a possible implementation, the calculating the terminal location information corresponding to the terminal positioning data based on a preset algorithm and the preset number of fingerprint data includes:

[0015] The terminal location information is calculated according to the following formula:

[0016]

[0017] Among them, U lon Indicates the longitude information in the terminal location information, d i represents the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the longitude information corresponding to the i-th feature data;

[0018]

[0019] Among them, U lat Indicates the latitude information in the terminal location information, d i represents the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the latitude information corresponding to the i-th feature data.

[0020] In a possible implementation, the calculating the terminal location information corresponding to the terminal positioning data based on a preset algorithm and the preset number of fingerprint data includes:

[0021] Obtaining a preset number of position information corresponding to the preset number of fingerprint data;

[0022] Calculate the average of the preset number of location information to obtain the terminal location information.

[0023] In a possible implementation manner, after acquiring the terminal location data, the method further includes:

[0024] Determining the format information of the terminal positioning data;

[0025] Determine a first preset fingerprint library corresponding to the terminal positioning data according to a preset correspondence between the standard information and the preset fingerprint library;

[0026] Determining whether the amount of fingerprint data in the first preset fingerprint library is greater than a first preset threshold;

[0027] When the number of fingerprint data in the first preset fingerprint library is greater than the first preset threshold, calculating the distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data;

[0028] When the number of fingerprint data in the first preset fingerprint library is less than or equal to the first preset threshold, and when the number of fingerprint data in the second preset fingerprint library is greater than the second preset threshold, calculate a first distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data, and calculate a second distance between the fingerprint data in the second preset fingerprint library and the terminal positioning data;

[0029] According to the size of the first distance, a first preset number of fingerprint data with the smallest first distance is obtained;

[0030] According to the size of the second distance, a second preset number of fingerprint data with the smallest second distance is obtained;

[0031] Calculate the first terminal location information corresponding to the terminal positioning data based on the preset algorithm and the first preset number of fingerprint data;

[0032] Calculate the second terminal location information corresponding to the terminal positioning data based on the preset algorithm and the second preset number of fingerprint data;

[0033] Calculate the average of the first terminal location information and the second terminal location information to obtain the terminal location information.

[0034] In a possible implementation manner, the calculating a second distance between the fingerprint data in the second preset fingerprint library and the terminal positioning data includes:

[0035] Determine the target fingerprint data in the second preset fingerprint library according to the same coverage correspondence relationship between the fingerprint data in the first preset fingerprint library and the fingerprint data in the second preset fingerprint library;

[0036] The second distance is calculated according to the target fingerprint data.

[0037] In a possible implementation manner, before calculating the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data, the method further includes:

[0038] Acquire historical positioning data of each terminal in different cells, the historical positioning data including terminal identification, cell identification, characteristic data of the terminal and location information of the terminal;

[0039] For the same cell identifier, the historical positioning data is aggregated using the location information of the terminal to obtain a data set corresponding to each cell;

[0040] For each terminal corresponding to each terminal identifier in each data set, calculate the mean of the location information of each terminal in the data set to obtain the location information corresponding to the terminal;

[0041] For each terminal corresponding to each terminal identifier in each data set, calculate the mean of the feature data of each terminal in the data set to obtain the feature data corresponding to the terminal;

[0042] The terminal identifier, the cell identifier, the location information corresponding to the terminal, and the feature data corresponding to the terminal are used as a fingerprint data to construct the preset fingerprint library.

[0043] In a second aspect, an embodiment of the present application provides a terminal positioning device, including:

[0044] An acquisition module, used to acquire functional description information of the component from the knowledge graph corresponding to the component, wherein the functional description information is used to represent the function of the component;

[0045] An extraction module, used to extract keywords corresponding to the component from the functional description information corresponding to the component;

[0046] A calculation module, used for calculating the text similarity between the component to be replaced and the component using the keyword for each component;

[0047] A determination module, used for selecting components whose text similarity is greater than a preset threshold as candidate components;

[0048] The determination module is further configured to determine a replacement component for the component to be replaced based on the candidate component.

[0049] In a third aspect, an embodiment of the present application provides an electronic device, the device comprising: a processor and a memory storing computer program instructions;

[0050] When the processor executes the computer program instructions, the method for terminal positioning as described in any one of the first aspects is implemented.

[0051] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the terminal positioning method as described in any one of the first aspects is implemented.

[0052] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the terminal positioning method as described in any one of the first aspects.

[0053] A terminal positioning method, device, equipment, storage medium and program product of an embodiment of the present application, the preset fingerprint library includes fingerprint data, and the fingerprint data is used to represent the correspondence between the terminal location information and the measurement report data. Based on this, after obtaining the terminal positioning data, the fingerprint data corresponding to the measurement report data in the terminal positioning data is searched in the preset database, and then the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data is calculated. Among them, the fingerprint data includes multiple feature data, so the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data can be calculated based on each feature data. Then, according to the size of the distance, the preset number of fingerprint data with the smallest distance is selected, and the above-mentioned preset number of fingerprint data information and the terminal location information are closest. In this way, the terminal location information corresponding to the terminal can be calculated by using the preset algorithm and the preset number of fingerprint data. Thereby, the accuracy of the calculation result is improved, and the terminal positioning accuracy is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0055] Figure 1 It is a flowchart of a terminal positioning method provided in an embodiment of the present application;

[0056] Figure 2 It is a flow chart of a method for constructing a preset fingerprint library provided in an embodiment of the present application;

[0057] Figure 3 is a flowchart of a joint positioning and calibration method provided in an embodiment of the present application;

[0058] Figure 4 is an exemplary schematic diagram of a terminal positioning method provided in an embodiment of the present application;

[0059] Figure 5 is a structural schematic diagram of a terminal positioning device provided in an embodiment of the present application;

[0060] Figure 6 It is a structural schematic diagram of an electronic device provided in yet another embodiment of the present application. DETAILED DESCRIPTION

[0061] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0062] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0063] Currently, there are two ways to determine the terminal location information:

[0064] The first method is to obtain the distance and azimuth information between the terminal and the base station in the measurement report data according to the measurement report data returned by the terminal, and calculate the position of the terminal with the base station as a reference point.

[0065] However, due to the reflection and refraction during signal propagation and the influence of the distance dimension, the calculated terminal position accuracy is insufficient.

[0066] The second method is to build an RSRP fingerprint library in advance using measurement report data with longitude and latitude information. After receiving the measurement report data without longitude and latitude information returned by the terminal, the corresponding fingerprint is matched in the RSRP fingerprint library according to the RSRP in the measurement report, and the longitude and latitude information of the matched fingerprint is used as the longitude and latitude information of the terminal.

[0067] However, in the second method, the positioning accuracy is insufficient due to the use of fewer positioning data sources and the use of only RSRP data as the feature data for positioning. In addition, there is currently no suitable positioning algorithm for 5G application scenarios. In addition, for the joint positioning scenario of 4G and 5G, there is currently no method for jointly positioning the terminal by integrating the two positioning scenarios of 4G and 5G.

[0068] In order to solve the problems existing in the prior art, the embodiments of the present application provide a method, apparatus, device, storage medium and program product for terminal positioning. Figure 1 A terminal positioning method provided in an embodiment of the present application is introduced, and the method is applied to electronic devices, such as Figure 1 As shown, the method includes:

[0069] S101. Obtain terminal positioning data.

[0070] The terminal positioning data includes a plurality of measurement report data corresponding to the terminal.

[0071] It should be noted that the electronic device can obtain the measurement report data of the terminal from the third-party platform, and obtain the measurement report data of the same category from the obtained terminal measurement report data according to the category of the feature data in the preset fingerprint library.

[0072] For example, the measurement report data stored in the third-party platform includes occupied cell information, signal strength information, signal quality information, signal delay information, antenna arrival angle information, and longitude and latitude information, etc. The fingerprint data in the preset fingerprint library includes feature data categories of signal quality information, signal strength information, and occupied cell information. The electronic device then obtains data corresponding to the signal quality information, data corresponding to the signal strength information, and data corresponding to the occupied cell information from the third-party platform.

[0073] S102: Calculate the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data by using multiple feature data of the fingerprint data in the preset fingerprint library and multiple measurement report data corresponding to the terminal.

[0074] The fingerprint data in the preset fingerprint library is used to represent the corresponding relationship between the terminal location information and the measurement report data.

[0075] Specifically, the fingerprint data includes terminal location information, terminal identification, cell identification, and multiple measurement report data, and the measurement report data in the terminal positioning data and the feature data in the fingerprint data are of the same category. The electronic device determines the feature data in the preset fingerprint library that is most similar to the terminal positioning data by calculating the distance, and based on the terminal location information of the most similar feature data, the terminal location information corresponding to the terminal positioning data can be determined. The electronic device can calculate the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data by calculating the Euclidean distance.

[0076] S103: According to the distance, a preset number of fingerprint data with the shortest distance is obtained.

[0077] The distance is used to characterize the similarity between the fingerprint data and the terminal positioning data. The smaller the distance, the more similar the fingerprint data and the terminal positioning data are, and the closer the terminal location information in the fingerprint data is to the terminal location information corresponding to the terminal positioning data.

[0078] S104: Calculate the terminal location information corresponding to the terminal positioning data based on a preset algorithm and a preset amount of fingerprint data.

[0079] Using the above method, the preset fingerprint library includes fingerprint data, and the fingerprint data is used to represent the correspondence between the terminal location information and the measurement report data. Based on this, after obtaining the terminal positioning data, the fingerprint data corresponding to the measurement report data in the terminal positioning data is searched in the preset database, and then the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data is calculated. Among them, the fingerprint data includes multiple feature data, so the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data can be calculated based on each feature data. Then, according to the size of the distance, the preset number of fingerprint data with the smallest distance is selected, and the above preset number of fingerprint data information and the terminal location information are closest. In this way, the terminal location information corresponding to the terminal can be calculated by using the preset algorithm and the preset number of fingerprint data. Thereby improving the accuracy of the calculation result and the terminal positioning accuracy.

[0080] The following combination Figure 2 Introduce the process of building a preset fingerprint library, such as Figure 2 As shown, the method includes:

[0081] S201. Obtain historical positioning data of each terminal in different cells.

[0082] The historical positioning data includes the terminal identification, the cell identification, the characteristic data of the terminal and the location information of the terminal.

[0083] S202: For the same cell identifier, the historical positioning data is aggregated using the terminal's location information to obtain a data set corresponding to each cell.

[0084] Specifically, the electronic device aggregates the historical positioning data according to the cell identifier to obtain a first set corresponding to different cell identifiers, and then aggregates each first set using the terminal identifier to obtain a second set corresponding to each first set, wherein the second set includes historical positioning data corresponding to the same cell identifier and terminal identifier.

[0085] S203: For each terminal corresponding to each terminal identifier in each data set, calculate the mean of the location information of each terminal in the data set to obtain the location information corresponding to the terminal.

[0086] For each second set, the electronic device sorts the historical positioning data according to the timestamp of the historical positioning data to obtain a second set sequence. According to the arrangement order in the second set sequence, the distance between the first historical positioning data and the second historical positioning data is calculated. If the distance is less than the preset distance value, the first historical positioning data and the second historical positioning data are used as aggregation set 1, and then the mean value of the terminal location information of aggregation set 1 is calculated. Then the electronic device calculates the distance between the third historical positioning data and the mean value of the terminal location information of aggregation set 1. If the distance is less than the preset distance value, the third historical positioning data is added to aggregation set 1. If the distance is greater than or equal to the preset distance value, the third historical positioning data is used as aggregation set 2. Repeat the above steps until the electronic device determines the aggregation set corresponding to each second set. Each aggregation set corresponds to a fingerprint data in the preset fingerprint library.

[0087] S204: For each terminal corresponding to each terminal identifier in each data set, calculate the mean of the feature data of each terminal in the data set to obtain feature data corresponding to the terminal.

[0088] It should be noted that, when the number of fingerprint data corresponding to each second set is greater than a preset number threshold, the mean value of the feature data corresponding to each aggregation set is calculated.

[0089] S205: Use the terminal identifier, the cell identifier, the location information corresponding to the terminal, and the feature data corresponding to the terminal as a fingerprint data to construct a preset fingerprint library.

[0090] The electronic device calculates the location information mean and feature data mean of each aggregation set, and uses the calculated location information mean, feature data mean, cell identifier and terminal identifier corresponding to the aggregation set as a fingerprint, thereby constructing a preset fingerprint library.

[0091] In an example, Table 1 exemplarily shows the historical positioning data of the serving cell RH13532A and the terminal identification 32156143, as shown in Table 1:

[0092] Terminal identification timestamp Cell ID longitude Dimensions NrScRSRP 32156143 2021 / 06 / 19 8:00:02 RH13532A 124.4556 23.28695 52 32156143 2021 / 06 / 19 8:00:17 RH13532A 124.4557 23.28696 51 32156143 2021 / 06 / 19 8:00:32 RH13532A 124.4558 23.28714 47 32156143 2021 / 06 / 19 8:00:47 RH13532A 124.456 23.28719 48 32156143 2021 / 06 / 19 8:01:01 RH13532A 124.456 23.28714 46 32156143 2021 / 06 / 19 8:01:16 RH13532A 124.4576 23.28774 46 32156143 2021 / 06 / 19 8:01:31 RH13532A 124.4576 23.28778 51 32156143 2021 / 06 / 19 8:01:46 RH13532A 124.4577 23.28773 52 32156143 2021 / 06 / 19 8:02:00 RH13532A 124.4579 23.28775 52 32156143 2021 / 06 / 19 8:02:15 RH13532A 124.4575 23.28779 51

[0093] Table 1 is the second set in the above embodiment, the first historical positioning data is the data in the second row of Table 1, the second historical positioning data is the data in the third row of Table 1, the third historical positioning data is the data in the fourth row of Table 1, the fourth historical positioning data is the data in the fifth row of Table 1, and so on.

[0094] Assume that the preset distance value is 50 meters. The electronic device calculates that the distance between the terminal positions represented by the first historical positioning data and the second historical positioning data is 11 meters, then the first historical positioning data and the second historical positioning data are used as aggregation set 1, and the longitude and latitude mean of aggregation set 1 is calculated. Then the distance between the third historical positioning data and the longitude and latitude mean of aggregation set 1 is calculated. The distance is less than the preset distance value. Therefore, the third historical positioning data is added to aggregation set 1. By analogy, the fourth historical positioning data and the fifth historical positioning data both meet the above distance conditions. The electronic device adds the fourth historical positioning data and the fifth historical positioning data to aggregation set 1. After calculation, the distance between the sixth historical positioning data and aggregation set 1 is 197 meters, then the sixth historical positioning data is used as aggregation set 2. By analogy, the seventh historical positioning data to the tenth historical positioning data are added to aggregation set 2. By calculating the feature data mean and longitude and latitude mean of aggregation set 1 and aggregation set 2, two fingerprint data as shown in Table 2 can be obtained:

[0095]

[0096] It should be noted that the embodiment of the present application exemplifies one type of feature data, and in actual implementation, the number of feature data is greater than 1. The number and type of feature data can be set according to actual application scenarios.

[0097] In addition, based on the fingerprint data obtained by the above calculation, the electronic device can update the fingerprint data in the preset fingerprint library every preset period. Specifically, the electronic device uses the timestamp in the fingerprint data to delete the fingerprint data of the oldest day and add the fingerprint data of the latest day to the preset fingerprint library.

[0098] Using the method provided in the embodiment of the present application, after the historical positioning data, firstly, according to the cell identifier, the terminals corresponding to the same cell identifier are aggregated according to the location information to obtain the data set corresponding to each cell, and then, for each data set, the mean of the location information of the terminal in the data set is calculated, and the mean of the feature data of each data set is calculated, so as to obtain the location information and feature data of each data set. Finally, a fingerprint data can be constructed using the terminal identifier, cell identifier, location information and feature data, and then to the preset fingerprint library. In this way, each fingerprint data includes multiple feature data, and when the terminal positioning data is subsequently positioned using multiple feature data, the positioning accuracy can be improved.

[0099] With respect to the above S201, obtaining the historical positioning data of each terminal in different cells may be specifically implemented as follows:

[0100] The historical positioning data includes the terminal identification, the cell identification, the characteristic data of the terminal and the location information of the terminal.

[0101] Specifically, the electronic device obtains historical positioning data from multiple pre-set data sources. In one example, the historical positioning data may be Minimization of Drive Tests (MDT), Over The Top (OTT) positioning data, Measurement Report (MR) data, and 5G positioning service data.

[0102] Among them, MDT is a minimized drive test technology in the 3rd Generation Partnership Project (3GPP), which can carry the longitude and latitude information of the terminal. MDT data has the advantages of wide protocol standard practicability, high positioning accuracy, large data volume and low association difficulty.

[0103] OTT positioning data refers to the location information data generated when users conduct Internet services.

[0104] 5G positioning service data includes downlink arrival time difference, uplink arrival time difference, multi-cell round-trip time, downlink departure angle, uplink arrival angle, enhanced cell identification and other information. The 5G positioning system can calculate the terminal location information through the above 5G positioning service data based on the terminal's positioning capability and positioning method.

[0105] MDT data, OTT positioning data and 5G positioning service data include the latitude and longitude information of the terminal.

[0106] It should be noted that the electronic device extracts the above-mentioned MR data, MDT data, OTT positioning data and 5G positioning service data from the third-party platform at preset intervals. And at preset intervals, the preset fingerprint library is updated using historical positioning data such as MR data, MDT data, OTT positioning data and 5G positioning service data stored locally within the preset period. In this way, by constructing or updating the preset fingerprint library using the historical positioning data within the preset period, it can be ensured that the fingerprint data in the preset fingerprint library can cover most areas in the positioning scenario.

[0107] The electronic device extracts field data from the MR data according to a preset extraction rule. Specifically, for 4GMR data, the electronic device extracts field data of the following fields according to the preset rule:

[0108] MR.LteTimeStamp: the time of generating the measurement sampling point;

[0109] MR.LteMmeUeS1apId: terminal identity;

[0110] MR.LteScRSRP: the signal strength of the 4G service cell measured by the terminal;

[0111] MR.LteSiteid: 4G site ID;

[0112] MR.LteScEarfcn: frequency number of 4G service cell;

[0113] MR.LteScPci: Physical Cell Identifier (PCI) of 4G service cell;

[0114] MR.LteScTadv: The air interface delay between the 4G service cell and the user reflects the signal propagation time from the terminal to the service cell and is the main indicator of the distance between the terminal and the service cell.

[0115] MR.LteScAOA: reflects the reference azimuth of the terminal relative to the communication service cell. The reference direction should be due north, counterclockwise;

[0116] MR.LteUePhr: terminal transmit power;

[0117] MR.LteSinrDl: The downlink signal to interference plus noise ratio (SINR) signal quality value measured by 4G users.

[0118] For 5GMR data, the electronic device extracts field data of the following fields according to preset rules:

[0119] MR.NrTimeStamp: the time when the measurement sampling point is generated;

[0120] MR.NrUeN2Id: The terminal's identity on the S1 interface on the MME side;

[0121] MR.NrScRSRP: signal strength of the 5G service cell measured by the terminal;

[0122] MR.NrSiteid: 5G site ID;

[0123] MR.NrScEarfcn: frequency number of the 5G service cell;

[0124] MR.NrScPci: PCI of 5G serving cell;

[0125] MR.NrScTadv: reflects the signal propagation time from the terminal to the serving cell, and is the main indicator reflecting the distance between the terminal and the serving cell;

[0126] MR.NrScAOA: reflects the reference azimuth of the terminal relative to the communication service cell. The reference direction should be due north, counterclockwise.

[0127] MR.NrUePhr: terminal transmit power;

[0128] MR.NrSinrDl: Downlink SINR signal quality value measured by 5G users.

[0129] It should be noted that, based on the MR data collected by the above-mentioned electronic device, after collecting the MDT data, OTT data and 5G positioning service data, the electronic device uses the terminal identifier to associate the MDT data, OTT data and 5G positioning service data with the MR data, thereby obtaining positioning data with accurate longitude and latitude information.

[0130] Then, after obtaining the positioning data with longitude and latitude information, feature data is extracted from the positioning data to construct a preset fingerprint library. As an example, in the embodiment of the present application, the feature data includes NrScRSRP, NrScTadv, NrScAOA, NrUePhr and NrSinrDl. In actual implementation, the user can set the type and quantity of feature data in the preset fingerprint library according to actual business needs.

[0131] With respect to the above S102, the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data is calculated by using the multiple feature data of the fingerprint data in the preset fingerprint library and the multiple measurement report data corresponding to the terminal, which can be specifically implemented as follows:

[0132] Step 1: For each fingerprint data, calculate the target distance of each feature data and the corresponding measurement report data in the terminal positioning data.

[0133] Step 2: Calculate the product of the target distance and the preset weight corresponding to the feature data to obtain a first product.

[0134] Step 3: Calculate the sum of the first products corresponding to each feature data to obtain the distance.

[0135] In the method provided in the embodiment of the present application, since each feature data has different dimensions, different features and different effects on positioning accuracy, a preset weight is set for each feature data, so that after calculating the target distance, the product of the target distance and the preset weight is calculated, and the above distance is determined using the first product. In this way, the distance between each fingerprint data and the terminal positioning data can be accurately calculated, thereby improving the accuracy of subsequent terminal positioning.

[0136] It should be noted that, based on the above-mentioned construction of the preset fingerprint library, since the feature data in the fingerprint library has different dimensions, different characteristics and different impacts on positioning accuracy, the electronic device can determine the preset weight of each feature data through a feature selection algorithm after acquiring the feature data.

[0137] Specifically, the electronic device may use a feature weighting algorithm (Relief algorithm), wherein the Relief algorithm determines the corresponding weights of different feature data according to the correlation between different feature data and categories.

[0138] The method for the electronic device to calculate the preset weight corresponding to the characteristic data is as follows:

[0139] A first sample is randomly selected from a preset fingerprint library, a first nearest neighbor sample is obtained from samples of the same type as the first sample, and a second nearest neighbor sample is obtained from samples of a different type than the first sample.

[0140] For each feature of the first sample, the electronic device calculates the first sample distance between each feature data of the first sample and the corresponding feature data in the first nearest neighbor sample, and the second sample distance between each feature data of the first sample and the corresponding feature data in the second nearest neighbor sample. If the first sample distance is less than the second sample distance, the preset weight of the feature data is increased, otherwise, the preset weight of the feature data is reduced.

[0141] The same type of samples refer to samples whose distance from the terminal position of the first sample is less than or equal to a preset distance value. The electronic device can calculate the first sample distance and the second sample distance by a method of calculating the Euclidean distance.

[0142] The electronic device repeats the above steps m times, and calculates the average weight of each feature data according to the weight of the feature data calculated each time, and uses the average weight as the preset weight of the feature data. In this way, the running time of the Relief algorithm increases or decreases linearly with the increase of the number of sample extractions and the number of feature data N, thereby ensuring the running efficiency.

[0143] In one example, the fingerprint data in the preset fingerprint library is D, the threshold of the preset weight is 0, and the electronic device first resets the preset weight of the feature data in the preset fingerprint library to zero. Execute the command line for i=1 to m do to select the first sample U from the preset fingerprint library. Then obtain k first nearest neighbor samples from the same type of samples, and obtain k second nearest neighbor samples from different types of samples. Then the electronic device executes the command line:

[0144] for A=1to N do

[0145] W(A)=W(A)–∑diff(A,U,H) / (m*k)+∑diff(A,U,M) / (m*k)

[0146] Among them, ∑diff(A,U,H) represents the sum of the differences between the first sample U and the first nearest neighbor sample on feature A, and ∑diff(A,U,M) represents the sum of the differences between the first sample U and the second nearest neighbor sample on feature A.

[0147] In addition, if the calculated preset weight is less than 0, the preset weight corresponding to the feature data is set to 0.

[0148] To reduce the workload, for cells whose number of fingerprint data is less than or equal to a preset number threshold, the electronic device can calculate the mean of the preset weights of the feature data corresponding to other cells, and use the calculated mean of the preset weights corresponding to other cells as the preset weight of the cell.

[0149] In some embodiments of the present application, after the distance is calculated as described above, the terminal location information may be calculated in the following two ways:

[0150] The first implementation method: The terminal location information is calculated according to the following formula:

[0151]

[0152] Among them, U lon Indicates the longitude information in the terminal location information, d i Indicates the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the longitude information corresponding to the i-th feature data;

[0153]

[0154] Among them, U lat Indicates the latitude information in the terminal location information, d i Indicates the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the latitude information corresponding to the i-th feature data.

[0155] For the first implementation method mentioned above, the latitude and longitude information is obtained by calculating the inverse weighted distance between adjacent feature data and terminal positioning, and the influence of different feature data on the accuracy of terminal positioning is comprehensively considered, so that the calculated terminal location information is more accurate.

[0156] The second implementation method: obtaining a preset number of position information corresponding to a preset number of fingerprint data; calculating the average of the preset number of position information to obtain the terminal location information.

[0157] By using the method provided in the embodiment of the present application, after obtaining a preset number of fingerprint data, the average of the preset number of location information can be calculated according to the location information of each fingerprint data. In this way, the calculated average is used as the terminal location information, which can improve the accuracy of the calculated terminal location information.

[0158] It should be noted that after obtaining the terminal positioning data as described above, if the number of fingerprint data in the preset fingerprint library corresponding to the terminal positioning data is small, the terminal can be jointly positioned and calibrated with other preset fingerprint libraries to improve the accuracy of terminal positioning. Figure 3 As shown, after the above S101, obtaining the terminal positioning data, the method further includes:

[0159] S301: Determine the format information of terminal positioning data.

[0160] In an embodiment of the present application, the standard information of the terminal positioning data is used to indicate that the terminal is a 4G terminal or a 5G terminal.

[0161] It should be noted that the electronic device can quickly locate the terminal based on the terminal positioning data. Some terminal positioning data include longitude and latitude information, and the electronic device can directly determine the terminal position based on the longitude and latitude information. Some terminal positioning data do not include longitude and latitude information. Therefore, the electronic device locates the terminal according to the preset fingerprint library and the terminal positioning data.

[0162] In one example, in the embodiment of the present application, the terminal positioning data is divided into three categories, as shown in Table 3:

[0163]

[0164]

[0165] After the electronic device obtains the first-class positioning data and the second-class positioning data, it can determine the terminal location based on the latitude and longitude information carried in the first-class positioning data and the second-class positioning data. After the electronic device receives the third-class positioning data, it uses the third-class positioning data and the corresponding preset fingerprint library to locate the terminal.

[0166] S302: Determine a first preset fingerprint library corresponding to the terminal positioning data according to the preset correspondence between the standard information and the preset fingerprint library.

[0167] In an embodiment of the present application, the preset fingerprint library corresponding to the standard information includes a 4G preset fingerprint library and a 5G preset fingerprint library.

[0168] It can be understood that the 4G preset fingerprint library is constructed by the electronic device based on the 4G positioning data, and the 5G preset fingerprint library is constructed by the electronic device based on the 5G positioning data.

[0169] S303: Determine whether the number of fingerprint data in the first preset fingerprint library is greater than a first preset threshold.

[0170] S304: When the number of fingerprint data in the first preset fingerprint library is greater than a first preset threshold, calculate the distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data.

[0171] Specifically, the method for calculating the distance is referred to the relevant description in the above embodiment, which will not be repeated here.

[0172] It can be understood that when the number of fingerprint data in the first preset fingerprint library is greater than the first preset threshold, it means that the amount of fingerprint data in the first preset fingerprint library for terminal positioning is sufficient, and the terminal can be accurately positioned. Figure 1 The method provided by the illustrated embodiment is used to locate the terminal.

[0173] S305. When the number of fingerprint data in the first preset fingerprint library is less than or equal to the first preset threshold, and when the number of fingerprint data in the second preset fingerprint library is greater than the second preset threshold, calculate the first distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data, and calculate the second distance between the fingerprint data in the second preset fingerprint library and the terminal positioning data.

[0174] It can be understood that when the number of fingerprint data in the first preset fingerprint library is less than or equal to the first preset threshold, it means that the amount of fingerprint data in the first preset database used for terminal positioning is small, and the calculated terminal location information is less accurate. Therefore, when the electronic device determines that the number of fingerprint data in the second preset fingerprint library is greater than the second preset threshold, the second preset fingerprint library and the first preset fingerprint library are used to jointly locate and calibrate the terminal.

[0175] S306: Acquire a first preset number of fingerprint data with the smallest first distance according to the size of the first distance.

[0176] S307: Acquire a second preset number of fingerprint data with the smallest second distance according to the size of the second distance.

[0177] S301. Calculate first terminal location information corresponding to terminal positioning data based on a preset algorithm and a first preset number of fingerprint data.

[0178] S308: Calculate the second terminal location information corresponding to the terminal positioning data based on a preset algorithm and a second preset number of fingerprint data.

[0179] S309: Calculate the average of the first terminal location information and the second terminal location information to obtain the terminal location information.

[0180] According to the method provided by the embodiment of the present application, after the terminal positioning data is obtained as described above, the corresponding first preset fingerprint library is determined according to the format information of the terminal positioning data. When the number of fingerprint data in the first preset fingerprint library is greater than the first preset threshold, it indicates that the data volume of the first preset fingerprint library supports accurate positioning of the terminal, and thus the distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data is calculated using the first preset fingerprint library. When the number of fingerprint data in the first preset fingerprint library is less than or equal to the first preset threshold, and when the number of fingerprint data in the second preset fingerprint library is greater than the second preset threshold, the first distance and the second distance are calculated respectively. In this way, the first terminal location information of the terminal is determined based on the first preset fingerprint library, and the second terminal location information of the terminal is determined based on the second preset fingerprint library. The average of the first terminal location information and the second terminal location information is calculated, and the terminal location information is finally obtained. In this way, when the first preset fingerprint library cannot support accurate positioning of the terminal, the second preset fingerprint library is used to calibrate the terminal location information of the first preset fingerprint library to improve the accuracy of the terminal location information.

[0181] It is understandable that, since the first preset fingerprint library and the second preset fingerprint library correspond to different standard information, when the terminal is positioned using the preset fingerprint library corresponding to different standard information, the terminal positioning data is adjusted so that the adjusted terminal positioning data is more consistent with the data requirements of the preset fingerprint library, thereby ensuring the accuracy of the positioning result. Therefore, the above calculation of the second distance between the fingerprint data in the second preset fingerprint library and the terminal positioning data can be implemented as:

[0182] According to the same coverage correspondence between the fingerprint data in the first preset fingerprint library and the fingerprint data in the second preset fingerprint library, the terminal positioning data is adjusted to obtain updated terminal positioning data, and a second distance between the updated terminal positioning data and the fingerprint data in the second preset fingerprint library is calculated.

[0183] The same coverage correspondence relationship includes the correspondence between the terminal positioning data in the first preset fingerprint library and the second preset fingerprint library.

[0184] When adjusting the terminal positioning data using the same coverage correspondence relationship, the electronic device needs to ensure that the first preset fingerprint library and the second preset fingerprint library meet the prerequisite of the same coverage correspondence relationship. Specifically, the prerequisite of the same coverage correspondence relationship is that the cells in the first preset fingerprint library and the second preset fingerprint library are both macro cells, there are cells with co-sites in the first preset fingerprint library and the second preset fingerprint library, and the fingerprint data of the same terminal identifier and cell identifier in the first preset fingerprint library and the second preset fingerprint library have the same longitude and latitude information and the same azimuth information.

[0185] Furthermore, based on the same coverage correspondence, when the electronic device uses the preset fingerprint library corresponding to different standard information to jointly locate and calibrate the terminal, it can adjust the terminal positioning data to obtain updated terminal positioning data, and the updated terminal positioning data is more in line with the data requirements of different preset fingerprint libraries for positioning data, thereby ensuring the accuracy of the calculation results.

[0186] In the embodiment of the present application, for the above same coverage correspondence, the electronic device adjusts the downlink signal strength difference value, the downlink signal SINR difference value and the mobile phone transmission power difference value. It should be noted that in actual implementation, the above same coverage correspondence can be preset according to the actual scenario.

[0187] Specifically, the downlink signal strength difference value, the downlink signal SINR difference value and the mobile phone transmission power difference value can be calculated in advance based on the fingerprint data of the same location. The same location means that the distance between the terminals is less than a fixed threshold.

[0188] In one example, before the electronic device locates the terminal using a preset fingerprint library different from the standard information of the terminal positioning data, the downlink signal strength, downlink signal SINR and mobile phone transmission power in the terminal positioning data are adjusted.

[0189] For example, when an electronic device uses a 4G preset fingerprint library to locate a 5G terminal, the terminal positioning data is adjusted according to the following formula:

[0190] LteScRSRP5G = NrScRSRP + downlink signal strength difference;

[0191] LteUePhr5G = NrUePhr + mobile phone transmission power difference;

[0192] LteSinrDl5G = NrSinrDl + downlink signal SINR difference value;

[0193] When the electronic device uses the 5G preset fingerprint library to locate the 4G terminal, the terminal positioning data is adjusted according to the following formula:

[0194] NrScRSRP4G = LteScRSRP - downlink signal strength difference value;

[0195] NrUePhr4G = LteUePhr - mobile phone transmission power difference;

[0196] NrSinrDl4G=LteSinrDl-downlink signal SINR difference value.

[0197] Based on the terminal positioning method provided in the above embodiment, Figure 4 An exemplary schematic diagram of a terminal positioning method is provided for an embodiment of the present application, such as Figure 4 As shown, the method specifically includes:

[0198] S401, collection and processing of positioning data from multiple data sources.

[0199] The electronic device may obtain the historical positioning data according to a preset data source. Specifically, the method for processing the historical positioning data refers to the relevant description in the above embodiment, which will not be described in detail here.

[0200] S402, constructing a positioning feature fingerprint library.

[0201] Specifically, after the electronic device obtains preset feature data from the historical positioning data, it calculates a preset weight of each feature data, thereby constructing a preset fingerprint library.

[0202] S403: Online fingerprint positioning.

[0203] Among them, after the electronic device obtains the terminal positioning data, the method for positioning the terminal using the preset fingerprint library and the terminal positioning data refers to the relevant description in the above embodiment, which will not be repeated here.

[0204] S404: Joint detection and calibration of positioning information.

[0205] Specifically, when the electronic device determines that the number of fingerprint data in the preset fingerprint library corresponding to the terminal positioning data is insufficient, the preset fingerprint library corresponding to other standard information can be used to jointly locate and calibrate the terminal position. The specific method refers to the relevant description in the above embodiment and will not be repeated here.

[0206] S405: Output the positioning result.

[0207] By adopting the method provided in the embodiment of the present application, a preset fingerprint library is constructed using multiple data sources, thereby enriching the feature data in the preset fingerprint library. Furthermore, when the preset fingerprint library is used for online fingerprint positioning, multiple feature data can be integrated to locate the terminal positioning data, and preset fingerprint libraries of different formats can be used to jointly locate and calibrate the terminal, thereby improving the accuracy of terminal positioning.

[0208] Based on the same concept, the embodiment of the present application provides a terminal positioning device, such as Figure 5 As shown, the device comprises:

[0209] An acquisition module 501 is configured to acquire terminal positioning data, where the terminal positioning data includes a plurality of measurement report data corresponding to the terminal;

[0210] A calculation module 502, configured to calculate a distance between the fingerprint data in the preset fingerprint library and the terminal positioning data by using multiple feature data of the fingerprint data in the preset fingerprint library and multiple measurement report data corresponding to the terminal, wherein the fingerprint data in the preset fingerprint library is used to represent the corresponding relationship between the terminal location information and the measurement report data;

[0211] The calculation module 502 is further used to obtain a preset number of fingerprint data with the minimum distance according to the size of the distance;

[0212] The acquisition module 501 is further used to calculate the terminal location information corresponding to the terminal positioning data based on a preset algorithm and the preset number of fingerprint data.

[0213] In a possible implementation, each feature data corresponds to a preset weight; the calculation module 502 is specifically used to:

[0214] For each fingerprint data, calculating the target distance between each feature data and the corresponding measurement report data in the terminal positioning data;

[0215] Calculating the product of the target distance and the preset weight corresponding to the feature data to obtain a first product;

[0216] The sum of the first products corresponding to each feature data is calculated to obtain the distance.

[0217] In a possible implementation, the calculation module 502 is specifically configured to:

[0218] The terminal location information is calculated according to the following formula:

[0219]

[0220] Among them, U lon Indicates the longitude information in the terminal location information, d i represents the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the longitude information corresponding to the i-th feature data;

[0221]

[0222] Among them, U lat Indicates the latitude information in the terminal location information, d i represents the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the latitude information corresponding to the i-th feature data.

[0223] In a possible implementation, the calculation module 502 is specifically configured to:

[0224] Obtaining a preset number of position information corresponding to the preset number of fingerprint data;

[0225] Calculate the average of the preset number of location information to obtain the terminal location information.

[0226] In a possible implementation, the device further includes:

[0227] A determination module, used to determine the format information of the terminal positioning data;

[0228] The determination module is further used to determine the first preset fingerprint library corresponding to the terminal positioning data according to the preset correspondence between the standard information and the preset fingerprint library;

[0229] A judging module, used to judge whether the number of fingerprint data in the first preset fingerprint library is greater than a first preset threshold;

[0230] The calculation module 502 is further configured to calculate the distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data when the number of fingerprint data in the first preset fingerprint library is greater than the first preset threshold;

[0231] The calculation module 502 is further configured to calculate a first distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data, and calculate a second distance between the fingerprint data in the second preset fingerprint library and the terminal positioning data when the number of fingerprint data in the first preset fingerprint library is less than or equal to the first preset threshold and when the number of fingerprint data in the second preset fingerprint library is greater than the second preset threshold;

[0232] The acquisition module 501 is further configured to acquire a first preset number of fingerprint data with the smallest first distance according to the size of the first distance;

[0233] The acquisition module 501 is further configured to acquire a second preset number of fingerprint data with the smallest second distance according to the size of the second distance;

[0234] The calculation module 502 is further used to calculate the first terminal location information corresponding to the terminal positioning data based on the preset algorithm and the first preset number of fingerprint data;

[0235] The calculation module 502 is further used to calculate the second terminal location information corresponding to the terminal positioning data based on the preset algorithm and the second preset number of fingerprint data;

[0236] The calculation module 502 is further used to calculate the average of the first terminal location information and the second terminal location information to obtain the terminal location information.

[0237] In a possible implementation, the calculation module 502 is specifically configured to:

[0238] Determine the target fingerprint data in the second preset fingerprint library according to the same coverage correspondence relationship between the fingerprint data in the first preset fingerprint library and the fingerprint data in the second preset fingerprint library;

[0239] The second distance is calculated according to the target fingerprint data.

[0240] In a possible implementation, the device further includes:

[0241] The acquisition module 501 is further used to acquire the historical positioning data of each terminal in different cells, wherein the historical positioning data includes the terminal identifier, the cell identifier, the characteristic data of the terminal and the location information of the terminal;

[0242] An aggregation module, for aggregating the historical positioning data using the location information of the terminal for the same cell identifier to obtain a data set corresponding to each cell;

[0243] The calculation module 502 is further configured to calculate, for each terminal corresponding to each terminal identifier in each data set, a mean of the location information of each terminal in the data set to obtain the location information corresponding to the terminal;

[0244] The calculation module 502 is further used to calculate the mean of the characteristic data of each terminal in each data set for the terminal corresponding to each terminal identifier in the data set, so as to obtain the characteristic data corresponding to the terminal;

[0245] The construction module is used to construct the preset fingerprint library by taking the terminal identifier, the cell identifier, the location information corresponding to the terminal and the feature data corresponding to the terminal as a fingerprint data.

[0246] It should be noted that the terminal positioning device is a device corresponding to the above-mentioned method for terminal positioning, and all implementation methods in the above-mentioned method embodiments are applicable to the embodiments of the device and can achieve the same technical effects.

[0247] Figure 6 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0248] The electronic device may include a processor 601 and a memory 602 storing computer program instructions.

[0249] Specifically, the processor 1001 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0250] The memory 602 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 602 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 602 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 602 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 602 is a non-volatile solid-state memory.

[0251] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0252] The processor 601 implements any one of the terminal positioning methods in the above embodiments by reading and executing computer program instructions stored in the memory 602 .

[0253] In one example, the electronic device may further include a communication interface 603 and a bus 604. Figure 6 As shown, the processor 601, the memory 602, and the communication interface 603 are connected via a bus 604 and communicate with each other.

[0254] The communication interface 603 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0255] Bus 604 includes hardware, software or both, and the parts of electronic equipment are coupled to each other.For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 604 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0256] In addition, in combination with the terminal positioning method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any terminal positioning method in the above embodiment is implemented.

[0257] In combination with the terminal positioning method in the above embodiments, an embodiment of the present application may provide a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes any terminal positioning method in the above embodiments.

[0258] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0259] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0260] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0261] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0262] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A terminal positioning method, characterized in that: include: Acquire terminal positioning data, where the terminal positioning data includes a plurality of measurement report data corresponding to the terminal; Calculate the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data by using multiple feature data of the fingerprint data in the preset fingerprint library and multiple measurement report data corresponding to the terminal, wherein the fingerprint data in the preset fingerprint library is used to represent the corresponding relationship between the terminal location information and the measurement report data; According to the size of the distance, a preset number of fingerprint data with the smallest distance is obtained; Based on a preset algorithm and the preset number of fingerprint data, the terminal location information corresponding to the terminal positioning data is calculated.

2. The method according to claim 1, characterized in that Each feature data corresponds to a preset weight; the calculating the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data includes: For each fingerprint data, calculating the target distance between each feature data and the corresponding measurement report data in the terminal positioning data; Calculating the product of the target distance and the preset weight corresponding to the feature data to obtain a first product; The sum of the first products corresponding to each feature data is calculated to obtain the distance.

3. The method according to claim 2, characterized in that The calculating the terminal location information corresponding to the terminal positioning data based on the preset algorithm and the preset number of fingerprint data includes: The terminal location information is calculated according to the following formula: Among them, U lon Indicates the longitude information in the terminal location information, d i represents the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the longitude information corresponding to the i-th feature data; Among them, U lat Indicates the latitude information in the terminal location information, d i represents the distance between the i-th feature data and the feature data in the terminal positioning data, Lon i Indicates the latitude information corresponding to the i-th feature data.

4. The method according to claim 2, characterized in that: The calculating the terminal location information corresponding to the terminal positioning data based on the preset algorithm and the preset number of fingerprint data includes: Obtaining a preset number of position information corresponding to the preset number of fingerprint data; Calculate the average of the preset number of location information to obtain the terminal location information.

5. The method according to claim 1, characterized in that After acquiring the terminal location data, the method further includes: Determining the format information of the terminal positioning data; Determine a first preset fingerprint library corresponding to the terminal positioning data according to a preset correspondence between the standard information and the preset fingerprint library; Determining whether the amount of fingerprint data in the first preset fingerprint library is greater than a first preset threshold; When the number of fingerprint data in the first preset fingerprint library is greater than the first preset threshold, calculating the distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data; When the number of fingerprint data in the first preset fingerprint library is less than or equal to the first preset threshold, and when the number of fingerprint data in the second preset fingerprint library is greater than the second preset threshold, calculate a first distance between the fingerprint data in the first preset fingerprint library and the terminal positioning data, and calculate a second distance between the fingerprint data in the second preset fingerprint library and the terminal positioning data; According to the size of the first distance, a first preset number of fingerprint data with the smallest first distance is obtained; According to the size of the second distance, a second preset number of fingerprint data with the smallest second distance is obtained; Calculate the first terminal location information corresponding to the terminal positioning data based on the preset algorithm and the first preset number of fingerprint data; Calculate the second terminal location information corresponding to the terminal positioning data based on the preset algorithm and the second preset number of fingerprint data; Calculate the average of the first terminal location information and the second terminal location information to obtain the terminal location information.

6. The method according to claim 5, characterized in that The calculating a second distance between the fingerprint data in the second preset fingerprint library and the terminal positioning data includes: According to the same coverage correspondence relationship between the fingerprint data in the first preset fingerprint library and the fingerprint data in the second preset fingerprint library, the terminal positioning data is adjusted to obtain updated terminal positioning data; A second distance between the update terminal positioning data and the fingerprint data in the second preset fingerprint library is calculated.

7. The method according to claim 1, characterized in that Before calculating the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data, the method further includes: Acquire historical positioning data of each terminal in different cells, the historical positioning data including terminal identification, cell identification, characteristic data of the terminal and location information of the terminal; For the same cell identifier, the historical positioning data is aggregated using the location information of the terminal to obtain a data set corresponding to each cell; For each terminal corresponding to each terminal identifier in each data set, calculate the mean of the location information of each terminal in the data set to obtain the location information corresponding to the terminal; For each terminal corresponding to each terminal identifier in each data set, calculate the mean of the feature data of each terminal in the data set to obtain the feature data corresponding to the terminal; The terminal identifier, the cell identifier, the location information corresponding to the terminal, and the feature data corresponding to the terminal are used as fingerprint data to construct the preset fingerprint library.

8. A terminal positioning device, characterized in that: include: An acquisition module, configured to acquire terminal positioning data, wherein the terminal positioning data includes a plurality of measurement report data corresponding to the terminal; a calculation module, configured to calculate the distance between the fingerprint data in the preset fingerprint library and the terminal positioning data by using multiple feature data of the fingerprint data in the preset fingerprint library and multiple measurement report data corresponding to the terminal, wherein the fingerprint data in the preset fingerprint library is used to represent the corresponding relationship between the terminal location information and the measurement report data; The acquisition module is used to acquire a preset number of fingerprint data with the smallest distance according to the size of the distance; The calculation module is used to calculate the terminal location information corresponding to the terminal positioning data based on a preset algorithm and the preset number of fingerprint data.

9. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the method for terminal positioning as described in any one of claims 1-7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the terminal positioning method according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the terminal positioning method as described in any one of claims 1 to 7.

Images