Positioning data processing method and device

Abstract

The embodiment of the present application provides a positioning data processing method and device, the method comprising: determining at least one target positioning data that meets preset conditions from a plurality of positioning data. Obtaining the collection time corresponding to each of the target positioning data and the user identifier corresponding to each of the target positioning data. According to the collection time of each target positioning data, respectively obtain the positioning data of the adjacent time of each collection time, and obtain the adjacent positioning data corresponding to each of the target positioning data. According to each target positioning data and the adjacent positioning data corresponding to each of the target positioning data, determine the target user identifier from the user identifier corresponding to each of the target positioning data. By first screening out the target positioning data that meets the preset conditions from a plurality of positioning data, and then further determining the target user identifier for virtual positioning, the accuracy of identifying the user of virtual positioning can be effectively guaranteed.

Description

Technical Field

[0001] The embodiments of the present application relate to computer technology, and more particularly to a positioning data processing method and device. Background Art

[0002] Currently, terminal devices can implement a positioning function, wherein the terminal devices can, for example, perform real positioning or virtual positioning.

[0003] When a user performs virtual positioning through a terminal device, he or she may perform some illegal operations, which will reduce the security of the system. Therefore, it is particularly important to identify the user performing virtual positioning. The existing technology usually identifies the user performing virtual positioning by monitoring the jump points. Specifically, when a long-distance jump suddenly appears in the user's trajectory, it can be determined that the user has performed illegal operations using virtual positioning.

[0004] However, when the signal of the terminal device is poor, or when the terminal device fails, the positioning data may also jump, so the accuracy of the existing technology in detecting the user of virtual positioning is low. Summary of the invention

[0005] The embodiments of the present application provide a positioning data processing method and device to overcome the problem of low accuracy in detecting a virtually positioned user.

[0006] In a first aspect, an embodiment of the present application provides a positioning data processing method, including:

[0007] Determine at least one target positioning data satisfying a preset condition among the multiple positioning data;

[0008] Acquire the collection time corresponding to each of the target positioning data and the user identifier corresponding to each of the target positioning data;

[0009] According to the collection time of each target positioning data, respectively obtain the positioning data of the adjacent time of each collection time, and obtain the adjacent positioning data corresponding to each target positioning data;

[0010] According to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data, a target user identifier is determined from the user identifiers corresponding to each of the target positioning data.

[0011] In one possible design, the positioning data includes at least one of the following: longitude, latitude, accuracy, altitude, and collection time;

[0012] The step of determining at least one target positioning data satisfying a preset condition among the plurality of positioning data comprises:

[0013] Among the multiple positioning data, the positioning data whose accuracy is equal to the first preset value and whose altitude is equal to the second preset value is obtained to obtain at least one target positioning data.

[0014] In a possible design, determining the target user identifier from the user identifiers corresponding to the target positioning data respectively according to the target positioning data and the adjacent positioning data corresponding to the target positioning data respectively includes:

[0015] Determine the positioning parameters corresponding to each of the target positioning data according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data;

[0016] According to the positioning parameters corresponding to each of the target positioning data, a target user identifier is determined from the user identifiers corresponding to each of the target positioning data.

[0017] In a possible design, determining the positioning parameters corresponding to each of the target positioning data according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data includes:

[0018] Obtaining a distance between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to the first longitude and the first latitude in the target positioning data and the second longitude and the second latitude in the adjacent positioning data corresponding to the target positioning data;

[0019] Obtaining a time interval between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to a first acquisition time in the target positioning data and a second acquisition time in the adjacent positioning data corresponding to the target positioning data;

[0020] Obtaining a target accuracy according to a first accuracy in the target positioning data and a second accuracy in adjacent positioning data corresponding to the target positioning data, wherein the target accuracy is a maximum value between the first accuracy and the second accuracy;

[0021] The jump speed corresponding to the target positioning data is obtained according to the distance and the time interval.

[0022] In a possible design, determining the target user identifier from the user identifiers corresponding to the respective target positioning data according to the respective positioning parameters of the respective target positioning data includes:

[0023] The user identifier corresponding to the target positioning data whose positioning parameters meet the threshold condition is determined as the target user identifier.

[0024] In one possible design, the threshold condition is: the distance is greater than a preset distance, the jumping speed is greater than a preset speed, and the target accuracy is less than the target positioning data of a preset accuracy.

[0025] In a possible design, acquiring positioning data at adjacent moments of each of the collection moments according to the collection moments of each of the target positioning data, and obtaining adjacent positioning data corresponding to each of the target positioning data, respectively, includes:

[0026] According to the collection time of each target positioning data, the positioning data of a first preset number of moments adjacent to the collection time is obtained, and / or, according to the collection time of each target positioning data, the positioning data of a second preset number of moments adjacent to the collection time is obtained, so as to obtain the adjacent positioning data corresponding to the target positioning data.

[0027] In a possible design, the first preset value is 8.0, and the second preset value is 0.0.

[0028] In a second aspect, an embodiment of the present application provides a positioning data processing device, including:

[0029] A determination module, used to determine at least one target positioning data satisfying a preset condition among a plurality of positioning data;

[0030] An acquisition module, used to acquire the collection time corresponding to each of the target positioning data and the user identifier corresponding to each of the target positioning data;

[0031] The acquisition module is further used to respectively acquire the positioning data of the adjacent moments of each acquisition moment according to the acquisition moment of each target positioning data, so as to obtain the adjacent positioning data corresponding to each target positioning data;

[0032] The determination module is further configured to determine a target user identifier from user identifiers corresponding to each of the target positioning data according to each of the target positioning data and adjacent positioning data corresponding to each of the target positioning data.

[0033] In one possible design, the positioning data includes at least one of the following: longitude, latitude, accuracy, altitude, and collection time;

[0034] The determination module is specifically used for:

[0035] Among the multiple positioning data, the positioning data whose accuracy is equal to the first preset value and whose altitude is equal to the second preset value is obtained to obtain at least one target positioning data.

[0036] In a possible design, the determining module is specifically used to:

[0037] Determine the positioning parameters corresponding to each of the target positioning data according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data;

[0038] According to the positioning parameters corresponding to each of the target positioning data, a target user identifier is determined from the user identifiers corresponding to each of the target positioning data.

[0039] In a possible design, the determining module is specifically used to:

[0040] Obtaining a distance between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to the first longitude and the first latitude in the target positioning data and the second longitude and the second latitude in the adjacent positioning data corresponding to the target positioning data;

[0041] Obtaining a time interval between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to a first acquisition time in the target positioning data and a second acquisition time in the adjacent positioning data corresponding to the target positioning data;

[0042] Obtaining a target accuracy according to a first accuracy in the target positioning data and a second accuracy in adjacent positioning data corresponding to the target positioning data, wherein the target accuracy is a maximum value between the first accuracy and the second accuracy;

[0043] The jump speed corresponding to the target positioning data is obtained according to the distance and the time interval.

[0044] In a possible design, the determining module is specifically used to:

[0045] The user identifier corresponding to the target positioning data whose positioning parameters meet the threshold condition is determined as the target user identifier.

[0046] In one possible design, the threshold condition is: the distance is greater than a preset distance, the jumping speed is greater than a preset speed, and the target accuracy is less than the target positioning data of a preset accuracy.

[0047] In a possible design, the acquisition module is specifically used for:

[0048] According to the collection time of each target positioning data, the positioning data of a first preset number of moments adjacent to the collection time is obtained, and / or, according to the collection time of each target positioning data, the positioning data of a second preset number of moments adjacent to the collection time is obtained, so as to obtain the adjacent positioning data corresponding to the target positioning data.

[0049] In a possible design, the first preset value is 8.0, and the second preset value is 0.0.

[0050] In a third aspect, an embodiment of the present application provides a positioning data processing device, including:

[0051] Memory, used to store programs;

[0052] A processor is used to execute the program stored in the memory. When the program is executed, the processor is used to execute the method described in the first aspect and any one of the various possible designs of the first aspect.

[0053] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enables the computer to execute the method described in the first aspect and any one of the various possible designs of the first aspect.

[0054] The embodiment of the present application provides a positioning data processing method and device, the method comprising: determining at least one target positioning data that meets a preset condition from among a plurality of positioning data. Obtaining the collection time corresponding to each of the target positioning data and the user identifier corresponding to each of the target positioning data. According to the collection time of each target positioning data, respectively obtain the positioning data of the adjacent time of each collection time, and obtain the adjacent positioning data corresponding to each of the target positioning data. According to each target positioning data and the adjacent positioning data corresponding to each of the target positioning data, determine the target user identifier from the user identifier corresponding to each of the target positioning data. By first screening out the target positioning data that meets the preset condition from among the plurality of positioning data, wherein the preset condition is used to indicate the virtual positioning data, the accuracy of the user identifier for the subsequent determination of the virtual positioning can be effectively improved, and then the target user identifier for the virtual positioning is further determined based on the target positioning data and the adjacent positioning data, so that the accuracy of identifying the user for the virtual positioning can be effectively guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0056] Figure 1 A system diagram of a positioning data processing method provided in an embodiment of the present application;

[0057] Figure 2 A flowchart of a positioning data processing method provided in an embodiment of the present application;

[0058] Figure 3 Another flow chart of the positioning data processing method provided in an embodiment of the present application;

[0059] Figure 4 A schematic diagram of an implementation of determining target positioning data provided in an embodiment of the present application;

[0060] Figure 5 A schematic diagram of an implementation method for determining adjacent positioning data provided in an embodiment of the present application;

[0061] Figure 6 A schematic diagram of an implementation of determining a target user identifier provided in an embodiment of the present application;

[0062] Figure 7 A flowchart of a positioning data processing method provided in an embodiment of the present application;

[0063] Figure 8 A schematic diagram of the structure of a positioning data processing device provided in an embodiment of the present application;

[0064] Fig. 9 A schematic diagram of the hardware structure of a positioning data processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0066] In order to better understand the technical solution of the present application, the background technology involved in the present application is firstly introduced in further detail:

[0067] Terminal devices can usually implement a positioning function, and many applications rely on the positioning function of the terminal devices to implement corresponding business processing. The positioning of the terminal device can be, for example, real positioning or virtual positioning.

[0068] In the Android system, for example, a terminal device can be virtually positioned through the terminal device's own positioning function. For example, some mobile phone brands have a built-in function to change the positioning. Alternatively, the terminal device can also install an application for virtual positioning to achieve virtual positioning of the terminal device. Whether it is the virtual positioning function that comes with the terminal device or the virtual positioning function implemented based on the application, it is usually implemented in a two-point jump manner. For example, the current user is holding the terminal device at point A, and the user's location can be changed to point B through virtual positioning.

[0069] It is understandable that users may perform some illegal operations through virtual positioning through terminal devices. For example, order service providers may use virtual positioning to make false order operations. For example, online car-hailing drivers may use virtual positioning to make virtual trips to obtain improper benefits. Therefore, it is particularly important to identify users of virtual positioning.

[0070] Therefore, the commonly used virtual positioning identification method is to monitor the jumping points. For example, when a long-distance jump suddenly appears in the user's trajectory, it can be considered that the current user has performed an illegal operation using virtual positioning.

[0071] However, when the signal of the terminal device is poor or the terminal device fails, the positioning data will also fluctuate, causing positioning jumps. Therefore, the implementation method of monitoring jump points in the prior art has certain limitations, resulting in low recognition accuracy of virtually positioned users.

[0072] In addition, in the prior art, the distance between the two points before and after needs to be calculated throughout the day to determine whether the user's positioning data has jumped, which will result in the consumption of a large amount of computing resources.

[0073] In response to the problems in the prior art, the present application proposes the following technical concept: after analyzing the virtual positioning data of the terminal device, it is found that the virtual positioning data all show the same characteristics, among which the accuracy and altitude in the virtual positioning data are usually fixed values. Then, it is possible to first determine whether the accuracy and altitude of the positioning data are fixed values, thereby screening out suspicious positioning data, and then compare the suspicious positioning data with the positioning data at the adjacent time to determine whether the current positioning data is virtual positioning data, and then determine the user performing virtual positioning, because a preliminary judgment is first made based on the value of the positioning data, and then a further determination is made, thereby effectively ensuring the accuracy of identifying the user of virtual positioning, and first screening out suspicious positioning data and then making a judgment, which can effectively reduce the amount of computing tasks to save resources.

[0074] The following is a detailed description of the positioning data processing method provided by the present application in conjunction with specific embodiments. Figure 1 The positioning data processing system in this application is described. Figure 1 A system diagram of a positioning data processing method provided in an embodiment of the present application.

[0075] like Figure 1 As shown, the system includes: a terminal device 101 and a server 102.

[0076] Among them, the terminal device can be, for example, a mobile phone (or called a "cellular" phone), a tablet computer, a computer device, etc. The terminal device can also be a portable, pocket-sized, handheld, or computer-built-in mobile device or device. There is no special limitation here. In this embodiment, the terminal device has a positioning function, and the terminal device can realize virtual positioning.

[0077] Among them, the server can interact with the terminal device to obtain the positioning data of the terminal device, and then analyze the positioning data of the terminal device to determine whether each positioning data is virtual positioning data. It can be understood that each positioning data can correspond to a user identifier, and then based on the determined virtual positioning data, the user identifier of the virtual positioning can be determined, thereby realizing the identification of the user identifier of the virtual positioning.

[0078] The interaction method may be, for example, through a wired network, or the interaction method may be, for example, a wireless network, and the wireless network may be a 2G network, a 3G network, a 4G network or a 5G network, a Wireless Fidelity (WIFI) network, etc.

[0079] The embodiments of the present application do not limit the specific type or form of interaction, as long as it can realize the function of interaction between the server and the terminal device.

[0080] The positioning data processing method provided in the embodiments of the present application is described in detail below in conjunction with specific embodiments. The execution subject of each embodiment of the present application may be the server introduced above, or may also be a device with data processing function such as a processor or a microprocessor.

[0081] Figure 2 A flowchart of a positioning data processing method provided in an embodiment of the present application, such as Figure 2 As shown, the method includes:

[0082] S201. Determine at least one target positioning data satisfying a preset condition among multiple positioning data.

[0083] In this embodiment, the server can identify the user identifier for virtual positioning based on the positioning data, so the server needs to first obtain multiple positioning data, where the positioning data is data used to indicate the location, which may include, for example, longitude, latitude, altitude, etc. This embodiment does not impose any special restrictions on the specific implementation of the positioning data.

[0084] In one possible implementation, a user can log in through an APP (application) on a terminal device, and then the APP can collect the positioning data of the currently logged-in user account at multiple times. The server can, for example, interact with the terminal device to obtain the positioning data of the user account in the APP at multiple times, and the server can interact with multiple terminal devices to obtain the positioning data corresponding to multiple user accounts. Therefore, in this embodiment, the multiple positioning data can be the positioning data corresponding to multiple user accounts at multiple times.

[0085] After the server acquires multiple positioning data, it can determine at least one target positioning data satisfying a preset condition from the multiple positioning data. In this embodiment, the preset condition is a condition for indicating that the positioning data is virtual positioning data.

[0086] In a possible implementation, after analyzing the virtual positioning data of the Android system, it is found that the virtual positioning data all present certain characteristics. For example, if the positioning data is equal to a specific value, the preset condition may be that the positioning data is equal to the specific value, and the positioning data that meets the preset condition is determined as the target positioning data. It can be understood that the target positioning data in this embodiment is the initially determined suspicious positioning data, that is, this part of the positioning data is likely to be virtual positioning data.

[0087] In the actual implementation process, the specific implementation method of the preset condition can be selected according to actual needs, as long as the preset condition is a condition used to indicate that the positioning data is virtual positioning data. For example, it can be the above-mentioned positioning data equal to specific data, or with the continuous development of relevant technologies, when the virtual positioning data presents other characteristics, the preset condition can also be expanded according to actual needs.

[0088] S202: Acquire the collection time corresponding to each target positioning data and the user identifier corresponding to each target positioning data.

[0089] In this embodiment, each positioning data corresponds to a collection time, and the collection time is the time when the current positioning data is collected; and each positioning data is collected by the APP, and the user can log in to the APP through the user account, so each positioning data also corresponds to the user account. In a possible implementation method, the positioning data includes the collection time and the user identifier, or the collection time and the user identifier can also be information associated with the positioning data, but not included in the positioning data. This embodiment does not limit this.

[0090] Among them, at least one target positioning data is obtained from the multiple positioning data, so the collection time corresponding to each target positioning data can be obtained, and the user identification corresponding to each target positioning data can be obtained.

[0091] S203 . According to the collection time of each target positioning data, respectively obtain the positioning data of the adjacent time of each collection time, and obtain the adjacent positioning data corresponding to each target positioning data.

[0092] After the target positioning data is determined as described above, the possible virtual positioning data is preliminarily determined. In order to ensure the accuracy of the user identification of the determined virtual positioning, this embodiment needs to further determine at least one of the determined target positioning data to determine the virtual positioning data from the at least one target positioning data.

[0093] Based on the above introduction, it can be understood that after the user performs virtual positioning, the user's trajectory will jump. When the user's trajectory jumps, there must be a certain gap between the positioning data at the jumping moment and the positioning data at the adjacent moment. Therefore, the adjacent positioning data corresponding to each target positioning data can be obtained to determine whether the current target positioning data is virtual positioning data.

[0094] Among them, each target positioning data corresponds to its own collection time. Taking any target positioning data as an example, the positioning data of the adjacent time of the collection time of the current target positioning data can be obtained, so as to obtain the adjacent positioning data corresponding to the current target positioning data.

[0095] In one possible implementation, assuming that the positioning data is collected every 3 seconds, the positioning data of the 3 seconds before the collection moment of the current target positioning data can be determined, and / or the positioning data of the 3 seconds after the collection moment of the current target positioning data can be determined, so as to obtain adjacent positioning data. Currently, the positioning data collected at the first adjacent moment and / or the last adjacent moment is introduced. In the actual implementation process, the positioning data of the first N moments and / or the last M adjacent moments can also be collected to obtain adjacent positioning data, where M and N are integers greater than or equal to 1.

[0096] Wherein, for each target positioning data, the adjacent positioning data is obtained in the above manner, so that the adjacent positioning data corresponding to each target positioning data can be obtained.

[0097] S204: Determine a target user identifier from user identifiers corresponding to each target positioning data according to each target positioning data and the adjacent positioning data corresponding to each target positioning data.

[0098] After the adjacent positioning data corresponding to each target positioning data are determined, the target user identifier can be determined from the user identifiers corresponding to each target positioning data.

[0099] Taking any target positioning data as an example, it is assumed that the current target positioning data 1 corresponds to two adjacent positioning data, which are the positioning data at the previous moment and the positioning data at the next moment, and are assumed to be adjacent positioning data A and adjacent positioning data B. For example, it is possible to determine whether the target positioning data 1 jumps based on the target positioning data 1 and the adjacent positioning data A, and to determine whether the target positioning data 1 jumps based on the target positioning data 1 and the adjacent positioning data B.

[0100] Among them, judging whether the target positioning data jumps, for example, can judge whether the distance between the target positioning data and the adjacent positioning data is greater than a preset threshold, whether the moving speed is greater than a preset threshold, whether the maximum accuracy between the target positioning data and the adjacent positioning data is small enough, etc. This embodiment does not impose any special restrictions on the specific implementation method of judging whether the target positioning data jumps, which can be selected and expanded according to actual needs. As long as there is a certain difference between the target positioning data and the adjacent positioning data, it can be considered that the target positioning data jumps.

[0101] In this embodiment, if it is determined that the target positioning data has jumped, the user identifier corresponding to the current target positioning data can be determined as the target positioning data. Therefore, in this embodiment, a judgment can be made based on each target positioning data and each corresponding adjacent positioning data, so as to determine the target user identifier among the user identifiers corresponding to each target positioning data, wherein the target user identifier is the user identifier that has been virtually positioned.

[0102] It is worth noting that the execution process in this embodiment can be performed by the server online, for example, after the server obtains a positioning data, it directly executes subsequent operations to determine whether the user identifier corresponding to the current positioning data is the target user identifier; or, the execution process can also be performed by the server offline, for example, the server can obtain positioning data for a period of time, and identify the target user identifier in the positioning data during this period of time. This embodiment does not limit the specific implementation method of this execution process, and it can be selected according to actual needs.

[0103] The positioning data processing method provided in the embodiment of the present application includes: determining at least one target positioning data that meets the preset conditions among multiple positioning data. Obtaining the collection time corresponding to each of the target positioning data and the user identification corresponding to each of the target positioning data. According to the collection time of each target positioning data, respectively obtain the positioning data of the adjacent time of each collection time, and obtain the adjacent positioning data corresponding to each of the target positioning data. According to each target positioning data and the adjacent positioning data corresponding to each target positioning data, determine the target user identification among the user identifications corresponding to each of the target positioning data. By first screening out the target positioning data that meets the preset conditions among the multiple positioning data, wherein the preset conditions are used to indicate the virtual positioning data, the accuracy of the user identification for the subsequent determination of the virtual positioning can be effectively improved, and then the target user identification for the virtual positioning is further determined based on the target positioning data and the adjacent positioning data, so that the accuracy of the user identification for the virtual positioning can be effectively guaranteed.

[0104] Based on the above embodiments, Figures 3 to 6 The positioning data processing method provided in this application is further introduced in detail. Figure 3 Another flow chart of the positioning data processing method provided in an embodiment of the present application, Figure 4 A schematic diagram of an implementation of determining target positioning data provided in an embodiment of the present application, Figure 5 A schematic diagram of an implementation method for determining adjacent positioning data provided in an embodiment of the present application, Figure 6 A schematic diagram of an implementation of determining a target user identifier provided in an embodiment of the present application.

[0105] like Figure 3 As shown, the method includes:

[0106] S301. From a plurality of positioning data, obtain positioning data having an accuracy equal to a first preset value and an altitude equal to a second preset value, and obtain at least one target positioning data.

[0107] In this embodiment, the server can obtain multiple positioning data, and after analyzing the virtual positioning data of the Android system, it is found that the accuracy of the virtual positioning data is equal to the first preset value, and the altitude is equal to the second preset value. For example, Figure 4 It is understood that the positioning data having an accuracy equal to the first preset value and an altitude equal to the second preset value in the positioning data can be determined as the target positioning data.

[0108] In a possible implementation, the first preset value may be, for example, 8.0, and the second preset value may be, for example, 0.0, and positioning data with an accuracy equal to 8.0 and an altitude equal to 1.0 may be determined as target positioning data, thereby obtaining at least one positioning data.

[0109] In this embodiment, the positioning data includes at least one of the following: longitude, latitude, accuracy, altitude, and collection time, wherein accuracy refers to the degree of error of the current positioning data. For example, an accuracy of 20 means that the error between the longitude and latitude of the positioning data and the actual position is within plus or minus 20 meters. Therefore, the smaller the accuracy feature, the more accurate the current positioning data.

[0110] In another possible implementation, the positioning data may also include, for example, the brand of the terminal device. Because some brands of terminal devices support virtual positioning, while some brands of terminal devices do not support virtual positioning, before filtering based on accuracy and altitude, you may first filter based on the brand of the terminal device. First, obtain the positioning data of terminal devices of brands that support virtual positioning, and then filter based on accuracy and altitude in this part of the positioning data. This can effectively narrow the filtering range and save system resources.

[0111] Among them, the brand of terminal devices supporting virtual positioning can be selected and expanded according to actual needs. This embodiment does not impose any special restrictions on this. It can be understood that this embodiment supports the processing of any terminal device with a virtual positioning function.

[0112] S302: Obtain the collection time corresponding to each target positioning data and the user identifier corresponding to each target positioning data.

[0113] The implementation of S302 is similar to the implementation of S202 described above, and will not be described in detail here.

[0114] S303 . According to the collection time of each target positioning data, respectively obtain the positioning data of the adjacent time of each collection time, and obtain the adjacent positioning data corresponding to each target positioning data.

[0115] In this embodiment, based on the collection time of each target positioning data, the positioning data of a first preset number of adjacent moments before the collection time can be obtained, and / or, based on the collection time of each target positioning data, the positioning data of a second preset number of adjacent moments after the collection time can be obtained to obtain the adjacent positioning data corresponding to the target positioning data.

[0116] The first preset number and the second preset number can be selected according to actual needs, which specifically depends on how many adjacent positioning data are currently required.

[0117] Combine the following Figure 5 , taking any target positioning data as an example, the implementation method of determining the adjacent positioning data of the target positioning data is introduced:

[0118] In a possible implementation, for example, adjacent positioning data is determined for the current positioning data, and then the positioning data of the user identifier corresponding to the current positioning data at each time can be obtained, for example, see Figure 5 Assuming that the current target positioning data is the positioning data of user A at time 7, the positioning data of user A at other times can be obtained, and the adjacent positioning data of the target positioning data at time 7 can be determined based on the positioning data at other times.

[0119] Assuming that the current time is to obtain the positioning data of the moment before the collection time of the target positioning data, the positioning data of the moment 6 can be obtained. Assuming that the current time is also to obtain the positioning data of the moment after the collection time of the target positioning data, the positioning data of the moment 8 can be obtained. The positioning data of the moment 6 and the moment 8 are the adjacent positioning data corresponding to the current target positioning data.

[0120] Alternatively, for example, if the current time is to obtain the positioning data of the three moments before the collection time of the target positioning data, then the positioning data of moments 4, 5, and 6 can be obtained. And assuming that the current time is also to obtain the positioning data of the three moments after the collection time of the target positioning data, then the positioning data of moments 8, 9, and 10 can be obtained. Then the positioning data of moments 4, 5, 6, 8, 9, and 10 are the adjacent positioning data corresponding to the current target positioning data.

[0121] Among them, each target positioning data specifically corresponds to several adjacent positioning data, which can be selected according to actual needs, and this embodiment does not impose any special limitation on this.

[0122] It can be understood that the moment in this embodiment refers to the moment of acquiring positioning data, and the specific time difference between each moment depends on the implementation of acquiring positioning data, which is not limited in this embodiment.

[0123] S304: Obtain a distance between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to the first longitude and the first latitude in the target positioning data and the second longitude and the second latitude in the adjacent positioning data corresponding to the target positioning data.

[0124] After determining the adjacent positioning data corresponding to each target positioning data, it is possible to determine whether the user corresponding to the current user identifier has been virtually positioned based on the target positioning data and the corresponding adjacent positioning data. In this embodiment, positioning parameters can be obtained based on the target positioning data and the corresponding adjacent positioning data, and then the positioning parameters are compared with the threshold information to determine the final target user identifier.

[0125] In a possible implementation manner, for example, the distance between the target positioning data and the corresponding adjacent positioning data can be determined. Specifically, the distance between the target positioning data and the adjacent positioning data corresponding to the target positioning data can be obtained according to the first longitude and the first latitude in the target positioning data and the second longitude and the second latitude in the adjacent positioning data corresponding to the target positioning data.

[0126] The following example illustrates that, assuming that Figure 6 , assuming that there are currently:

[0127] Target positioning data 1 (longitude 1, latitude 1, collection time 1, accuracy 1);

[0128] Adjacent positioning data (longitude 2, latitude 2, collection time 2, accuracy 2).

[0129] The distance may be determined by, for example, determining the difference between longitude 1 and longitude 2, and determining the difference between latitude 1 and latitude 2.

[0130] S305 . Obtain a time interval between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to a first collection time in the target positioning data and a second collection time in the adjacent positioning data corresponding to the target positioning data.

[0131] Furthermore, in this embodiment, the time interval between the target positioning data and the corresponding adjacent positioning data can also be determined. Specifically, the time interval between the target positioning data and the adjacent positioning data corresponding to the target positioning data can be obtained according to the first acquisition time in the target positioning data and the second acquisition time in the adjacent positioning data corresponding to the target positioning data.

[0132] Assuming that we continue to use the above example, see Figure 6 , the absolute value of the difference between acquisition time 1 and acquisition time 2 can be obtained, thereby obtaining the time interval.

[0133] S306. Obtain a target accuracy according to the first accuracy in the target positioning data and the second accuracy in the adjacent positioning data corresponding to the target positioning data, wherein the target accuracy is a maximum value between the first accuracy and the second accuracy.

[0134] Furthermore, in this embodiment, in order to avoid false detection caused by the influence of terminal equipment, the accuracy can also be combined in the process of determining the target user identification for virtual positioning. Therefore, in this embodiment, the maximum value of the first accuracy in the target positioning data and the second accuracy in the adjacent positioning data corresponding to the target positioning data can be determined as the target accuracy.

[0135] Assuming that we continue to use the above example, see Figure 6 , the maximum value of precision 1 and precision 2 can be determined as the target precision.

[0136] S307: Obtain the jump speed corresponding to the target positioning data according to the distance and time interval.

[0137] The above determines the distance and time interval between the target positioning data and the corresponding adjacent positioning data. Figure 6 , according to the ratio between distance and time interval, the jump speed corresponding to the target positioning data can be obtained.

[0138] It is worth noting that the execution order of the above S304-S307 can be selected according to actual needs during the actual implementation process, and the above steps do not constitute a limitation on the execution order. For example, the target accuracy can be determined first, and then the remaining positioning parameters can be determined. This embodiment does not impose any restrictions on this.

[0139] S308: Determine the user identifier corresponding to the target positioning data whose positioning parameters meet the threshold condition as the target user identifier.

[0140] After obtaining multiple positioning parameters, the user identifier corresponding to the target positioning data whose positioning parameters meet the threshold conditions can be determined as the target user identifier, wherein generally a jumping virtual trajectory is a long-distance jump in a short time, so the threshold conditions may include: the distance is greater than the preset distance, and the jumping speed is greater than the preset speed, and, in this embodiment, in order to avoid signal interference and misjudgment caused by equipment fault lights, in this embodiment, the maximum accuracy needs to be limited to be small enough, so the threshold conditions may also include: target positioning data with a target accuracy less than a preset accuracy, wherein the preset accuracy can be 30, for example.

[0141] See for example Figure 6 , assuming that the current distance is greater than the preset distance, the jumping speed is greater than the preset speed, and the maximum accuracy is less than the preset accuracy, the user identification 1 corresponding to the current target positioning data can be determined as the target user identification.

[0142] It can be understood that the above is an introduction using one adjacent positioning data corresponding to a certain target positioning data as an example. In the actual implementation process, the target positioning data may correspond to multiple adjacent positioning data, and the above operation can be performed according to the target positioning data and each corresponding adjacent positioning data; and, in this embodiment, there is at least one target positioning data, and the above operation can also be performed for each target positioning data to obtain the target user identifier from the user identifiers corresponding to the multiple positioning data.

[0143] It can be understood that in this embodiment, after data analysis, it is found that when the terminal device of the Android system performs virtual positioning, the accuracy of the positioning data is usually 8.0. Therefore, in this embodiment, the data with an accuracy equal to 8.0 in the positioning data can be pulled out, and then the adjacent point features of this part of the data are used to determine whether the current positioning data is virtual positioning data, thereby effectively improving the accuracy of determining the virtual positioning data.

[0144] In addition, the currently commonly used method for identifying virtual positioning requires pulling out all the data and comparing adjacent points one by one to see if there is a jump, which will result in a very large amount of calculation. In this application, the abnormal positioning data with an accuracy of 8.0 and an altitude of 0.0 can be directly filtered out, and only the abnormal positioning data and its corresponding adjacent positioning data are compared to achieve good data sampling, greatly improving the efficiency of data processing.

[0145] The positioning data processing method provided in the embodiment of the present application can effectively improve the accuracy of subsequent virtual positioning by first determining the target positioning data from multiple positioning data according to the characteristics of altitude and accuracy presented in the virtual positioning data. At the same time, by screening out a small part of the target positioning data from the multiple positioning data, the amount of data to be processed can be effectively reduced, so that when calculating adjacent positioning data, it is not necessary to calculate the distances of adjacent points of all points one by one, but only perform jump detection on the adjacent points of the target positioning data, thereby improving processing efficiency. In addition, in the present embodiment, when finally determining the user identification for virtual positioning, the accuracy is also limited, thereby effectively avoiding signal interference and misjudgment caused by equipment fault lights, and effectively ensuring the accuracy of virtual positioning recognition.

[0146] Combine the following Figure 7 The positioning data processing method provided by this application is described in detail with a specific example. Figure 7 A flowchart of a positioning data processing method provided in an embodiment of the present application.

[0147] like Figure 7As shown, first, the positioning data is collected in the APP in the terminal device, where the main fields collected include: mobile phone brand, longitude, latitude, accuracy, altitude, and collection time, so as to obtain multiple positioning data.

[0148] Then the data is filtered. First, the mobile phone brand is screened to determine whether the mobile phone brand in the positioning data is a preset brand. The preset brand is a brand that can be virtually positioned. After restricting the mobile phone brand, points with an accuracy of 8.0 and an altitude of 0.0 are filtered out.

[0149] It can be understood that if the current data filtering conditions are not met, the current positioning data is considered to be normal positioning data and no subsequent processing is required. Those that meet the above conditions can be determined as target positioning data, or they can be understood as suspicious data points. The user ID and collection time corresponding to the target positioning data are then recorded.

[0150] For each target positioning data, the adjacent point information before and after the acquisition time of the target positioning data can be obtained to obtain the adjacent positioning information corresponding to the target positioning information. Assuming that the current result is:

[0151] Target positioning data 1 (longitude 1, latitude 1, collection time 1, accuracy 1);

[0152] Adjacent positioning data 2 (longitude 2, latitude 2, collection time 2, accuracy 2).

[0153] Then the distance, time interval, maximum accuracy and jump speed between the target positioning information 1 and the adjacent positioning information can be calculated.

[0154] Among them, thresholds can be set for distance, jump speed and maximum accuracy to obtain the user identification for virtual positioning. Generally, the virtual trajectory of jumping is a long-distance jump in a short time, so it can be restricted that the distance is greater than a certain value and the jump speed is also greater than a certain value. These two thresholds can be selected according to actual needs. There is no restriction on this here, but in order to ensure that the signal interference and other problems will not cause misjudgment, the maximum accuracy must be small enough. The threshold of the maximum accuracy can be, for example, 30.

[0155] To sum up, the positioning data processing method provided in the embodiment of the present application determines the target positioning data from multiple positioning data according to the characteristics of the altitude and accuracy presented in the virtual positioning data, thereby effectively improving the accuracy of subsequent virtual positioning while improving processing efficiency. In addition, in the present embodiment, when finally determining the user identification for virtual positioning, accuracy limitations are also imposed, thereby effectively avoiding signal interference and misjudgments caused by equipment fault lights, and effectively ensuring the accuracy of virtual positioning recognition.

[0156] Figure 8This is a schematic diagram of the structure of the positioning data processing device provided in the embodiment of the present application. Figure 8 As shown, the device 80 includes: a determination module 801 and an acquisition module 802.

[0157] The determination module 801 is used to determine at least one target positioning data satisfying a preset condition among multiple positioning data;

[0158] An acquisition module 802 is used to acquire the collection time corresponding to each of the target positioning data and the user identifier corresponding to each of the target positioning data;

[0159] The acquisition module 802 is further configured to acquire the positioning data of the adjacent moments of each acquisition moment according to the acquisition moment of each target positioning data, so as to obtain the adjacent positioning data corresponding to each target positioning data;

[0160] The determination module 801 is further configured to determine a target user identifier from user identifiers corresponding to each of the target positioning data according to each of the target positioning data and adjacent positioning data corresponding to each of the target positioning data.

[0161] In one possible design, the positioning data includes at least one of the following: longitude, latitude, accuracy, altitude, and collection time;

[0162] The determining module 801 is specifically used for:

[0163] Among the multiple positioning data, the positioning data whose accuracy is equal to the first preset value and whose altitude is equal to the second preset value is obtained to obtain at least one target positioning data.

[0164] In a possible design, the determining module 801 is specifically configured to:

[0165] Determine the positioning parameters corresponding to each of the target positioning data according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data;

[0166] According to the positioning parameters corresponding to each of the target positioning data, a target user identifier is determined from the user identifiers corresponding to each of the target positioning data.

[0167] In a possible design, the determining module 801 is specifically configured to:

[0168] Obtaining a distance between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to the first longitude and the first latitude in the target positioning data and the second longitude and the second latitude in the adjacent positioning data corresponding to the target positioning data;

[0169] Obtaining a time interval between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to a first acquisition time in the target positioning data and a second acquisition time in the adjacent positioning data corresponding to the target positioning data;

[0170] Obtaining a target accuracy according to a first accuracy in the target positioning data and a second accuracy in adjacent positioning data corresponding to the target positioning data, wherein the target accuracy is a maximum value between the first accuracy and the second accuracy;

[0171] The jump speed corresponding to the target positioning data is obtained according to the distance and the time interval.

[0172] In a possible design, the determining module 801 is specifically configured to:

[0173] The user identifier corresponding to the target positioning data whose positioning parameters meet the threshold condition is determined as the target user identifier.

[0174] In one possible design, the threshold condition is: the distance is greater than a preset distance, the jumping speed is greater than a preset speed, and the target accuracy is less than the target positioning data of a preset accuracy.

[0175] In a possible design, the acquisition module 802 is specifically used to:

[0176] According to the collection time of each target positioning data, the positioning data of a first preset number of moments adjacent to the collection time is obtained, and / or, according to the collection time of each target positioning data, the positioning data of a second preset number of moments adjacent to the collection time is obtained, so as to obtain the adjacent positioning data corresponding to the target positioning data.

[0177] In a possible design, the first preset value is 8.0, and the second preset value is 0.0.

[0178] The device provided in this embodiment can be used to execute the technical solution of the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0179] Fig. 9 A schematic diagram of the hardware structure of the positioning data processing device provided in the embodiment of the present application is shown in FIG. Fig. 9 As shown, the positioning data processing device 90 of this embodiment includes: a processor 901 and a memory 902;

[0180] Memory 902, used to store computer-executable instructions;

[0181] The processor 901 is used to execute the computer-executable instructions stored in the memory to implement the various steps performed by the positioning data processing method in the above embodiment. For details, please refer to the relevant description in the above method embodiment.

[0182] Optionally, the memory 902 may be independent or integrated with the processor 901 .

[0183] When the memory 902 is independently provided, the positioning data processing device further includes a bus 903 for connecting the memory 902 and the processor 901 .

[0184] An embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the positioning data processing method executed by the positioning data processing device as described above is implemented.

[0185] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, 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 interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0186] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (English: processor) to perform some steps of the method described in each embodiment of the present application.

[0187] It should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented by a hardware processor or implemented by a combination of hardware and software modules in the processor.

[0188] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0189] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0190] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0191] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0192] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A positioning data processing method, characterized in that: include: Determine at least one target positioning data satisfying a preset condition among the multiple positioning data; Acquire the collection time corresponding to each of the target positioning data and the user identifier corresponding to each of the target positioning data; According to the collection time of each target positioning data, respectively obtain the positioning data of the adjacent time of each collection time, and obtain the adjacent positioning data corresponding to each target positioning data; as well as Determine a target user identifier from user identifiers corresponding to each of the target positioning data according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data; Wherein, the preset condition is a condition for indicating that the positioning data is virtual positioning data; Wherein, according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data, determining the target user identifier from the user identifiers corresponding to each of the target positioning data includes: Determine, according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data, the positioning parameters corresponding to each of the target positioning data; the positioning parameters are used to characterize at least one of the distance, moving speed or maximum accuracy between the target positioning data and the adjacent positioning data; According to the positioning parameters corresponding to each of the target positioning data, a target user identifier is determined from the user identifiers corresponding to each of the target positioning data.

2. The method according to claim 1, characterized in that The positioning data includes at least one of the following: longitude, latitude, accuracy, altitude, and collection time; The step of determining at least one target positioning data satisfying a preset condition among the plurality of positioning data comprises: Among the multiple positioning data, the positioning data whose accuracy is equal to the first preset value and whose altitude is equal to the second preset value is obtained to obtain at least one target positioning data.

3. The method according to claim 1, characterized in that The determining, according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data, the positioning parameters corresponding to each of the target positioning data respectively include: Obtaining a distance between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to the first longitude and the first latitude in the target positioning data and the second longitude and the second latitude in the adjacent positioning data corresponding to the target positioning data; Obtaining a time interval between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to a first acquisition time in the target positioning data and a second acquisition time in the adjacent positioning data corresponding to the target positioning data; Obtaining a target accuracy according to a first accuracy in the target positioning data and a second accuracy in adjacent positioning data corresponding to the target positioning data, wherein the target accuracy is a maximum value between the first accuracy and the second accuracy; The jump speed corresponding to the target positioning data is obtained according to the distance and the time interval.

4. The method according to claim 3, characterized in that The determining, according to the positioning parameters corresponding to each of the target positioning data, the target user identifier from the user identifiers corresponding to each of the target positioning data, comprises: The user identifier corresponding to the target positioning data whose positioning parameters meet the threshold condition is determined as the target user identifier.

5. The method according to claim 4, characterized in that The threshold conditions are: the distance is greater than a preset distance, the jumping speed is greater than a preset speed, and the target accuracy is less than the target positioning data of a preset accuracy.

6. The method according to any one of claims 1 to 5, characterized in that: The acquiring of positioning data at adjacent moments of each of the target positioning data according to the collection moments of each of the target positioning data to obtain adjacent positioning data corresponding to each of the target positioning data includes: According to the collection time of each target positioning data, the positioning data of a first preset number of moments adjacent to the collection time is obtained, and / or, according to the collection time of each target positioning data, the positioning data of a second preset number of moments adjacent to the collection time is obtained, so as to obtain the adjacent positioning data corresponding to the target positioning data.

7. The method according to claim 2, characterized in that The first preset value is 8.0, and the second preset value is 0.

0.

8. A positioning data processing device, characterized in that: include: A determination module, used to determine at least one target positioning data satisfying a preset condition among a plurality of positioning data; An acquisition module, used to acquire the collection time corresponding to each of the target positioning data and the user identifier corresponding to each of the target positioning data; The acquisition module is further used to respectively acquire the positioning data of the adjacent moments of each acquisition moment according to the acquisition moment of each target positioning data, so as to obtain the adjacent positioning data corresponding to each target positioning data; The determination module is further configured to determine a target user identifier from user identifiers corresponding to each of the target positioning data according to each of the target positioning data and adjacent positioning data corresponding to each of the target positioning data; Wherein, the preset condition is a condition for indicating that the positioning data is virtual positioning data; Wherein, the determination module is specifically used for: Determine, according to each of the target positioning data and the adjacent positioning data corresponding to each of the target positioning data, the positioning parameters corresponding to each of the target positioning data; the positioning parameters are used to characterize at least one of the distance, moving speed or maximum accuracy between the target positioning data and the adjacent positioning data; According to the positioning parameters corresponding to each of the target positioning data, a target user identifier is determined from the user identifiers corresponding to each of the target positioning data.

9. The device according to claim 8, characterized in that The positioning data includes at least one of the following: longitude, latitude, accuracy, altitude, and collection time; The determination module is specifically used for: Among the multiple positioning data, the positioning data whose accuracy is equal to the first preset value and whose altitude is equal to the second preset value is obtained to obtain at least one target positioning data.

10. The device according to claim 8, characterized in that The determination module is specifically used for: Obtaining a distance between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to the first longitude and the first latitude in the target positioning data and the second longitude and the second latitude in the adjacent positioning data corresponding to the target positioning data; Obtaining a time interval between the target positioning data and the adjacent positioning data corresponding to the target positioning data according to a first acquisition time in the target positioning data and a second acquisition time in the adjacent positioning data corresponding to the target positioning data; Obtaining a target accuracy according to a first accuracy in the target positioning data and a second accuracy in adjacent positioning data corresponding to the target positioning data, wherein the target accuracy is a maximum value between the first accuracy and the second accuracy; The jump speed corresponding to the target positioning data is obtained according to the distance and the time interval.

11. The device according to claim 10, characterized in that The determination module is specifically used for: The user identifier corresponding to the target positioning data whose positioning parameters meet the threshold condition is determined as the target user identifier.

12. The device according to claim 11, characterized in that The threshold conditions are: the distance is greater than a preset distance, the jumping speed is greater than a preset speed, and the target accuracy is less than the target positioning data of a preset accuracy.

13. The device according to any one of claims 8 to 12, characterized in that: The acquisition module is specifically used for: According to the collection time of each target positioning data, the positioning data of a first preset number of moments adjacent to the collection time is obtained, and / or, according to the collection time of each target positioning data, the positioning data of a second preset number of moments adjacent to the collection time is obtained, so as to obtain the adjacent positioning data corresponding to the target positioning data.

14. The device according to claim 9, characterized in that The first preset value is 8.0, and the second preset value is 0.

0.

15. A positioning data processing device, characterized in that: include: Memory, used to store programs; A processor, configured to execute the program stored in the memory; when the program is executed, the processor is configured to execute the method according to any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that: The method comprises instructions which, when executed on a computer, cause the computer to perform the method as claimed in any one of claims 1 to 7.

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