Positioning method and apparatus, device, and storage medium

Abstract

Embodiments of the present application disclose a positioning method and device, equipment and a storage medium, including: a terminal device acquires cell parameters of a cell at a current position, the cell at the current position including a serving cell and multiple neighboring cells; the cell parameters of the serving cell at the current position are matched with cell distribution of multiple fixed lines to obtain a matched serving cell, the cell distribution including position coordinates of multiple positions in the fixed lines and cell parameters of each position, the multiple positions including collection positions and interpolation positions, the interpolation positions being obtained by interpolation processing on the collection positions; and position coordinates of the current position are determined according to the cell parameters of the cell at the current position, cell parameters of the cell at multiple candidate positions in a coverage range of the matched serving cell and the position coordinates of the multiple candidate positions. The positioning accuracy of the terminal device is improved, and the positioning power consumption of the terminal device is reduced.

Description

Technical Field

[0001] This application relates to communication technology, and to, but is not limited to, a positioning method, apparatus, device, and storage medium. Background Technology

[0002] In today's digital age, the rapid development of mobile communication and internet technologies has profoundly changed people's daily lives. Among the applications of mobile communication technology, the technology of locating user positions has been widely used in industries such as transportation construction, public safety, and travel services.

[0003] In related technologies, when locating users, most methods include base station positioning, Global Positioning System (GPS) positioning, and radio frequency fingerprint positioning.

[0004] However, the aforementioned base station positioning methods require prior knowledge of the base station's location information. In reality, the obtained base station location information has a large error, leading to inaccurate positioning. Furthermore, base station positioning requires the base station to collect and analyze signal information between the terminal device and the base station, complete calculations, and transmit the positioning results back to the terminal device. This involves signal transmission, data processing, and positioning calculations, thus introducing positioning delays. GPS positioning is generally difficult to obtain due to privacy concerns, and frequent GPS information collection can also cause power consumption issues. Radio frequency fingerprint positioning requires a large amount of radio frequency signal measurement in the RF fingerprint database, demanding a high data volume. Summary of the Invention

[0005] In view of this, the positioning method, apparatus, device, and storage medium provided in the embodiments of this application can improve the positioning accuracy of terminal devices and reduce the positioning power consumption of terminal devices. The positioning method, apparatus, device, and storage medium provided in the embodiments of this application are implemented as follows:

[0006] In a first aspect, embodiments of this application provide a positioning method applied to a terminal device, the method comprising:

[0007] Obtain the cell parameters of the cell at the current location, wherein the cell at the current location includes the serving cell and multiple neighboring cells, and the cell parameters include identification information and / or signal strength information;

[0008] The cell parameters of the serving cell at the current location are matched with the cell distribution of multiple fixed lines to obtain a matching serving cell. The matching serving cell has the same identification information as the serving cell at the current location. The cell distribution of the fixed lines includes the location coordinates of multiple locations in the fixed lines and the cell parameters of each location. The multiple locations include the acquisition location and the interpolation location. The interpolation location is obtained by interpolating the acquisition location.

[0009] The location coordinates of the current location are determined based on the cell parameters of the cell at the current location, the cell parameters of cells at multiple candidate locations within the coverage area of ​​the matching serving cell, and the location coordinates of the multiple candidate locations.

[0010] Secondly, embodiments of this application provide a positioning device, comprising:

[0011] The acquisition module is used to acquire the cell parameters of the cell at the current location. The cell at the current location includes the serving cell and multiple neighboring cells. The cell parameters include identification information and / or signal strength information.

[0012] The matching module is used to match the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines to obtain a matching serving cell. The matching serving cell has the same identification information as the serving cell at the current location. The cell distribution of the fixed lines includes the location coordinates of multiple locations in the fixed lines and the cell parameters of each location. The multiple locations include the acquisition location and the interpolation location. The interpolation location is obtained by interpolating the acquisition location.

[0013] The determining module is used to determine the location coordinates of the current location based on the cell parameters of the cell at the current location, the cell parameters of cells at multiple candidate locations within the coverage area of ​​the matching serving cell, and the location coordinates of the multiple candidate locations.

[0014] Thirdly, embodiments of this application provide a computer device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the program to implement the method described in embodiments of this application.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods described in embodiments of this application.

[0016] The positioning method, apparatus, computer equipment, and computer-readable storage medium provided in this application embodiment allow the terminal device to match the cell parameters of the cell at the current location with the cell parameters of multiple locations in a known fixed line during positioning. After a successful match, a location is selected as the current location of the terminal device within the coverage area of ​​the matched serving cell.

[0017] In this way, on the one hand, since there is no need to obtain GPS and base station information from the terminal device, only the cell parameters of the cell at the current location need to be collected, which can reduce the power consumption of the terminal device; and positioning based on the identification information and / or signal strength information in the cell parameters is more accurate than considering only the cell identification information. On the other hand, the location information in the fixed line is obtained by combining the collected location and the interpolated location obtained by interpolating the sampled location. When constructing the fixed line, the line can be accurately constructed with less sampling data, thereby improving the comparison accuracy when comparing it with the cell parameters of the cell at the current location of the terminal device, and thus improving the positioning accuracy of the terminal device. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application.

[0019] Figure 1 A schematic diagram illustrating the implementation process of a positioning method provided in an embodiment of this application;

[0020] Figure 2 This is a schematic diagram illustrating the effect of a cell at the current location of a terminal device provided in an embodiment of this application.

[0021] Figure 3 A schematic diagram illustrating the effect of fixed-line cell distribution in an embodiment of this application;

[0022] Figure 4 A schematic diagram illustrating the implementation process of another positioning method provided in this application embodiment;

[0023] Figure 5 A schematic diagram illustrating the implementation flow of the method for determining a matching serving cell provided in an embodiment of this application;

[0024] Figure 6 A schematic diagram illustrating the implementation flow of the method for determining the target location provided in the embodiments of this application;

[0025] Figure 7 A schematic diagram illustrating the implementation process of an optimization method provided in an embodiment of this application;

[0026] Figure 8 A schematic diagram illustrating the implementation process of optimizing operations performed by a terminal device according to an embodiment of this application;

[0027] Figure 9 A schematic diagram illustrating the implementation flow of the method for constructing a fixed line provided in an embodiment of this application;

[0028] Figure 10A schematic diagram illustrating the implementation flow of an interpolation processing method provided in an embodiment of this application;

[0029] Figure 11 This is a schematic diagram illustrating the effect of multiple sub-sampling location sets provided in the embodiments of this application;

[0030] Figure 12 A schematic diagram illustrating the implementation flow of another interpolation processing method provided in an embodiment of this application;

[0031] Figure 13 This is a schematic diagram of the positioning device provided in the embodiments of this application;

[0032] Figure 14 A schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the specific technical solutions of this application will be further described in detail below with reference to the accompanying drawings of the embodiments of this application. The following embodiments are used to illustrate this application, but are not intended to limit the scope of this application.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0035] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0036] It should be noted that the terms "first, second, third" used in the embodiments of this application are used to distinguish similar or different objects and do not represent a specific order of objects. It can be understood that "first, second, third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0037] In industries such as transportation construction, public safety, and travel services, it is often necessary to obtain the location of terminal devices. The following methods are generally used in related technologies to locate terminal devices:

[0038] (1) Base Station Positioning: Base station positioning is a common terminal positioning technology used to determine the location of terminal devices. Base station positioning determines the location of a terminal device by using base stations in a mobile communication network. This positioning method may include methods based on triangulation principles, utilizing information such as signal strength and latency between the terminal device and surrounding base stations to calculate the terminal device's location. Specifically:

[0039] Location method based on time of arrival difference: Different base stations can calculate the distance between the terminal device and the base station based on the time difference of the signals received from the terminal device, and thus determine the location of the terminal device.

[0040] Positioning method based on received signal strength indication: By measuring the signal strength between the terminal device and multiple base stations, the distance between the terminal device and the base stations can be inferred, and the location can be calculated.

[0041] Angle-of-arrival (AOA) positioning method: The location of a terminal device can be calculated by measuring the angle of incidence of its signal at different base stations.

[0042] (2) Radio frequency fingerprint positioning: Radio frequency fingerprint positioning is a technology that uses radio frequency signal fingerprint information to locate a position. By collecting the characteristics of radio frequency signals, such as signal strength, phase, and time delay, and comparing them with the radio frequency fingerprint database, the accurate location of the terminal device in the environment can be determined.

[0043] However, the above methods have certain drawbacks. For example, the base station positioning method has the following disadvantages:

[0044] (1) When locating a base station, it is necessary to know the location information of the base station in advance. In reality, the location information of the base station obtained has a large error and may be missing.

[0045] (2) Base station positioning requires processing a large number of positioning requests and data, especially in high-density user areas. This increases the system load of the base station, leading to problems such as network congestion, extended response time, and unstable service.

[0046] (3) Base station positioning requires the base station to collect and analyze signal information between the mobile device and the base station, and transmit the positioning result back to the terminal device after completing the calculation. This requires signal transmission, data processing, and positioning calculation, thus resulting in positioning delay. In some application scenarios, such as emergency rescue or navigation systems, positioning delay may lead to serious consequences.

[0047] Radio frequency fingerprinting requires the pre-construction of an radio frequency fingerprint database, which requires a large number of radio frequency signal measurements and has high data requirements.

[0048] In view of this, embodiments of this application provide a positioning method, which is applied to a terminal device.

[0049] The terminal devices involved in the embodiments of this application may include general handheld electronic terminals, such as mobile phones, smartphones, portable terminals, terminals, personal digital assistants (PDAs), portable multimedia players (PMPs), laptops, notebooks, wireless broadband (Wibro) terminals, tablet computers (PCs), smart PCs, point of sale (POS) terminals, and in-vehicle computers, etc.

[0050] Terminal devices can also include wearable devices. Wearable devices are portable electronic devices that can be worn directly on a user's body or integrated into a user's clothing or accessories. Wearable devices are not just hardware devices; they can also achieve powerful intelligent functions through software support, data interaction, and cloud interaction, such as computing, positioning, and alarm functions. They can also connect to mobile phones and various terminals. Wearable devices can include, but are not limited to, wrist-supported devices (such as watches, wristbands, etc.), foot-supported devices (such as shoes, socks, or other leg-wearing products), head-supported devices (such as glasses, helmets, headbands, etc.), as well as smart clothing, backpacks, canes, accessories, and other non-mainstream product forms.

[0051] Figure 1 This is a schematic diagram illustrating the implementation flow of the positioning method provided in an embodiment of this application. Figure 1 As shown, the method may include the following steps:

[0052] Step 101: Obtain the cell parameters of the cell at the current location. The cell at the current location includes the serving cell and multiple neighboring cells. The cell parameters include identification information and / or signal strength information.

[0053] In this embodiment of the application, the cell identification information may include the cell unique identifier (E-UTRAN CellIdentifier, ECI), physical cell identifier (PCI), mobile country code (MCC), mobile network code (MNC), absolute radio frequency channel number (ARFCN), etc.; the cell signal strength information may include reference signal receiving power (RSRP), service type, received signal strength indicator (RSSI), etc.

[0054] It should be noted that the cell where the terminal device is located at its current location may include the serving cell and multiple neighboring cells. For example... Figure 2 As shown, a schematic diagram of the effect of a cell at the current location of a terminal device is given. The cell corresponding to the terminal device 200 may include serving cell 200a, neighboring cells 200b and 201b.

[0055] Step 102: Match the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines to obtain the matching serving cell. The matching serving cell has the same identification information as the serving cell at the current location. The cell distribution of fixed lines includes the location coordinates of multiple locations in the fixed lines and the cell parameters of each location. The multiple locations include the collection location and the interpolation location. The interpolation location is obtained by interpolating the collection location.

[0056] In some embodiments, the number of fixed lines can be limited to improve positioning speed. Fixed lines can be associated with the habits of the user of the terminal device, such as lines frequently accessed by the user.

[0057] Of course, in other embodiments, the number of fixed lines can also be set to multiple, which can be set according to actual needs.

[0058] In some embodiments, when matching the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines, the cell parameters of the serving cell at the current location can be matched with the cell distribution of each fixed line to obtain a matching serving cell with the same identification information as the serving cell at the current location. The fixed line where the matching serving cell is located is the fixed line where the terminal device is currently located.

[0059] In this embodiment, the cell distribution information for a fixed line includes the location coordinates of multiple locations along the fixed line and the cell parameters for each location. These multiple locations are obtained by combining actual data collection locations with interpolated locations obtained through interpolation. This allows for accurate line construction with less sampling data when pre-constructing the cell distribution information for the fixed line. Consequently, when comparing this information with the cell parameters of the cells at the current location of the terminal device, the comparison accuracy is improved, thereby enhancing the positioning accuracy of the terminal device.

[0060] Figure 3 A schematic diagram illustrating the effect of a fixed-line cell distribution is provided. For example... Figure 3 As shown, the cell distribution includes multiple locations, each with corresponding coordinates and cell parameters. Taking location 1 as an example, the cell distribution includes the latitude and longitude coordinates of location 1, as well as the cell parameters of the cell corresponding to location 1. Specifically, this may include the identification information and signal strength information of cell 1; and the identification information and signal strength information of cell 2.

[0061] Here, the identification information may include ECI, PCI, MCC, MNC, etc., and the signal strength information may include RSRP, RSSI, etc.

[0062] It should be noted that the implementation method disclosed in this step is also applicable to step 202 below.

[0063] Step 103: Determine the location coordinates of the current location based on the cell parameters of the cell at the current location, the cell parameters of cells at multiple candidate locations within the coverage area of ​​the matching serving cell, and the location coordinates of the multiple candidate locations.

[0064] In this embodiment of the application, after a matching serving cell that matches the serving cell of the current location is found, the location coordinates of the current location can be determined from multiple candidate locations within the coverage area of ​​the matching serving cell, based on the cell parameters of the cell of the current location, the cell parameters of the cells of the candidate locations, and the location coordinates of the multiple candidate locations.

[0065] In this embodiment, when the terminal device performs positioning, it does not need to collect GPS information, but only needs to perform positioning based on the cell parameters of the cell at the current location, which can effectively reduce power consumption; and the terminal device can complete positioning locally based on the data it collects itself, without needing to transmit the positioning calculation task to the base station, thereby reducing the base station load and avoiding positioning delay.

[0066] In some embodiments, step 103 can be implemented by performing steps 403 to 404 in the following embodiments.

[0067] In this embodiment, when locating, the terminal device matches the cell parameters of the cell at its current location with the cell parameters of multiple locations on a known fixed line. Upon successful matching, a location within the coverage area of ​​the matched serving cell is selected as the terminal device's current location. This approach offers several advantages. First, since it eliminates the need for GPS and base station information, requiring only the cell parameters of the cell at the current location, it reduces power consumption. Furthermore, locating based on the cell identifier and / or signal strength information provides higher accuracy compared to considering only the cell identifier. Second, when constructing a fixed line, precise line construction with less sampling data is achieved, improving comparison accuracy when comparing with the cell parameters of the cell at the terminal device's current location, thereby enhancing the terminal device's positioning accuracy.

[0068] Figure 4 This is a schematic diagram illustrating the implementation flow of the positioning method provided in an embodiment of this application. Figure 4 As shown, the method may include the following steps:

[0069] Step 401: Obtain the cell parameters of the cell at the current location. The cell at the current location includes the serving cell and multiple neighboring cells. The cell parameters include identification information and / or signal strength information.

[0070] In this embodiment, the method of executing step 401 is the same as the method of executing step 101 in the above embodiment, and will not be repeated here.

[0071] Step 402: Match the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines to obtain the matching serving cell. The matching serving cell has the same identification information as the serving cell at the current location. The cell distribution of fixed lines includes the location coordinates of multiple locations in the fixed lines and the cell parameters of each location. The multiple locations include the collection location and the interpolation location. The interpolation location is obtained by interpolating the collection location.

[0072] In this application embodiment, the storage location for the cell distribution information of multiple fixed lines can be in various ways.

[0073] For example, in some embodiments, the cell distribution information of multiple fixed lines can be stored in a server. In this way, after the terminal device obtains the cell parameters of the serving cell at the current location, it can download the cell distribution information of multiple fixed lines from the server to match the cell parameters of the serving cell at the current location with the cell distribution information of multiple fixed lines.

[0074] Alternatively, in other embodiments, the cell distribution information of multiple fixed lines can also be stored locally, i.e., stored in the terminal device. In this way, after the terminal device obtains the cell parameters of the serving cell at the current location, it can directly match the cell parameters of the serving cell at the current location with the cell distribution information of multiple fixed lines stored in its own memory.

[0075] In some embodiments, a schematic diagram of the implementation process of a method for determining a matching serving cell is provided, such as... Figure 5 As shown, the method includes the following steps:

[0076] Step 501: Determine the area identifier of the current location based on the identifier information of the serving cell.

[0077] In this embodiment of the application, after obtaining the identification information of the serving cell of the current location, the area identifier of the area where the terminal device is currently located can be determined based on the identification information of the serving cell of the current location.

[0078] It should be noted that the distribution information of fixed-line cells also includes the area identifier of the area where the fixed-line is located.

[0079] Step 502: Based on the area identifier, determine the target fixed line from multiple fixed lines. The identifier of the target fixed line is the same as the area identifier of the area where the terminal device is located.

[0080] In this way, after the terminal device obtains the area identifier of its current location, it can identify the fixed line with the same area identifier as the area where the terminal device is located from the area identifiers corresponding to multiple fixed lines, and use it as the target fixed line.

[0081] In this embodiment of the application, depending on the storage location of the cell distribution of the fixed line, the terminal device determines the target fixed line from multiple fixed lines in different ways.

[0082] For example, in some embodiments, when the cell distribution information of multiple fixed lines is stored in a server (cloud), the terminal device can send a loading request to the server so that the server responds to the loading request, selects a target fixed line from the multiple fixed lines, and sends the cell distribution information of the target fixed line to the terminal device. The loading request includes a region identifier, and the identifier of the target fixed line is the same as the region identifier.

[0083] In other embodiments, when the cell distribution information of multiple fixed lines is stored in the terminal device, the terminal device can search for a target fixed line from the multiple pre-stored fixed lines based on the area identifier, the identifier of which is the same as the area identifier.

[0084] Step 503: Match the cell parameters of the serving cell at the current location with the cell distribution of the target fixed line to obtain the matching serving cell.

[0085] In this embodiment, after identifying the target fixed line from multiple fixed lines, the terminal device can match the cell parameters of the serving cell at its current location with the cell distribution of the target fixed line to determine whether a matching serving cell can be obtained. This effectively reduces the number of matching operations performed by the terminal device with the fixed line, thereby improving matching efficiency.

[0086] It should be noted that the implementation method disclosed in this step is also applicable to step 102 above.

[0087] Step 403: Based on the identification information of multiple neighboring cells at the current location, determine at least one matching location among multiple candidate locations within the coverage area of ​​the matching serving cell. The identification information of the neighboring cells at the matching location is the same as the identification information of one of the multiple neighboring cells at the current location.

[0088] In this embodiment of the application, the number of neighboring cells at the current location can be multiple, such as neighboring cell1a, neighboring cell2a, ..., neighboring cellna.

[0089] Furthermore, within the coverage area of ​​the matched service cell, there are multiple candidate locations, each with location coordinates and multiple neighboring cells. For example, the neighboring cells corresponding to candidate location 1 may include neighboring cell1b, neighboring cell2b, ..., neighboring cellnb; the neighboring cells corresponding to candidate location 2 may include neighboring cell1c, neighboring cell2c, ..., neighboring cellnc; the neighboring cells corresponding to candidate location 3 may include neighboring cell1d, neighboring cell2d, ..., neighboring cellnd; ...; the neighboring cells corresponding to candidate location m may include neighboring cell1m, neighboring cell2m, ..., neighboring cellnm.

[0090] In this way, the identification information of each neighboring cell can be compared with the identification information of multiple neighboring cells corresponding to each candidate location to determine whether there are neighboring cells with the same identification information.

[0091] For example, the obtained neighboring cell cell1a at the current location is compared with the neighboring cells at each candidate location. Specifically, the identification information of neighboring cell cell1a is compared with that of neighboring cells cell1b, cell2b, ..., cellnb; cell1c, cell2c, ..., cellnc; ...; cell1m, cell2m, ..., cellnm, to determine whether there is a neighboring cell with the same identification information as neighboring cell cell1a.

[0092] After determining that there are neighboring cells with the same identification information as neighboring cell cell1a, if the neighboring cells with the same identification information as neighboring cell cell1a are neighboring cell1b, neighboring cell2c, and neighboring cell2m, then the candidate position 1 corresponding to neighboring cell1b, the candidate position 2 corresponding to neighboring cell2c, and the candidate position m corresponding to neighboring cell2m can be determined as matching positions.

[0093] Step 404: Based on the signal strength information of the serving cell at at least one matching location and the signal strength information of the serving cell at the current location, determine the target location from at least one matching location, and set the location coordinates of the target location as the location coordinates of the current location.

[0094] After determining multiple matching locations within the coverage area of ​​the matching serving cell, a target location can be selected from these matching locations based on the signal strength information of the serving cell corresponding to each matching location and the signal strength information of the serving cell at the current location. This target location is equivalent to the current location of the terminal device, and the location coordinates of the target location are the location coordinates of the current location.

[0095] In some embodiments, such as Figure 6 The diagram shows a flowchart of a method for determining a target location. Step 404 can be achieved by performing the following steps:

[0096] Step 601: Determine the signal strength difference between the signal strength information of the serving cell at at least one matching location and the signal strength information of the serving cell at the current location.

[0097] It should be noted that each matching location also includes the serving cell. Therefore, after obtaining multiple matching locations, the difference between the signal strength information of the serving cell at each matching location and the signal strength information of the serving cell at the current location can be calculated.

[0098] For example, suppose the matching locations are candidate location 1, candidate location 2, and candidate location m. The serving cell corresponding to candidate location 1 is cell0b, the serving cell corresponding to candidate location 2 is cell0c, the serving cell corresponding to candidate location m is cell0m, and the serving cell for the current location is cell0a. Then, the signal strength value RSRP0 of serving cell cell0a can be calculated by subtracting it from the signal strength values ​​RSRP1, RSRP2, and RSRPm of serving cell cell0b, cell0c, and cell0m, respectively, to obtain the signal strength difference corresponding to each candidate location.

[0099] Step 602: Determine the candidate position corresponding to the smallest signal strength difference among at least one signal strength difference as the target position.

[0100] After obtaining multiple signal strength differences, the value with the smallest absolute value can be selected from the multiple signal strength differences. The candidate position corresponding to the smallest value is determined as the target position, and the position coordinates of the candidate position are the position coordinates of the current position of the terminal device.

[0101] In this embodiment, the location coordinates of the current location are determined by combining the cell identification information and signal strength information. Compared with considering only one type of cell information, the positioning accuracy is higher.

[0102] Understandably, if the pre-stored fixed lines are lines that users frequently access, then when the user moves to a new line, the terminal device may not be able to find a matching serving cell when matching the cell parameters of the cell at the current location with the cell distribution of the fixed lines.

[0103] Therefore, in this case, the user's current line can be redefined as a new fixed line and stored for later use. In some embodiments, the terminal device can perform interpolation processing on the acquired line set to obtain a new fixed line, the line set including the cell parameters of the cell at the current location, multiple historical locations, and the cell parameters of the cell at each historical location.

[0104] In other words, the terminal device can form a sampling location set by combining the location coordinates of multiple historical locations, the cell parameters of each historical location, and the cell parameters of the current location; then, the sampling location set can be interpolated using an interpolation method to obtain an interpolated location set, thereby combining the sampling location set and the interpolated location set to obtain the cell distribution of the new fixed line.

[0105] Of course, in other embodiments, the terminal device obtains a set of sampled locations based on the location coordinates of multiple historical locations and the cell parameters of each historical location, as well as the cell parameters of the current location. After interpolating the sampled location set to obtain an interpolated location set, a prediction algorithm can be used to predict the location coordinates of multiple locations of the terminal device in the future time period and the cell parameters of each location. Interpolation is then performed on the multiple locations in the future time period to obtain multiple interpolated locations in the future time period. Thus, by combining the sampled location set, the interpolated location set, the multiple locations in the future time period, and the multiple interpolated locations in the future time period, a new cell distribution of the fixed line can be obtained.

[0106] In this embodiment, the terminal device obtains the cell parameters of the cell at the current location, matches the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines to obtain a matching serving cell; then, based on the signal strength information of the serving cell at at least one matching location and the signal strength information of the serving cell at the current location, it determines the target location from at least one matching location, and determines the location coordinates of the target location as the location coordinates of the current location.

[0107] In this way, on the one hand, since there is no need to obtain GPS and base station information from the terminal device, only the cell parameters of the cell at the current location need to be collected, which can reduce the power consumption of the terminal device; and the positioning based on the identification information and / or signal strength information in the cell parameters is more accurate than considering only the cell identification information. On the other hand, when constructing a fixed line, the line can be accurately constructed with less sampling data, thereby improving the comparison accuracy when comparing it with the cell parameters of the cell at the current location of the terminal device, and thus improving the positioning accuracy of the terminal device.

[0108] In this embodiment of the application, after determining the current location coordinates of the terminal device by executing steps 101 to 103 and steps 401 to 404 in the above embodiments, the method for optimizing service requirements of the terminal device in the following embodiments can also be executed.

[0109] Figure 7 This is a schematic diagram illustrating the implementation flow of the optimization method provided in an embodiment of this application. For example... Figure 7 As shown, the method may include the following steps:

[0110] Step 701: Obtain the location coordinates of the problem area in the fixed line corresponding to the current location. The problem area is the area where the signal strength information of the cell is less than the strength threshold.

[0111] Here, the distribution of fixed-line cells can also include locations with signal lag, low signal transmission speed, and low user experience scores. These locations are characterized by the signal strength of the corresponding cells being less than the strength threshold. The locations where the above situations occur can be collectively referred to as problem locations, and the areas where the problem locations are located can be referred to as problem areas.

[0112] It is evident that the distribution of residential areas can also reflect the location coordinates of the problem area.

[0113] Therefore, after determining the current location coordinates of the terminal device, the problem area can also be obtained from the cell distribution of the corresponding fixed line.

[0114] Step 702: Based on the current location coordinates and the location coordinates of the terminal device in the historical time period, predict the location coordinates at each moment in the future time period.

[0115] In the embodiments of this application, the specific implementation method for the terminal device to predict its location coordinates at each moment in the future time period is not limited. For example, a neural network model can be used for prediction; or, a linear regression method can be used for prediction; or, a Kalman filter can be used for prediction; or, a probabilistic graphical model can be used for prediction, etc.

[0116] Deep neural network architectures can effectively process high-dimensional data, exhibiting good robustness and generalization ability, and can stably output results even when the input data contains noise and distortion. It can automatically extract important features from the data through structures such as convolution kernels, pooling operations, and memory gates, eliminating the need for manual feature engineering. Furthermore, it has low computational and space complexity, making it suitable for large-scale data processing and real-time applications, and capable of accurately predicting the location of terminal devices in the future.

[0117] In some embodiments, the example is taken where the terminal device uses a neural network model to predict the location coordinates at each time point in a future time period.

[0118] In implementation, the terminal device can first collect its location coordinates at each moment within a historical period. This location data can be obtained through GPS positioning, terminal device positioning, Wi-Fi positioning, etc. Subsequently, the collected location coordinates at each moment within the historical period can be preprocessed to make them scale-aligned. This preprocessing can be normalization or standardization, etc., ensuring that the processed coordinate data remains at the same scale. Finally, the processed coordinate data can be input into a pre-trained trajectory prediction model to predict the location coordinates of the terminal device at each moment within a future period.

[0119] The neural network model can be a Long Short Term Memory (LSTM) recurrent neural network model, or it can be a Transformer model, etc. The embodiments of this application do not limit this.

[0120] Step 703: Based on the location coordinates at each moment in the future time period, the location coordinates of the problem area, and the service requirements of the terminal device, perform optimization operations corresponding to the service requirements. The service requirements include one or more of the following: running real-time services, cell handover services, and power reduction services.

[0121] Here, the service requirements of a terminal device can be its current service requirements or its future service requirements. For example, if the terminal device is currently running a real-time service, then its service requirements in both the current and future periods are considered to be running real-time services; or, if the terminal device's current service is a call service, then it can be predicted that its service requirements in the future periods will be cell handover services to ensure call quality, etc.

[0122] Therefore, if there are problem areas in the current route of the terminal device, optimization operations corresponding to the service needs of the terminal device can be performed based on the service needs of the terminal device and the problem areas. The optimization operations performed on the terminal device will vary depending on the different service needs.

[0123] Figure 8 A schematic diagram of the implementation process of an optimization operation performed by a terminal device is provided, including the following steps:

[0124] Step 801: When the service requirement is to run a real-time service, preload the real-time service based on the distance between the problem area and the current location of the terminal device.

[0125] Here, when it is determined that the terminal device is about to reach the problem area, the real-time services currently running on the terminal device can be preloaded. The preloading time can be the time required for the terminal device to pass through the problem area.

[0126] In this way, by predicting the duration of network degradation on terminal devices in a timely manner, preloading operations can be performed on real-time services in a timely manner, thereby avoiding interruption of the operation of real-time services and improving user experience.

[0127] Step 802: When the service request is cell handover, cell handover processing is performed in advance based on the distance between the problem area and the current location of the terminal device.

[0128] Understandably, when the network signal quality of the current serving cell of a terminal device deteriorates, the terminal device will select a target serving cell from multiple candidate cells nearby and switch from the current serving cell to the target serving cell to ensure the network quality of the terminal device.

[0129] When a terminal device switches from the current serving cell to the target serving cell, due to the handover triggering time and handover delay, the network signal quality of the current serving cell can no longer meet the service requirements of the terminal device from the time the handover event is triggered until the handover is completed.

[0130] Therefore, in this embodiment of the application, the signal quality of the cell at the current location of the terminal device can be combined to trigger the cell handover operation of the terminal device in advance before the terminal device reaches the problem area, thereby ensuring the service quality of the terminal device and realizing the handover of the serving cell dominated by the terminal device.

[0131] Step 803: When the service request is to reduce power consumption, if the problem area is reached, the time interval for searching the network is increased; if the problem area is left, the time interval for searching the network is shortened.

[0132] Understandably, if a terminal device reaches a problem area where the network signal quality of the target serving cell is poor, it is highly likely that the terminal device will not be able to find a serving cell with good network signal quality if it frequently searches for networks. Therefore, the terminal device can be controlled to increase the time interval for searching networks in order to reduce the power consumption of the terminal device.

[0133] If the terminal device leaves the problem area, the network signal quality of the serving cell where the terminal device is located is likely to be relatively good. Therefore, the time interval for the terminal device to search for the network can be shortened to search for the network in a timely manner and improve the network quality of the terminal device.

[0134] In the embodiments of this application, when performing optimization operations on various service requirements of the terminal device, the timing of the optimization operations is not limited, and they can be executed in parallel, sequentially, or selectively.

[0135] In this embodiment, when locating the terminal device, the cell parameters of the cell at the current location are matched with the cell parameters of multiple locations on a known fixed line. Upon successful matching, a location is selected as the terminal device's current location within the coverage area of ​​the matched serving cell. This approach offers several advantages. First, since it eliminates the need for GPS and base station information, requiring only the cell parameters of the cell at the current location, it reduces power consumption. Furthermore, positioning based on the cell identifier and / or signal strength information within the cell parameters provides higher accuracy compared to considering only the cell identifier. Second, when constructing a fixed line, precise line construction with less sampling data is achieved, improving comparison accuracy when comparing with the cell parameters of the cell at the terminal device's current location, thereby enhancing the terminal device's positioning accuracy.

[0136] Furthermore, after determining its current location coordinates, the terminal device can also perform corresponding optimization operations on its own service needs based on the relationship between the terminal device's current location and the location of the problem area, thereby improving the user experience.

[0137] Understandably, in this embodiment of the application, when locating the terminal device, the cell parameters of the cell at the current location of the terminal device are compared with the cell distribution of the existing fixed lines to determine the location coordinates of the current location. Therefore, to implement the positioning method provided in this embodiment of the application, it is necessary to first obtain the cell distribution of the fixed lines, that is, to first construct the fixed lines.

[0138] Based on this, this application embodiment provides another method for constructing a fixed line. Figure 9 This is a schematic diagram illustrating the implementation flow of the method for constructing a fixed line provided in an embodiment of this application. Figure 9 As shown, the method may include the following steps:

[0139] Step 901: Obtain a set of sampling locations. The set of sampling locations includes the location coordinates of multiple sampling locations and the cell parameters of the cell at each sampling location. The cell at each sampling location includes the serving cell and multiple neighboring cells. The cell parameters include identification information and / or signal strength information.

[0140] In this embodiment of the application, the data acquisition system in the terminal device can periodically or as needed collect a set of sampling locations. The set of sampling locations includes multiple sampling locations, and each sampling location includes the serving cell and multiple neighboring cells.

[0141] During data collection, the location coordinates of each sampling location are collected, which can be the longitude and latitude of the sampling location; as well as the identification information and signal strength information of the serving cell at each sampling location, and the identification information and signal strength information of each neighboring cell at each sampling location are collected.

[0142] In this embodiment of the application, the cell identification information may include ECI, PCI, MCC, MNC, ARFCN, etc.; the cell signal strength information may include RSRP, service type, RSSI, etc.

[0143] In some embodiments, after obtaining the set of sampling locations, the set of sampling locations can be stored in the data storage and processing unit of the terminal device for later use. The data acquisition system running in the terminal device will periodically or as needed by the user to send requests to the data storage and processing unit.

[0144] In this embodiment of the application, the entity that constructs the fixed line is not limited. For example, the fixed line can be constructed by the terminal device itself or by the server.

[0145] When constructing a fixed-line connection via a server, a set of sampling locations can be obtained for the terminal devices. This set of locations can then be encrypted and compressed before being uploaded to the server. The server then uses a database system to save the data in a suitable format, such as a relational database, NoSQL database, or data lake. The server can process and analyze the saved data, planning the next stage of data collection based on the amount of data collected from each user, the location distribution, and the number of covered cells. Data collection instructions are then sent to each terminal, which begins the next stage of data collection upon receiving the instructions. Furthermore, the server can also construct a fixed-line connection based on the received set of sampling locations.

[0146] When constructing a fixed-line network using terminal devices, the terminal devices can store an original copy of the collected data set used to construct the fixed-line network. The stored data files typically use standard or proprietary file formats, including text files, Extensible Markup Language (XML), JSON, etc., and are then stored according to a hierarchical structure. Each file or folder contains data associated with different geographical regions and communication standards. Subsequently, a database system can be used to store the structured information of the data in the fixed-line network for querying and analysis. Specific data models (such as relational databases, NoSQL databases, etc.) are used to organize and manage the data. Database tables typically include columns for storing information such as geographical coordinates, communication standards, and RSRP values.

[0147] Step 902: Perform interpolation processing on the sampled location set to obtain an interpolated location set, which includes the location coordinates of multiple interpolated locations and the cell parameters of the cell at each interpolated location.

[0148] Understandably, in related technologies, when using radio frequency positioning technology to determine the current location coordinates of a terminal device, it is necessary to pre-build an radio frequency fingerprint database.

[0149] Constructing an RF fingerprint database requires extensive RF signal measurements and the establishment of an RF signal fingerprint model for each location point using interpolation algorithms. Commonly used interpolation algorithms, such as K-nearest neighbor interpolation and radial basis function interpolation, typically have the following problems:

[0150] Lack of uncertainty estimation: Many traditional interpolation algorithms typically only provide interpolation results for point estimates, without providing information on the uncertainties associated with the estimates. This makes it difficult to assess the reliability of the interpolation results, while uncertainty estimation is crucial in some applications.

[0151] Assumptions about the data structure: Some interpolation methods may require explicit assumptions about the form of the interpolation function or the distribution of the data. If the data does not conform to these assumptions, the performance of the fingerprint algorithm may be affected.

[0152] Not suitable for noisy data: Some interpolation methods are not suitable for data containing noise. In practical applications, data is often affected by measurement errors or random noise.

[0153] Data efficiency issues: Some interpolation algorithms may be sensitive to the amount and distribution of data, and therefore perform poorly on small or sparse datasets.

[0154] The interpolation method needs to be manually selected: When using traditional interpolation methods, it is necessary to manually select the interpolation function type and parameters suitable for the specific problem, which may require some experience and experimentation.

[0155] Therefore, in order to solve the problems existing in the above interpolation processing method, in the embodiments of this application, such as Figure 10 As shown, an interpolation processing method is provided, including the following steps 1001 to 1003. In this method, the joint distribution of the data is modeled by Gaussian distribution, the correlation between data points is described by covariance function, Bayesian inference is used to estimate model parameters, and a posterior distribution is generated, which overcomes the problems of data noise and insufficient data volume.

[0156] Step 1001: Group the multiple sampling locations in the sampling location set to obtain multiple sub-sampling location sets, where the difference between the position coordinates of the sampling locations in each sub-sampling location set is less than a distance threshold.

[0157] Understandably, the number of sampling locations included in the set of sampling locations obtained by the terminal device may be large. Therefore, if interpolation is directly performed on multiple sampling locations, it will be difficult to implement, slow to process, and inefficient.

[0158] Based on this, in this embodiment of the application, after the terminal device obtains the set of sampling locations, it can group multiple sampling locations to obtain multiple sets of sub-sampling locations. Specifically, when grouping the sampling locations, sampling locations that are close to each other can be grouped together based on the location coordinates of each sampling location.

[0159] Specifically, the set of sub-sampling locations after partitioning can be used... Here, Q represents the total number of sampling locations in the sub-sampling location set.

[0160] Figure 11 A schematic diagram illustrating the effect of grouping a set of sampling locations into multiple sub-sets of sampling locations is provided. For example... Figure 11 As shown, the set of sampling locations can be divided into sub-sampling location set 1, sub-sampling location set 2, and sub-sampling location set 3.

[0161] Step 1002: For each sub-sampling location set, construct a Gaussian process based on the location coordinates of multiple sampling locations in the sub-sampling location set and the cell parameters of the cell.

[0162] In this embodiment, Gaussian regression is used to interpolate the sampling locations. In Gaussian regression, an appropriate Gaussian process must first be selected for modeling. A Gaussian process is a stochastic process that can be viewed as a continuous probability distribution used to describe the distribution of the target variable in the input space. The behavior of the Gaussian process is defined by the covariance function (also called the kernel function). The covariance function determines the correlation between data points. Different covariance functions can be used to capture different data patterns. Common covariance functions include linear kernels and radial basis function kernels.

[0163] Based on this, in the embodiments of this application, for each sub-sampling location set A set can be constructed based on the location coordinates of each sampling location in the sub-sampling location set and the cell parameters of the cell. Then, a Gaussian process is constructed based on the signal strength information of the cell at each sampling location and the location coordinates of the sampling location. This Gaussian process uses... Let m(c) represent the mean function and k(c,c′) represent the covariance function. These mean and covariance functions can be used to characterize the correspondence between the location coordinates of multiple sampling locations in the sub-sampling location set and the cell parameters of the cell.

[0164] Step 1003: Based on the Gaussian process, the signal strength information of cells at multiple sampling locations, and the covariance function, determine the position coordinates of each interpolation location in the sub-interpolation location set corresponding to the sub-sampling location set and the cell parameters of the cell. The covariance function is used to characterize the correspondence between the position coordinates of multiple sampling locations in the sub-sampling location set and the cell parameters of the cell.

[0165] In some embodiments, a method for determining the interpolation position is provided to implement step 1003, the method comprising the following steps 1201 to 1203:

[0166] Step 1201: Construct a sub-interpolation location set corresponding to the sub-sampling location set. The location coordinates of each interpolation location in the sub-interpolation location set and the cell parameters of the cell are in a state to be solved.

[0167] Understandably, interpolating the sampling locations involves inserting constructed interpolation locations among multiple sampling locations. Therefore, in this embodiment, a sub-interpolation location set corresponding to the sub-sampling location set can be constructed first, but the location coordinates of each interpolation location in this sub-interpolation location set and the cell parameters of the cell are in a state of unsolved. That is, at this time, the location coordinates of each interpolation location in the sub-interpolation location set corresponding to the constructed sub-sampling location set and the cell parameters of the cell are unknown.

[0168] In some embodiments, the constructed sub-interpolation location set is denoted by r(c), which satisfies r(c) = f(c) + ∈, where c is the location coordinate of each interpolation location in the sub-interpolation set, f(c) is the signal strength information of each interpolation location, and ∈ is a zero-mean Gaussian noise.

[0169] Step 1202: Based on the sub-interpolation location set and the Gaussian process, construct a joint Gaussian distribution function. The parameters in the joint Gaussian distribution function include the mean vector, covariance function, and noise variance of the signal strength information of the cells at multiple sampling locations in the sub-sampling location set.

[0170] In some embodiments, a joint Gaussian distribution function is constructed based on the sub-interpolation location set and the Gaussian process, and the resulting joint Gaussian distribution function is shown in Equation (1):

[0171]

[0172] Where, r * This indicates the signal strength information of the cell at the interpolation location. express The mean vector of the interpolation position in μ * This represents the mean value at the interpolation position. With μ *Let it be a set The average signal strength information of the cells at all interpolation locations. It is the covariance function corresponding to the location coordinates of the sampling position. It is the covariance function between the position coordinates of the sampling location and the position coordinates of the interpolation location. K(c) is the covariance function between the position coordinates of the interpolation location and the position coordinates of the sampling location. * ,c * ) is the covariance function between the interpolated position and its own position coordinates. Let I represent the variance of the noise, and let I represent the identity matrix.

[0173] Step 1203: Based on the joint Gaussian distribution function, determine the location coordinates of each interpolation location in the sub-interpolation location set and the cell parameters of the cell through the posterior probability.

[0174] After obtaining the joint Gaussian distribution function, the posterior probability can be used. Determine the location coordinates of each interpolation location in the sub-interpolation location set and the cell parameters of the cell.

[0175] The mean of this Gaussian distribution can be considered an approximation of the signal strength information of the cell at the interpolation location, that is, I can obtain it through... To predict the signal strength information of the cell at the interpolation location.

[0176] Step 903: Combine the sampling location set and the interpolation location set to obtain the cell distribution of the corresponding fixed line.

[0177] After obtaining the sub-interpolation location set corresponding to each sub-sampling location set, multiple sub-interpolation location sets can be combined to obtain the interpolation location set. Thus, the sampling location set and the interpolation location set are merged to obtain the cell distribution of the corresponding fixed line.

[0178] In other embodiments, a probability-based kriging interpolation method can be used to interpolate the set of sampling locations to obtain an interpolated set of locations. For example, it can be calculated by dividing the two sampling locations into five equal parts. The probability-based kriging interpolation method utilizes the spatial correlation of radio frequency coverage to achieve accurate inversion with a small amount of measurement sample data.

[0179] In probability-based kriging interpolation methods, choosing an appropriate semivariogram is crucial for describing the spatial correlation between data points. The semivariogram is typically estimated from the sample semivariogram and used to quantify the degree of variation in data values ​​at different distances.

[0180] The selected semivariogram model is fitted using sample data, and the parameters of the semivariogram, such as variance, lag, direction, and lag threshold, are estimated. The locations to be interpolated are determined based on the trajectory formed by the set of sampling locations of the terminal devices. For each interpolation location, the distance between it and the sampling location is calculated, and then the semivariogram model is used to estimate the semivariogram value, i.e., the variability between data points.

[0181] Then, appropriate weights are assigned to each sampling location based on the distance weights of the semivariogram values. Typically, points that are closer have greater weights because they have a higher influence in the vicinity of the interpolation point. The weights of the sampling locations and the semivariogram values ​​are used to calculate the estimates of the interpolation locations, usually using a weighted average or other interpolation methods. The uncertainty of each interpolation location is calculated, usually estimated using the semivariogram function, and these uncertainty values ​​can be used to assess the confidence of the estimates.

[0182] By implementing this embodiment, the cell distribution of each fixed line can be constructed. The cell distribution includes the location coordinates of the sampling location and the cell parameters of each sampling location, as well as the location coordinates of the interpolation location and the cell parameters of each interpolation location.

[0183] Step 904: Obtain the location coordinates of the new location and the cell parameters of the cell at the new location. The cell parameters include identification information and / or signal strength information.

[0184] Step 905: If no location matching the new location's coordinates is found in the cell distribution of the fixed line, then the new location's coordinates and cell parameters are updated in the cell distribution of the fixed line, and multiple interpolated locations in the fixed line are updated to obtain the updated fixed line.

[0185] Understandably, the data acquisition system in the terminal device will continuously collect cell information of the location of the terminal device. After obtaining the location coordinates of the new location and the cell parameters of the cell at the new location, the relevant information of the new location can be matched with the cell distribution of the fixed line to determine whether the new location exists in the fixed line.

[0186] For example, the location coordinates of the new location can be compared with the location coordinates of multiple locations in the fixed line. If a mismatch is found, the location coordinates of the new location can be merged into the fixed line. In this way, the sampling locations in the cell distribution of the fixed line are updated. Subsequently, based on the updated sampling locations, multiple interpolation locations in the fixed line can also be updated to obtain updated interpolation locations. Thus, by combining the updated sampling locations and the updated interpolation locations, the updated fixed line can be obtained.

[0187] Of course, users may sometimes travel on new routes that are not part of the historically established fixed routes. Therefore, in some embodiments, if the location coordinates of a new location obtained by the terminal device, and the cell parameters of the cell at that new location, cannot be matched with multiple locations on the fixed route, it can be assumed that the user has traveled on a new route, and a corresponding cell distribution can be constructed for that new route.

[0188] Implementing this embodiment provides a method for constructing a fixed line. This method models the joint distribution of data using a Gaussian distribution, describes the correlation between data points using a covariance function, uses Bayesian inference to estimate model parameters, and generates a posterior distribution. It overcomes the problems of data noise and insufficient data volume, performs well when processing small sample datasets, and does not require a large amount of data for interpolation.

[0189] Implementing this embodiment also provides a method for updating the cell distribution of fixed lines, thereby enabling real-time updates of the cell distribution of fixed lines and improving the positioning accuracy of terminal devices.

[0190] It should be understood that although the steps in the above flowcharts are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the above flowcharts may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0191] Based on the foregoing embodiments, this application provides a positioning device, which includes various modules and units included in each module, and can be implemented by a processor; of course, it can also be implemented by specific logic circuits; in the implementation process, the processor can be a central processing unit (CPU), microprocessor (MPU), digital signal processor (DSP) or field programmable gate array (FPGA), etc.

[0192] Figure 13 This is a schematic diagram of the positioning device provided in the embodiments of this application, as shown below. Figure 13 As shown, the device 1300 includes an acquisition module 1301, a matching module 1302, and a determination module 1303, wherein:

[0193] The acquisition module 1301 is used to acquire the cell parameters of the cell at the current location. The cell at the current location includes the serving cell and multiple neighboring cells. The cell parameters include identification information and / or signal strength information.

[0194] The matching module 1302 is used to match the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines to obtain a matching serving cell. The matching serving cell has the same identification information as the serving cell at the current location. The cell distribution of the fixed lines includes the location coordinates of multiple locations in the fixed lines and the cell parameters of each location. The multiple locations include the acquisition location and the interpolation location. The interpolation location is obtained by interpolating the acquisition location.

[0195] The determining module 1303 is used to determine the location coordinates of the current location based on the cell parameters of the cell at the current location, the cell parameters of cells at multiple candidate locations within the coverage area of ​​the matching serving cell, and the location coordinates of the multiple candidate locations.

[0196] In some embodiments, the determining module 1303 includes a first determining submodule and a second determining submodule;

[0197] The first determining submodule is used to determine at least one matching location from multiple candidate locations within the coverage area of ​​the matching service cell based on the identification information of multiple neighboring cells of the current location, wherein the identification information of the neighboring cells of the matching location is the same as the identification information of one of the multiple neighboring cells of the current location.

[0198] The second determining submodule is used to determine a target location from at least one matching location based on the signal strength information of the serving cell of at least one matching location and the signal strength information of the serving cell of the current location, and to determine the location coordinates of the target location as the location coordinates of the current location.

[0199] In some embodiments, the second determining submodule is specifically used to determine the signal strength difference between the signal strength information of the serving cell at the at least one matching location and the signal strength information of the serving cell at the current location; and to determine the candidate location corresponding to the smallest signal strength difference among at least one of the signal strength differences as the target location.

[0200] In some embodiments, the apparatus further includes a prediction module and an optimization module;

[0201] The acquisition module 1301 is also used to acquire the location coordinates of the problem area in the fixed line corresponding to the current location, wherein the problem area is the area where the signal strength information of the cell is less than the strength threshold;

[0202] The prediction module is used to predict the location coordinates at each moment in the future time period based on the current location coordinates and the location coordinates of the terminal device in the historical time period.

[0203] The optimization module is used to perform optimization operations corresponding to the service requirements based on the location coordinates at each moment in the future time period, the location coordinates of the problem area, and the service requirements of the terminal device. The service requirements include one or more of the following: running real-time services, cell handover services, and power reduction services.

[0204] In some embodiments, the optimization module is specifically configured to: when the service requirement is to run a real-time service, preload the real-time service based on the distance between the problem area and the current location of the terminal device; or, when the service requirement is cell handover, perform cell handover in advance based on the distance between the problem area and the current location of the terminal device; or, when the service requirement is to reduce power consumption, increase the network search time interval if the device reaches the problem area, and shorten the network search time interval if the device leaves the problem area.

[0205] In some embodiments, the apparatus further includes a first processing module and a second processing module;

[0206] The acquisition module 1301 is further configured to acquire a set of sampling locations, the set of sampling locations including the location coordinates of multiple sampling locations and the cell parameters of the cell at each sampling location, the cell at each sampling location including the serving cell and multiple neighboring cells, and the cell parameters including identification information and / or signal strength information;

[0207] The first processing module is used to perform interpolation processing on the sampling location set to obtain an interpolated location set, wherein the interpolated location set includes the location coordinates of multiple interpolated locations and the cell parameters of the cell at each interpolated location;

[0208] The second processing module is used to combine the sampling location set and the interpolation location set to obtain the cell distribution of the corresponding fixed line.

[0209] In some embodiments, the first processing module further includes a grouping module, a building module, and a processing submodule;

[0210] The grouping module is used to group multiple sampling locations in the sampling location set to obtain multiple sub-sampling location sets, wherein the difference between the position coordinates of the sampling locations in each sub-sampling location set is less than a distance threshold.

[0211] The construction module is used to construct a Gaussian process for each of the sub-sampling location sets, based on the location coordinates of multiple sampling locations in the sub-sampling location set and the cell parameters of the cell.

[0212] The processing submodule is used to determine the position coordinates of each interpolation position and the cell parameters of the cell in the sub-interpolation position set corresponding to the sub-sampling position set, based on the Gaussian process, the signal strength information of the cells at the multiple sampling positions, and the covariance function. The covariance function is used to characterize the correspondence between the position coordinates of the multiple sampling positions and the cell parameters of the cells in the sub-sampling position set.

[0213] In some embodiments, the processing submodule includes a first construction submodule, a second construction submodule, and a third determination submodule;

[0214] The first construction submodule is used to construct the sub-interpolation location set corresponding to the sub-sampling location set, wherein the location coordinates of each interpolation location in the sub-interpolation location set and the cell parameters of the cell are in a state to be solved;

[0215] The second construction submodule is used to construct a joint Gaussian distribution function based on the sub-interpolation location set and the Gaussian process. The parameters in the joint Gaussian distribution function include the mean vector of the signal strength information of the cells at multiple sampling locations in the sub-sampling location set, the covariance function, and the noise variance.

[0216] The third determining submodule is used to determine the location coordinates of each interpolation position in the sub-interpolation position set and the cell parameters of the cell based on the joint Gaussian distribution function and the posterior probability.

[0217] In some embodiments, the apparatus further includes an update module;

[0218] The acquisition module 1301 is also used to acquire the location coordinates of the new location and the cell parameters of the cell at the new location, wherein the cell parameters include identification information and / or signal strength information;

[0219] The update module is used to update the location coordinates of the new location and the cell parameters of the cell in the cell distribution of the fixed line if no location matching the location coordinates of the new location is found in the cell distribution of the fixed line, and to update multiple interpolated locations in the fixed line to obtain the updated fixed line.

[0220] In some embodiments, the apparatus further includes a third processing module;

[0221] The third processing module is used to match the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines. If no matching serving cell is obtained, the module performs interpolation processing on the obtained line set to obtain a new fixed line. The line set includes the cell parameters of the cell at the current location, multiple historical locations, and the cell parameters of the cell at each historical location.

[0222] In some embodiments, the matching module 1302 includes a fourth determining submodule, a fifth determining submodule, and a matching submodule;

[0223] The fourth determining submodule is used to determine the area identifier of the current location based on the identifier information of the serving cell at the current location.

[0224] The fifth determining submodule is used to determine a target fixed line from multiple fixed lines based on the area identifier, wherein the identifier of the target fixed line is the same as the area identifier;

[0225] The matching submodule is used to match the cell parameters of the serving cell at the current location with the cell distribution of the target fixed line to obtain the matching serving cell.

[0226] In some embodiments, the fifth determining submodule is specifically used to send a loading request to the server, so that the server responds to the loading request, selects a target fixed line from the plurality of fixed lines, and sends the cell distribution information of the target fixed line to the terminal device. The loading request includes the area identifier, and the identifier of the target fixed line is the same as the area identifier.

[0227] In some embodiments, the fifth determining submodule is further configured to search for the target fixed line from a plurality of pre-stored fixed lines based on the area identifier, wherein the identifier of the target fixed line is the same as the area identifier.

[0228] The descriptions of the above device embodiments are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0229] It should be noted that, in the embodiments of this application... Figure 13The module division shown in the positioning device is illustrative and represents only one logical functional division; in actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, exist as separate physical units, or be integrated into one unit with two or more units. The integrated units can be implemented in hardware, as software functional units, or a combination of both.

[0230] It should be noted that, in the embodiments of this application, if the above-described methods are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0231] This application provides a computer device, which may be a server, and its internal structure diagram may be as follows: Figure 14 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the methods described above.

[0232] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method provided in the above embodiments.

[0233] This application provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the steps in the method provided in the above-described method embodiments.

[0234] Those skilled in the art will understand that Figure 14The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0235] In one embodiment, the positioning device provided in this application can be implemented as a computer program, and the computer program can be implemented in such a way as... Figure 14 The device operates on the computer device shown. The memory of the computer device can store the various program modules that make up the above-described apparatus. The computer program, composed of the various program modules, causes the processor to execute the steps of the methods in the various embodiments of this application described in this specification.

[0236] It should be noted that the descriptions of the storage medium and device embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium, storage medium, and device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0237] It should be understood that the phrases "one embodiment," "an embodiment," or "some embodiments" mentioned throughout the specification mean that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment," "in one embodiment," or "in some embodiments" appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. The descriptions of the various embodiments above tend to emphasize the differences between the various embodiments; their similarities or commonalities can be referred to mutually, and for the sake of brevity, they will not be repeated here.

[0238] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three kinds of relationships. For example, object A and / or object B can represent three situations: object A exists alone, object A and object B exist simultaneously, and object B exists alone.

[0239] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0240] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or modules can be electrical, mechanical, or other forms.

[0241] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules. They may be located in one place or distributed across multiple network units. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0242] In addition, each functional module in the various embodiments of this application can be integrated into one processing unit, or each module can be a separate unit, or two or more modules can be integrated into one unit; the integrated modules can be implemented in hardware or in the form of hardware plus software functional units.

[0243] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0244] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0245] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0246] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0247] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0248] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A positioning method, characterized in that, Applied to a terminal device, the method includes: Obtain the cell parameters of the cell at the current location, wherein the cell at the current location includes the serving cell and multiple neighboring cells, and the cell parameters include identification information and / or signal strength information; The cell parameters of the serving cell at the current location are matched with the cell distribution of multiple fixed lines to obtain a matching serving cell. The matching serving cell has the same identification information as the serving cell at the current location. The cell distribution of the fixed lines includes the location coordinates of multiple locations in the fixed lines and the cell parameters of each location. The multiple locations include the acquisition location and the interpolation location. The interpolation location is obtained by interpolating the acquisition location. The difference between the location coordinates of the acquisition location and the interpolation location is less than a distance threshold. Based on the identification information of multiple neighboring cells of the current location, at least one matching location is determined from multiple candidate locations within the coverage area of ​​the matching service cell. The identification information of the neighboring cells of the matching location is the same as the identification information of one of the multiple neighboring cells of the current location. The candidate location is a preset reference location. Determine the signal strength difference between the signal strength information of the serving cell at the at least one matching location and the signal strength information of the serving cell at the current location; The candidate position corresponding to the smallest signal strength difference among at least one of the signal strength differences is determined as the target position, and the position coordinates of the target position are determined as the position coordinates of the current position; The step of matching the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines to obtain the matching serving cell includes: Based on the identifier information of the serving cell at the current location, the area identifier of the area is determined; based on the area identifier, a target fixed line is determined from multiple fixed lines, the identifier of the target fixed line being the same as the area identifier; based on the cell parameters of the serving cell at the current location, the cell distribution of the target fixed line is matched to obtain the matched serving cell.

2. The method according to claim 1, characterized in that, After determining the position coordinates of the current location, the method further includes: Obtain the location coordinates of the problem area in the fixed line corresponding to the current location, where the problem area is the region where the signal strength information of the cell is less than the strength threshold; Based on the current location coordinates and the terminal device's location coordinates within a historical time period, the location coordinates at each moment in the future time period are predicted. Based on the location coordinates at each moment within the future time period, the location coordinates of the problem area, and the service requirements of the terminal device, optimization operations corresponding to the service requirements are executed. The service requirements include one or more of the following: running real-time services, cell handover services, and power reduction services.

3. The method according to claim 2, characterized in that, The step of performing optimization operations corresponding to the service requirements based on the location coordinates at each moment within the future time period, the location coordinates of the problem area, and the service requirements of the terminal device includes: When the service requirement is to run a real-time service, the real-time service is preloaded based on the distance between the problem area and the current location of the terminal device; or, When the service request is cell handover, cell handover processing is performed in advance based on the distance between the problem area and the current location of the terminal device; or, When the service request is to reduce power consumption, if the system reaches the problem area, the time interval for searching the network is increased; if the system leaves the problem area, the time interval for searching the network is shortened.

4. The method according to claim 1, characterized in that, Before obtaining the cell parameters of the cell at the current location, the method further includes: Obtain a set of sampling locations, which includes the location coordinates of multiple sampling locations and the cell parameters of the cell at each sampling location. The cell at each sampling location includes the serving cell and multiple neighboring cells. The cell parameters include identification information and / or signal strength information. The sampling location set is interpolated to obtain an interpolated location set, which includes the location coordinates of multiple interpolated locations and the cell parameters of the cell at each interpolated location; By combining the sampling location set and the interpolation location set, the cell distribution of the corresponding fixed line is obtained.

5. The method according to claim 4, characterized in that, The step of interpolating the sampled location set to obtain the interpolated location set includes: Multiple sampling locations in the sampling location set are grouped to obtain multiple sub-sampling location sets, and the difference between the position coordinates of the sampling locations in each sub-sampling location set is less than a distance threshold. For each set of sub-sampling locations, a Gaussian process is constructed based on the location coordinates of multiple sampling locations in the set of sub-sampling locations and the cell parameters of the cell. The covariance function of the Gaussian process adopts a radial basis function kernel. Based on the Gaussian process, the signal strength information of the cells at the multiple sampling locations, and the covariance function, the position coordinates of each interpolation location in the sub-interpolation location set corresponding to the sub-sampling location set and the cell parameters of the cell are determined. The covariance function is used to characterize the correspondence between the position coordinates of the multiple sampling locations in the sub-sampling location set and the cell parameters of the cell.

6. The method according to claim 5, characterized in that, The step of determining the position coordinates of each interpolation position and the cell parameters of the cell in the sub-interpolation position set corresponding to the sub-sampling position set based on the Gaussian process, the signal strength information of the cells at the multiple sampling positions, and the covariance function includes: Construct the sub-interpolation location set corresponding to the sub-sampling location set, where the location coordinates of each interpolation location in the sub-interpolation location set and the cell parameters of the cell are in a state of unsolved; Based on the sub-interpolation location set and the Gaussian process, a joint Gaussian distribution function is constructed. The parameters in the joint Gaussian distribution function include the mean vector of the signal strength information of the cells at multiple sampling locations in the sub-sampling location set, the covariance function, and the noise variance. Based on the joint Gaussian distribution function, the location coordinates of each interpolation position in the sub-interpolation location set and the cell parameters of the cell are determined by the posterior probability. The joint Gaussian distribution function is shown below: ； This is the signal strength information of the cell at the interpolation location. for The mean vector of the interpolation positions in the vector. The mean of the interpolation positions. and For the set of sub-sampling locations The average signal strength information of the cells at all interpolation locations. Let covariance be the function corresponding to the location coordinates of the sampling position. Let be the covariance function between the position coordinates of the sampling location and the position coordinates of the interpolation location. Let be the covariance function between the position coordinates of the interpolation location and the position coordinates of the sampling location. Let be the covariance function between the interpolated position and its own position coordinates. Let Variance be the noise variance. It is the identity matrix; The posterior probability is The mean of the Gaussian distribution is the signal strength information of the cell at the interpolation position. The mean of the Gaussian distribution is obtained through... Calculated.

7. The method according to claim 4, characterized in that, After obtaining the cell distribution information for the corresponding fixed lines, the method further includes: Obtain the location coordinates of the new location and the cell parameters of the cell at the new location, wherein the cell parameters include identification information and / or signal strength information; If no location matching the new location's coordinates is found in the cell distribution of the fixed line, the new location's coordinates and cell parameters are updated in the cell distribution of the fixed line, and multiple interpolated locations in the fixed line are updated to obtain the updated fixed line.

8. The method according to claim 1, characterized in that, The method further includes: If the cell parameters of the serving cell at the current location are matched with the cell distribution of multiple fixed lines and no matching serving cell is found, a set of sampling locations is obtained. The set of sampling locations includes the cell parameters of the cell at the current location, multiple historical locations, and the cell parameters of the cell at each historical location. Based on the method described in claims 5 to 6, the sampling location set is interpolated to obtain an interpolated location set; By combining the sampled location set and the interpolated location set, a new fixed route is obtained. The new fixed route is stored for subsequent use, and the historical location is the location that the user has already passed through on the new fixed route.

9. The method according to claim 1, characterized in that, The step of determining the target fixed line from multiple fixed lines based on the area identifier includes: A loading request is sent to the server, so that the server responds to the loading request, selects a target fixed line from the plurality of fixed lines, and sends the cell distribution information of the target fixed line to the terminal device. The loading request includes the area identifier, and the identifier of the target fixed line is the same as the area identifier.

10. The method according to claim 9, characterized in that, The step of determining the target fixed line from multiple fixed lines based on the area identifier includes: Based on the area identifier, the target fixed line is located from a plurality of pre-stored fixed lines, wherein the identifier of the target fixed line is the same as the area identifier.

11. A positioning device, characterized in that, include: The acquisition module is used to acquire the cell parameters of the cell at the current location. The cell at the current location includes the serving cell and multiple neighboring cells. The cell parameters include identification information and / or signal strength information. The matching module is used to match the cell parameters of the serving cell at the current location with the cell distribution of multiple fixed lines to obtain a matching serving cell. The matching serving cell has the same identification information as the serving cell at the current location. The cell distribution of the fixed lines includes the location coordinates of multiple locations in the fixed lines and the cell parameters of each location. The multiple locations include a collection location and an interpolation location. The interpolation location is obtained by interpolating the collection location. The difference between the location coordinates of the collection location and the interpolation location is less than a distance threshold. The determining module is configured to determine at least one matching location from multiple candidate locations within the coverage area of ​​the matching serving cell based on the identification information of multiple neighboring cells of the current location, wherein the identification information of the neighboring cells of the matching location is the same as the identification information of one of the multiple neighboring cells of the current location, and the candidate location is a preset reference location; determine the signal strength difference between the signal strength information of the serving cell of the at least one matching location and the signal strength information of the serving cell of the current location; determine the candidate location corresponding to the smallest signal strength difference among the at least one signal strength difference as the target location, and determine the location coordinates of the target location as the location coordinates of the current location; The matching module is further configured to determine the area identifier of the current location based on the identifier information of the serving cell of the current location; determine a target fixed line from multiple fixed lines based on the area identifier, wherein the identifier of the target fixed line is the same as the area identifier; and match the cell distribution of the target fixed line with the cell parameters of the serving cell of the current location to obtain the matching serving cell.

12. A computer device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1 to 10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 10.

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