Terminal positioning method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of indoor positioning, in particular to a terminal positioning method and device, computer equipment and a storage medium. The method comprises the steps of obtaining a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature comprises a channel estimation matrix, a signal power parameter and a base station distance parameter; selecting a first reference fingerprint feature from at least one candidate fingerprint feature stored in a first fingerprint database, wherein the feature similarity between the first reference fingerprint feature and the first target fingerprint feature is greater than a similarity threshold; wherein the first fingerprint database is a fingerprint database corresponding to the first frequency; and under the condition that the number of the first reference fingerprint feature is one, taking the candidate terminal position corresponding to the first reference fingerprint feature as a target terminal position of the target terminal in the target area. According to the invention, efficient terminal position positioning operation is realized, and the position positioning precision of the target terminal in the target area is ensured.

Description

Technical Field

[0001] The present application relates to the field of indoor positioning technology, and in particular to a terminal positioning method, device, computer equipment and storage medium. Background Art

[0002] Indoor positioning technology plays an extremely important role in certain specific fields. For example, in indoor environments such as factories, accurate indoor positioning technology plays a very critical role in factory operations and product production.

[0003] However, Wi-Fi positioning in traditional technology is a positioning method that estimates the location by analyzing the signal strength between a device and multiple access points. Although the Wi-Fi positioning method can realize indoor positioning operations, the positioning accuracy is limited and cannot meet the high-precision indoor positioning requirements in some scenarios. Summary of the invention

[0004] Based on this, it is necessary to provide a terminal positioning method, device, computer equipment and storage medium that can meet the high-precision indoor positioning requirements in some scenarios in response to the above technical problems.

[0005] In a first aspect, the present application provides a terminal positioning method. The method comprises:

[0006] Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0007] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in a first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to a first frequency;

[0008] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0009] In one of the embodiments, when the number of the first reference fingerprint features is at least two, obtaining a second target fingerprint feature obtained by the target terminal based on a second frequency;

[0010] The target terminal position of the target terminal in the target area is determined according to the second target fingerprint feature and the second fingerprint library; wherein the second fingerprint library is a fingerprint library corresponding to the second frequency.

[0011] In one of the embodiments, a second reference fingerprint feature whose feature similarity with the second target fingerprint feature is greater than a similarity threshold is selected from at least one candidate fingerprint feature stored in the second fingerprint library;

[0012] If the number of the second reference fingerprint feature is one, the candidate terminal position corresponding to the second reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0013] In one of the embodiments, the target area is divided into grids, and grid intersections in the gridded target area are all used as candidate terminal locations; wherein the number of the grid intersections is at least one;

[0014] Determining antenna deployment locations within the target area;

[0015] Performing simulated network coverage on at least one candidate terminal location based on the antenna deployment position to obtain a candidate fingerprint feature of at least one candidate terminal location;

[0016] A first fingerprint library is constructed based on at least one candidate terminal location and at least one candidate fingerprint feature corresponding to the candidate terminal location.

[0017] In one of the embodiments, at least one candidate deployment location is determined from the target area, and network coverage is simulated for at least one candidate terminal location based on each of the candidate deployment locations;

[0018] Determine an initial fingerprint feature corresponding to at least one candidate terminal position when each of the candidate deployment positions is subjected to simulated network coverage;

[0019] Determine the comprehensive fingerprint difference corresponding to each candidate deployment location according to the initial fingerprint feature corresponding to at least one candidate terminal location when each candidate deployment location performs simulated network coverage;

[0020] The candidate deployment position with the largest comprehensive fingerprint difference among the candidate deployment positions is used as the antenna deployment position.

[0021] In one embodiment, the initial fingerprint feature includes initial fingerprint sub-features of at least two dimensions, and the number of the candidate terminal positions is at least two; the determining of the comprehensive fingerprint difference corresponding to each candidate deployment position according to the initial fingerprint feature corresponding to at least one candidate terminal position when simulating network coverage at each candidate deployment position includes:

[0022] For each candidate deployment location, when simulating network coverage based on the candidate deployment location, the initial fingerprint sub-features of the same dimension corresponding to each candidate terminal location are subjected to pairwise difference operations to obtain difference operation results corresponding to the initial fingerprint sub-features of each dimension;

[0023] According to the preset weights corresponding to the initial fingerprint sub-features of each dimension, weighted operations are performed on the difference operation results corresponding to the initial fingerprint sub-features of each dimension to obtain the comprehensive fingerprint differences corresponding to the candidate deployment positions.

[0024] In a second aspect, the present application also provides a terminal positioning device. The device comprises:

[0025] An acquisition module, used to acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0026] A selection module, configured to select a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in a first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to a first frequency;

[0027] The determination module is configured to use, when the number of the first reference fingerprint features is one, the candidate terminal position corresponding to the first reference fingerprint feature as the target terminal position of the target terminal in the target area.

[0028] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0029] Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0030] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in a first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to a first frequency;

[0031] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0032] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0033] Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0034] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in a first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to a first frequency;

[0035] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0036] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0037] Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0038] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in a first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to a first frequency;

[0039] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0040] The terminal positioning method, device, computer equipment and storage medium obtain the first target fingerprint feature obtained by the target terminal located in the target area based on the first frequency, and select the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library. Then, when the number of the first reference fingerprint features is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area. According to the above content, the present application determines the first target fingerprint feature to achieve the wireless network coverage information corresponding to the target terminal at the location through the channel estimation matrix, the signal power parameter and the distance parameter from the base station. Then, according to at least one candidate fingerprint feature stored in the first fingerprint library, each candidate fingerprint feature is used to characterize the wireless network coverage information at different locations in the target area, and determines the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold. Since the first reference instruction feature is similar to the first target fingerprint feature, and the number of the first reference fingerprint features is one, it can be considered that the candidate terminal position corresponding to the first reference fingerprint feature is the target terminal position, thereby realizing an efficient terminal position positioning operation and ensuring the position positioning accuracy of the target terminal in the target area. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] FIG1 is a diagram of an application environment of a terminal positioning method provided by an embodiment of the present application;

[0042] FIG2 is a schematic diagram of a flow chart of a first terminal positioning method provided in an embodiment of the present application;

[0043] FIG3 is a schematic diagram of a flow chart of a second terminal positioning method provided in an embodiment of the present application;

[0044] FIG4 is a schematic diagram of a flow chart of a third terminal positioning method provided in an embodiment of the present application;

[0045] FIG5 is a schematic diagram of a gridded target area provided in an embodiment of the present application;

[0046] FIG6 is a schematic diagram of a flow chart of a fourth terminal positioning method provided in an embodiment of the present application;

[0047] FIG7 is a structural block diagram of a terminal positioning device provided in an embodiment of the present application;

[0048] FIG. 8 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0050] The terminal positioning method provided in the embodiment of the present application can be applied in the application environment shown in FIG. 1. The terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers, by obtaining the first target fingerprint feature obtained by the target terminal located in the target area based on the first frequency, and selecting the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library, and then, when the number of the first reference fingerprint features is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0051] In one embodiment, as shown in FIG. 2 , a terminal positioning method is provided, which is described by taking the method applied to the server 104 in FIG. 1 as an example, and includes the following steps:

[0052] S201, obtaining a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency.

[0053] The first target fingerprint features include a channel estimation matrix, a signal power parameter, and a distance parameter from a base station.

[0054] It should be noted that the channel estimation matrix, signal power parameters and distance parameters from the base station of the target terminal in the target area can be acquired respectively to obtain the first target fingerprint feature of the target terminal in the target area based on the first frequency.

[0055] In one embodiment of the present application, when it is necessary to obtain the channel estimation matrix of the target terminal in the target area, the following contents may be specifically included: establishing a mathematical model to use the "channel" matrix to associate the "transmitted signal" and the "received signal"; sending a known "reference signal" or "pilot signal" and detecting the received signal. By comparing the transmitted signal and the received signal, the elements of the channel matrix can be calculated. The matrix describes the changes in the signal during the transmission process, including attenuation, phase shift, etc.

[0056] In another embodiment of the present application, when it is necessary to obtain the signal power parameters of the target terminal in the target area, the following may be specifically included: determine the time domain or digital expression of the signal. For analog signals, its mean square value (RMS) can be calculated, that is, the square root of the average value of the signal square; for digital signals, its power spectral density (PSD) can be calculated, that is, the distribution of signal power in the frequency domain. For analog signals, the mean square value can be directly used to calculate the power (if the signal is a voltage signal, the power P=V² / R, where V is the mean square value of the voltage signal and R is the load resistance). For digital signals, the power spectral density needs to be integrated over the entire frequency range to obtain the total power of the signal.

[0057] In another embodiment of the present application, when it is necessary to obtain the distance parameter of the target terminal from the base station in the target area, the following contents may be specifically included: it is necessary to obtain the latitude and longitude and other location information of the base station and the target terminal (such as a mobile phone). Use an appropriate distance calculation formula (such as the Euclidean distance formula) to calculate the distance between the base station and the target terminal. On a two-dimensional plane, the following formula can be used: distance = √((x2-x1)²+(y2-y1)²), where (x1, y1) and (x2, y2) are the coordinates of the base station and the target terminal, respectively.

[0058] S202: Select a first reference fingerprint feature from at least one candidate fingerprint feature stored in the first fingerprint database, the first reference fingerprint feature having a feature similarity with the first target fingerprint feature greater than a similarity threshold.

[0059] The first fingerprint library is a fingerprint library corresponding to the first frequency.

[0060] It should be noted that since the first target fingerprint feature includes three parameters, namely, the channel estimation matrix, the signal power parameter and the distance parameter from the base station, when comparing the similarity between the first target fingerprint feature and the candidate fingerprint feature, the three parameters, namely, the channel estimation matrix, the signal power parameter and the distance parameter from the base station, can be compared with the three candidate parameters, namely, the candidate estimation matrix, the candidate power parameter and the candidate distance parameter, corresponding to each candidate fingerprint feature, and the similarities corresponding to the three parameters are weightedly calculated, and the calculation result obtained is the feature similarity between the first target fingerprint feature and each candidate fingerprint feature.

[0061] To further illustrate, the parameter weights corresponding to the three parameters of the channel estimation matrix, the signal power parameter and the distance parameter from the base station can be pre-specified, and then, the similarities corresponding to the three parameters are weighted according to the parameter weights corresponding to each parameter, so as to obtain the feature similarity between the first target fingerprint feature and each candidate fingerprint feature.

[0062] In one embodiment of the present application, when it is necessary to select a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library, the following contents may also be included: performing feature difference analysis on the first target fingerprint feature and each candidate fingerprint feature to achieve a detailed comparison of the first target fingerprint feature with each candidate fingerprint feature, and obtaining the feature difference degree between the first target fingerprint feature and each candidate fingerprint feature; and then, using the candidate fingerprint feature with the smallest feature difference degree as the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold.

[0063] S203: When the number of the first reference fingerprint feature is one, use the candidate terminal position corresponding to the first reference fingerprint feature as the target terminal position of the target terminal in the target area.

[0064] It should be noted that if the number of first reference fingerprint features is one, since the feature similarity between the first reference fingerprint feature and the first target fingerprint feature is greater than the similarity threshold, the channel estimation matrix, signal power parameter and distance parameter from the base station obtained at the current position of the target terminal, and the feature similarity between the candidate estimation matrix, candidate power parameter and candidate distance parameter corresponding to the first reference fingerprint feature are greater than the similarity threshold, and since the candidate fingerprint features corresponding to different candidate terminal positions in the target area are different, the candidate terminal position corresponding to the first reference fingerprint feature is determined to be the target terminal position of the target terminal in the target area.

[0065] The terminal positioning method, by obtaining the first target fingerprint feature obtained by the target terminal located in the target area based on the first frequency, and selecting the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library, and then, when the number of the first reference fingerprint features is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area. According to the above content, the present application determines the first target fingerprint feature to achieve the wireless network coverage information corresponding to the target terminal at the location through the channel estimation matrix, the signal power parameter and the distance parameter from the base station, and then, according to at least one candidate fingerprint feature stored in the first fingerprint library, each candidate fingerprint feature is used to characterize the wireless network coverage information at different locations in the target area, and determines the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold. Since the first reference instruction feature is similar to the first target fingerprint feature, and the number of the first reference fingerprint features is one, it can be considered that the candidate terminal position corresponding to the first reference fingerprint feature is the target terminal position, thereby realizing an efficient terminal position positioning operation and ensuring the position positioning accuracy of the target terminal in the target area.

[0066] In an embodiment, as shown in FIG3 , when it is necessary to determine the target terminal position in the target area, the following contents may also be included:

[0067] S301: When the number of first reference fingerprint features is at least two, obtain a second target fingerprint feature obtained by a target terminal based on a second frequency.

[0068] It should be noted that if the number of the first reference fingerprint features is at least two, it indicates that there are two candidate terminal positions that may be the target terminal positions. Therefore, it is necessary to further determine the position of the target terminal in the target area.

[0069] S302: Determine a target terminal position of a target terminal in a target area according to a second target fingerprint feature and a second fingerprint library.

[0070] The second fingerprint library is a fingerprint library corresponding to the second frequency.

[0071] It should be noted that when it is necessary to determine the target terminal position of the target terminal in the target area based on the second target fingerprint feature and the second fingerprint library, it may specifically include the following contents: selecting a second reference fingerprint feature whose feature similarity with the second target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the second fingerprint library; if the number of second reference fingerprint features is one, then taking the candidate terminal position corresponding to the second reference fingerprint feature as the target terminal position of the target terminal in the target area.

[0072] Further explanation, in order to reduce the time cost required to determine the target terminal position of the target terminal in the target area and improve the efficiency of determining the target terminal position of the target terminal in the target area, the target second reference fingerprint features of the candidate terminal positions corresponding to the at least two first reference fingerprint features determined can be respectively compared with the second target fingerprint features obtained based on the second frequency for similarity to obtain the feature similarity corresponding to the two target second reference fingerprint features, and then, the candidate terminal position corresponding to the target second reference fingerprint feature with the largest feature similarity value is used as the target terminal position of the target terminal in the target area.

[0073] The above-mentioned terminal positioning method obtains the second target fingerprint feature obtained by the target terminal based on the second frequency to realize the terminal positioning operation on the target terminal based on different frequencies, thereby preventing the situation where the target terminal position in the target area cannot be accurately obtained when the number of first reference fingerprint features is at least two, thereby ensuring the smooth execution of the terminal positioning operation.

[0074] In one embodiment, as shown in FIG4 , when it is necessary to construct a first fingerprint library, the following contents may be specifically included:

[0075] S401, gridding the target area, and taking grid intersections in the gridded target area as candidate terminal locations.

[0076] The number of grid intersections is at least one.

[0077] It should be noted that in order to ensure that the terminal position can be smoothly positioned in the future and to improve the terminal positioning efficiency while ensuring the terminal positioning accuracy, the spectrum and carrier need to be configured when building the first fingerprint library. Specifically: (1) For spectrum resource analysis, in view of the flexibility of NR-U technology in unlicensed spectrum, especially the increasingly clear application prospects of 5GHz and 6GHz bands worldwide, the terminal positioning process can be focused on the above two bands. Considering the congestion and limited bandwidth of the 2.4GHz band and the special challenges of the 60GHz band, 5GHz and 6GHz become better choices. (2) For carrier aggregation strategy: Utilize the 5 carriers supported by NR-U at most, configure each CC with a maximum bandwidth of 80MHz, and a total bandwidth of 400MHz to enhance signal quality and positioning accuracy while improving user experience.

[0078] To further illustrate, when the target area needs to be divided into grids, the terminal positioning accuracy can be pre-specified, and then the corresponding grid length when the target area is divided into grids is determined according to the terminal positioning accuracy.

[0079] In one embodiment of the present application, if the terminal positioning accuracy is determined to be 0.5 meters, the target area is gridded based on the terminal positioning accuracy, and the resulting gridded target area is shown in Figure 5, wherein grid intersections are all used as candidate terminal positions.

[0080] S402: Determine antenna deployment positions within the target area.

[0081] It should be noted that in order to ensure that the target terminal position in the target area can be accurately obtained, it is necessary to ensure that when the network coverage is performed at the antenna deployment position, the feature difference between the candidate fingerprint features corresponding to each candidate terminal position is the largest; therefore, the process of determining the antenna deployment position may include the following: determine at least one candidate deployment position from the target area, and simulate network coverage for at least one candidate terminal position based on each candidate deployment position; determine the initial fingerprint feature corresponding to at least one candidate terminal position when each candidate deployment position performs simulated network coverage; determine the comprehensive fingerprint difference corresponding to each candidate deployment position based on the initial fingerprint feature corresponding to at least one candidate terminal position when each candidate deployment position performs simulated network coverage; and use the candidate deployment position with the largest comprehensive fingerprint difference among the candidate deployment positions as the antenna deployment position.

[0082] Further explanation: since the initial fingerprint feature includes initial fingerprint sub-features of at least two dimensions and the number of candidate terminal locations is at least two, when the initial fingerprint feature corresponding to at least one candidate terminal location when simulating network coverage for each candidate deployment location is used, determining the comprehensive fingerprint difference corresponding to each candidate deployment location may include the following contents: for each candidate deployment location, performing pairwise difference operations on the initial fingerprint sub-features of the same dimension corresponding to each candidate terminal location when simulating network coverage based on the candidate deployment location to obtain difference operation results corresponding to the initial fingerprint sub-features of each dimension; performing weighted operations on the difference operation results corresponding to the initial fingerprint sub-features of each dimension according to preset weights corresponding to the initial fingerprint sub-features of each dimension to obtain the comprehensive fingerprint difference corresponding to the candidate deployment location.

[0083] In one embodiment of the present application, when it is necessary to determine the antenna deployment location, a fingerprint difference analysis can be first performed for each candidate deployment location, and then the fingerprint difference values ​​can be accumulated and integrated to achieve the preset weights corresponding to the initial fingerprint sub-features of each dimension, and the difference operation results obtained after performing the difference operation on the initial fingerprint sub-features of the same dimension are weighted to obtain the comprehensive fingerprint difference corresponding to each candidate deployment location, wherein the determination process of the comprehensive fingerprint difference integrates multi-dimensional information and realizes a comprehensive evaluation of the variability of fingerprint characteristics within the network. According to the comprehensive fingerprint difference, the network coverage quality and fingerprint feature distribution of each candidate deployment location are analyzed to select the candidate deployment location with the largest comprehensive fingerprint difference among the candidate deployment locations as the antenna deployment location.

[0084] Furthermore, the effectiveness and accuracy of antenna deployment location determination can be further improved by performing multiple rounds of iterative convergence evaluations through unsupervised learning algorithms (including but not limited to particle swarm, bird flock, genetics, etc.) and determining the comprehensive fingerprint differences of each candidate deployment location through multiple rounds.

[0085] S403: Simulate network coverage for at least one candidate terminal location based on the antenna deployment position to obtain a candidate fingerprint feature of the at least one candidate terminal location.

[0086] In one embodiment of the present application, in order to reflect the actual channel conditions and the significant signal differences under the frequency band when simulating network coverage for at least one candidate terminal location, a ray tracing method is used to simulate the multipath effect, so as to simulate network coverage for at least one candidate terminal location and obtain candidate fingerprint features of at least one candidate terminal location.

[0087] S404: construct a first fingerprint library based on at least one candidate terminal location and at least one candidate fingerprint feature corresponding to the candidate terminal location.

[0088] In one embodiment of the present application, candidate fingerprint features corresponding to each candidate terminal position are determined, and the candidate fingerprint features include a candidate estimation matrix, a candidate power parameter, and a candidate distance parameter corresponding to each candidate terminal position. At least one candidate terminal position and the candidate fingerprint features corresponding to at least one candidate terminal position are stored in a first fingerprint library according to a corresponding relationship to realize the process of constructing the first fingerprint library.

[0089] The above-mentioned terminal positioning method simulates network coverage for at least one candidate terminal location to obtain candidate fingerprint features of at least one candidate terminal location; then, the operation of building a first fingerprint library is realized, which ensures that the subsequent terminal positioning process for the target terminal can proceed smoothly, and provides a data basis for determining the target terminal position in the target area.

[0090] In one embodiment, as shown in FIG6 , when it is necessary to determine the target terminal position in the target area, the following contents may be specifically included:

[0091] S601: Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency.

[0092] S602: Select a first reference fingerprint feature from at least one candidate fingerprint feature stored in the first fingerprint database, the first reference fingerprint feature having a feature similarity with the first target fingerprint feature greater than a similarity threshold.

[0093] S603: When the number of the first reference fingerprint feature is one, use the candidate terminal position corresponding to the first reference fingerprint feature as the target terminal position of the target terminal in the target area.

[0094] S604: When the number of the first reference fingerprint features is at least two, obtain a second target fingerprint feature obtained by the target terminal based on the second frequency.

[0095] S605: Select a second reference fingerprint feature from at least one candidate fingerprint feature stored in the second fingerprint database, the second reference fingerprint feature having a feature similarity with the second target fingerprint feature greater than a similarity threshold.

[0096] S606: If the number of the second reference fingerprint feature is one, use the candidate terminal position corresponding to the second reference fingerprint feature as the target terminal position of the target terminal in the target area.

[0097] In one embodiment of the present application, a multi-frequency single-station fingerprint positioning technology driven by NR-U carrier aggregation is used to obtain electromagnetic propagation responses of more frequencies based on carrier aggregation technology. The differences in radio wave propagation responses at different frequencies are used to achieve high-precision positioning of the target terminal. This method realizes the construction of a complex environment fingerprint database at different frequencies in multiple dimensions. By utilizing the differences in electromagnetic propagation characteristics at different frequencies, after the actual deployment of base station antennas, high-precision indoor positioning is implemented by obtaining information at different frequencies of the same dimension as the fingerprint library and matching it with the information in the fingerprint database. Furthermore, in the positioning process, in order to obtain more frequency fingerprint information, this application proposes a MAC scheduling algorithm that is different from the traditional one for target terminals with insufficient target fingerprint features. The MAC scheduling algorithm is used to select frequencies that have not been scheduled when the target terminal has an opportunity to schedule the target fingerprint features. This obtains fingerprint information at more frequencies and improves the positioning matching degree.

[0098] The terminal positioning method, by obtaining the first target fingerprint feature obtained by the target terminal located in the target area based on the first frequency, and selecting the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library, and then, when the number of the first reference fingerprint features is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area. According to the above content, the present application determines the first target fingerprint feature to achieve the wireless network coverage information corresponding to the target terminal at the location through the channel estimation matrix, the signal power parameter and the distance parameter from the base station, and then, according to at least one candidate fingerprint feature stored in the first fingerprint library, each candidate fingerprint feature is used to characterize the wireless network coverage information at different locations in the target area, and determines the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold. Since the first reference instruction feature is similar to the first target fingerprint feature, and the number of the first reference fingerprint features is one, it can be considered that the candidate terminal position corresponding to the first reference fingerprint feature is the target terminal position, thereby realizing an efficient terminal position positioning operation and ensuring the position positioning accuracy of the target terminal in the target area.

[0099] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0100] Based on the same inventive concept, the embodiment of the present application also provides a terminal positioning device for implementing the terminal positioning method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more terminal positioning device embodiments provided below can refer to the limitations of the terminal positioning method above, and will not be repeated here.

[0101] In one embodiment, as shown in FIG. 7 , a terminal positioning device is provided, including: an acquisition module 10, a selection module 20 and a determination module 30, wherein:

[0102] The acquisition module 10 is used to acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0103] A selection module 20 is used to select a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to the first frequency;

[0104] The determination module 30 is configured to use, when the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature as the target terminal position of the target terminal in the target area.

[0105] In one embodiment, a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency is obtained; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0106] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to the first frequency;

[0107] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0108] In one embodiment, when the number of the first reference fingerprint features is at least two, obtaining a second target fingerprint feature obtained by the target terminal based on the second frequency;

[0109] The target terminal position in the target area is determined according to the second target fingerprint feature and the second fingerprint library; wherein the second fingerprint library is a fingerprint library corresponding to the second frequency.

[0110] In one embodiment, a second reference fingerprint feature whose feature similarity with the second target fingerprint feature is greater than a similarity threshold is selected from at least one candidate fingerprint feature stored in the second fingerprint library;

[0111] If the number of the second reference fingerprint feature is one, the candidate terminal position corresponding to the second reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0112] In one embodiment, the target area is gridded, and grid intersections in the gridded target area are all used as candidate terminal locations; wherein the number of grid intersections is at least one;

[0113] Determine antenna deployment locations within the target area;

[0114] Simulating network coverage for at least one candidate terminal location based on the antenna deployment position to obtain a candidate fingerprint feature of at least one candidate terminal location;

[0115] A first fingerprint library is constructed based on at least one candidate terminal location and at least one candidate fingerprint feature corresponding to the candidate terminal location.

[0116] In one embodiment, at least one candidate deployment location is determined from within the target area, and network coverage is simulated for at least one candidate terminal location based on each candidate deployment location;

[0117] Determine an initial fingerprint feature corresponding to at least one candidate terminal position when each candidate deployment position is subjected to simulated network coverage;

[0118] Determine the comprehensive fingerprint difference corresponding to each candidate deployment position according to the initial fingerprint feature corresponding to at least one candidate terminal position when simulating network coverage at each candidate deployment position;

[0119] The candidate deployment location with the largest comprehensive fingerprint difference among the candidate deployment locations is used as the antenna deployment location.

[0120] In one embodiment, for each candidate deployment location, when simulating network coverage based on the candidate deployment location, initial fingerprint sub-features of the same dimension corresponding to each candidate terminal location are subjected to pairwise difference operations to obtain difference operation results corresponding to the initial fingerprint sub-features of each dimension;

[0121] According to the preset weights corresponding to the initial fingerprint sub-features of each dimension, the difference operation results corresponding to the initial fingerprint sub-features of each dimension are weighted to obtain the comprehensive fingerprint differences corresponding to the candidate deployment positions.

[0122] The terminal positioning device obtains the first target fingerprint feature obtained by the target terminal located in the target area based on the first frequency, and selects the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library. Then, when the number of the first reference fingerprint features is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area. According to the above content, the present application determines the first target fingerprint feature to achieve the wireless network coverage information corresponding to the target terminal at the location through the channel estimation matrix, the signal power parameter and the distance parameter from the base station. Then, according to at least one candidate fingerprint feature stored in the first fingerprint library, each candidate fingerprint feature is used to characterize the wireless network coverage information at different locations in the target area, and determines the first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than the similarity threshold. Since the first reference instruction feature is similar to the first target fingerprint feature, and the number of the first reference fingerprint features is one, it can be considered that the candidate terminal position corresponding to the first reference fingerprint feature is the target terminal position, thereby realizing an efficient terminal position positioning operation and ensuring the position positioning accuracy of the target terminal in the target area.

[0123] Each module in the above terminal positioning device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0124] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG8. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a terminal positioning method is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0125] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0126] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0127] Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0128] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to the first frequency;

[0129] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0130] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0131] When the number of the first reference fingerprint features is at least two, obtaining a second target fingerprint feature obtained by the target terminal based on the second frequency;

[0132] The target terminal position in the target area is determined according to the second target fingerprint feature and the second fingerprint library; wherein the second fingerprint library is a fingerprint library corresponding to the second frequency.

[0133] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0134] Selecting a second reference fingerprint feature whose feature similarity with the second target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the second fingerprint library;

[0135] If the number of the second reference fingerprint feature is one, the candidate terminal position corresponding to the second reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0136] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0137] Divide the target area into grids, and use grid intersections in the gridded target area as candidate terminal locations; wherein the number of grid intersections is at least one;

[0138] Determine antenna deployment locations within the target area;

[0139] Simulating network coverage for at least one candidate terminal location based on the antenna deployment position to obtain a candidate fingerprint feature of at least one candidate terminal location;

[0140] A first fingerprint library is constructed based on at least one candidate terminal location and at least one candidate fingerprint feature corresponding to the candidate terminal location.

[0141] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0142] Determine at least one candidate deployment location within the target area, and simulate network coverage for at least one candidate terminal location based on each candidate deployment location;

[0143] Determine an initial fingerprint feature corresponding to at least one candidate terminal position when each candidate deployment position is subjected to simulated network coverage;

[0144] Determine the comprehensive fingerprint difference corresponding to each candidate deployment position according to the initial fingerprint feature corresponding to at least one candidate terminal position when simulating network coverage at each candidate deployment position;

[0145] The candidate deployment location with the largest comprehensive fingerprint difference among the candidate deployment locations is used as the antenna deployment location.

[0146] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0147] For each candidate deployment location, when simulating network coverage based on the candidate deployment location, the initial fingerprint sub-features of the same dimension corresponding to each candidate terminal location are subjected to pairwise difference operations to obtain the difference operation results corresponding to the initial fingerprint sub-features of each dimension;

[0148] According to the preset weights corresponding to the initial fingerprint sub-features of each dimension, the difference operation results corresponding to the initial fingerprint sub-features of each dimension are weighted to obtain the comprehensive fingerprint differences corresponding to the candidate deployment positions.

[0149] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0150] Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0151] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to the first frequency;

[0152] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0153] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0154] When the number of the first reference fingerprint features is at least two, obtaining a second target fingerprint feature obtained by the target terminal based on the second frequency;

[0155] The target terminal position in the target area is determined according to the second target fingerprint feature and the second fingerprint library; wherein the second fingerprint library is a fingerprint library corresponding to the second frequency.

[0156] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0157] Selecting a second reference fingerprint feature whose feature similarity with the second target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the second fingerprint library;

[0158] If the number of the second reference fingerprint feature is one, the candidate terminal position corresponding to the second reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0159] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0160] Divide the target area into grids, and use grid intersections in the gridded target area as candidate terminal locations; wherein the number of grid intersections is at least one;

[0161] Determine antenna deployment locations within the target area;

[0162] Simulating network coverage for at least one candidate terminal location based on the antenna deployment position to obtain a candidate fingerprint feature of at least one candidate terminal location;

[0163] A first fingerprint library is constructed based on at least one candidate terminal location and at least one candidate fingerprint feature corresponding to the candidate terminal location.

[0164] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0165] Determine at least one candidate deployment location within the target area, and simulate network coverage for at least one candidate terminal location based on each candidate deployment location;

[0166] Determine an initial fingerprint feature corresponding to at least one candidate terminal position when each candidate deployment position is subjected to simulated network coverage;

[0167] Determine the comprehensive fingerprint difference corresponding to each candidate deployment position according to the initial fingerprint feature corresponding to at least one candidate terminal position when simulating network coverage at each candidate deployment position;

[0168] The candidate deployment location with the largest comprehensive fingerprint difference among the candidate deployment locations is used as the antenna deployment location.

[0169] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0170] For each candidate deployment location, when simulating network coverage based on the candidate deployment location, the initial fingerprint sub-features of the same dimension corresponding to each candidate terminal location are subjected to pairwise difference operations to obtain the difference operation results corresponding to the initial fingerprint sub-features of each dimension;

[0171] According to the preset weights corresponding to the initial fingerprint sub-features of each dimension, the difference operation results corresponding to the initial fingerprint sub-features of each dimension are weighted to obtain the comprehensive fingerprint differences corresponding to the candidate deployment positions.

[0172] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0173] Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station;

[0174] Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to the first frequency;

[0175] When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0176] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0177] When the number of the first reference fingerprint features is at least two, obtaining a second target fingerprint feature obtained by the target terminal based on the second frequency;

[0178] The target terminal position in the target area is determined according to the second target fingerprint feature and the second fingerprint library; wherein the second fingerprint library is a fingerprint library corresponding to the second frequency.

[0179] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0180] Selecting a second reference fingerprint feature whose feature similarity with the second target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the second fingerprint library;

[0181] If the number of the second reference fingerprint feature is one, the candidate terminal position corresponding to the second reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0183] Divide the target area into grids, and use grid intersections in the gridded target area as candidate terminal locations; wherein the number of grid intersections is at least one;

[0184] Determine antenna deployment locations within the target area;

[0185] Simulating network coverage for at least one candidate terminal location based on the antenna deployment position to obtain a candidate fingerprint feature of at least one candidate terminal location;

[0186] A first fingerprint library is constructed based on at least one candidate terminal location and at least one candidate fingerprint feature corresponding to the candidate terminal location.

[0187] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0188] Determine at least one candidate deployment location within the target area, and simulate network coverage for at least one candidate terminal location based on each candidate deployment location;

[0189] Determine an initial fingerprint feature corresponding to at least one candidate terminal position when each candidate deployment position is subjected to simulated network coverage;

[0190] Determine the comprehensive fingerprint difference corresponding to each candidate deployment position according to the initial fingerprint feature corresponding to at least one candidate terminal position when simulating network coverage at each candidate deployment position;

[0191] The candidate deployment location with the largest comprehensive fingerprint difference among the candidate deployment locations is used as the antenna deployment location.

[0192] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0193] For each candidate deployment location, when simulating network coverage based on the candidate deployment location, the initial fingerprint sub-features of the same dimension corresponding to each candidate terminal location are subjected to pairwise difference operations to obtain the difference operation results corresponding to the initial fingerprint sub-features of each dimension;

[0194] According to the preset weights corresponding to the initial fingerprint sub-features of each dimension, the difference operation results corresponding to the initial fingerprint sub-features of each dimension are weighted to obtain the comprehensive fingerprint differences corresponding to the candidate deployment positions.

[0195] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0196] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0197] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0198] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A terminal positioning method, characterized in that: The method comprises: Acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station; Selecting a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in a first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to a first frequency; When the number of the first reference fingerprint feature is one, the candidate terminal position corresponding to the first reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

2. The method according to claim 1, characterized in that The method further comprises: When the number of the first reference fingerprint features is at least two, obtaining a second target fingerprint feature obtained by the target terminal based on a second frequency; The target terminal position of the target terminal in the target area is determined according to the second target fingerprint feature and the second fingerprint library; wherein the second fingerprint library is a fingerprint library corresponding to the second frequency.

3. The method according to claim 2, characterized in that The determining the target terminal position of the target terminal in the target area according to the second target fingerprint feature and the second fingerprint library includes: Selecting a second reference fingerprint feature whose feature similarity with the second target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in the second fingerprint library; If the number of the second reference fingerprint feature is one, the candidate terminal position corresponding to the second reference fingerprint feature is used as the target terminal position of the target terminal in the target area.

4. The method according to claim 1, characterized in that: The construction process of the first fingerprint library includes: Divide the target area into grids, and use grid intersections in the gridded target area as candidate terminal locations; wherein the number of the grid intersections is at least one; Determining antenna deployment locations within the target area; Performing simulated network coverage on at least one candidate terminal location based on the antenna deployment position to obtain a candidate fingerprint feature of at least one candidate terminal location; A first fingerprint library is constructed based on at least one candidate terminal location and at least one candidate fingerprint feature corresponding to the candidate terminal location.

5. The method according to claim 4, characterized in that The determining of the antenna deployment position within the target area includes: Determine at least one candidate deployment location within the target area, and simulate network coverage for at least one candidate terminal location based on each of the candidate deployment locations; Determine an initial fingerprint feature corresponding to at least one candidate terminal position when each of the candidate deployment positions is subjected to simulated network coverage; Determine the comprehensive fingerprint difference corresponding to each candidate deployment location according to the initial fingerprint feature corresponding to at least one candidate terminal location when each candidate deployment location performs simulated network coverage; The candidate deployment position with the largest comprehensive fingerprint difference among the candidate deployment positions is used as the antenna deployment position.

6. The method according to claim 5, characterized in that The initial fingerprint feature includes initial fingerprint sub-features of at least two dimensions, and the number of the candidate terminal positions is at least two; the determining of the comprehensive fingerprint difference corresponding to each candidate deployment position according to the initial fingerprint feature corresponding to at least one candidate terminal position when simulating network coverage at each candidate deployment position includes: For each candidate deployment location, when simulating network coverage based on the candidate deployment location, the initial fingerprint sub-features of the same dimension corresponding to each candidate terminal location are subjected to pairwise difference operations to obtain difference operation results corresponding to the initial fingerprint sub-features of each dimension; According to the preset weights corresponding to the initial fingerprint sub-features of each dimension, weighted operations are performed on the difference operation results corresponding to the initial fingerprint sub-features of each dimension to obtain the comprehensive fingerprint differences corresponding to the candidate deployment positions.

7. A terminal positioning device, characterized in that: The device comprises: An acquisition module, used to acquire a first target fingerprint feature obtained by a target terminal located in a target area based on a first frequency; wherein the first target fingerprint feature includes a channel estimation matrix, a signal power parameter, and a distance parameter from a base station; A selection module, configured to select a first reference fingerprint feature whose feature similarity with the first target fingerprint feature is greater than a similarity threshold from at least one candidate fingerprint feature stored in a first fingerprint library; wherein the first fingerprint library is a fingerprint library corresponding to a first frequency; The determination module is configured to use, when the number of the first reference fingerprint features is one, the candidate terminal position corresponding to the first reference fingerprint feature as the target terminal position of the target terminal in the target area.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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