User positioning method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a user positioning method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring initial base station signal intensity received by user equipment at current time and an environment factor feature vector of a location; inputting the environmental factor feature vector into a base station signal strength adjustment factor calculation model, and outputting an adjustment factor; according to the adjustment factor and the initial base station signal strength, determining the target base station signal strength; and determining the position information of the user equipment according to the signal strength of the target base station. According to the user positioning method provided by the invention, the influence of the environment change on the signal intensity is simulated by using the base station signal intensity adjustment factor calculation model, the adjustment factor under the current environment condition is generated, and then the collected real-time base station signal intensity is dynamically corrected based on the adjustment factor; the problem that the signal strength of the base station cannot be determined in a complex and changeable environment is effectively solved, and the precision and stability of a positioning mode based on the signal strength of the base station are further improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, and in particular to a user positioning method and device, electronic equipment, storage medium and program product. BACKGROUND

[0002] Currently widely used positioning technologies mainly include Global Positioning System (GPS) positioning and base station signal strength positioning. The base station signal strength positioning technology is not only suitable for outdoor environments, but also can provide positioning services in indoor, underground parking lots, tunnels and other areas where GPS signals are weak or cannot be covered, making up for the shortcomings of GPS in indoor positioning and becoming an indispensable positioning means.

[0003] In the existing base station signal strength positioning technology, a pre-constructed fingerprint library method is usually used to collect base station signal strength data at different positions in a target area to form a fingerprint library of position-base station signal strength correspondence, so as to match the user position by comparing the base station signal strength measured by the user equipment in real time with the data in the fingerprint library. However, environmental factors change have a certain influence on wireless signal propagation, resulting in a large deviation between the data in the fingerprint library and the real-time base station signal strength data collected, thereby reducing the positioning accuracy. SUMMARY

[0004] The present application provides a user positioning method, device, electronic equipment, storage medium and program product to solve the problem of low accuracy of the user positioning method in the prior art.

[0005] In a first aspect, the present application provides a user positioning method, comprising: obtaining an initial base station signal strength received by a user equipment at a current time and an environmental factor feature vector of the location; inputting the environmental factor feature vector into a base station signal strength adjustment factor calculation model to obtain an adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model is used to simulate the influence of environmental changes on base station signal strength and generate an adjustment factor under current environmental conditions; determining a target base station signal strength according to the adjustment factor and the initial base station signal strength; determining the position information of the user equipment according to the target base station signal strength.

[0006] In one embodiment, the base station signal strength adjustment factor calculation model is obtained by training in the following way: constructing a first mathematical model; the first mathematical model is used to describe the relationship between the environmental factor feature vector and the adjustment factor; initializing a plurality of parameters in the first mathematical model; inputting an environmental factor feature vector sample into the initialized first mathematical model to obtain an adjustment factor sample; calculating a loss value according to the adjustment factor sample; optimizing the plurality of parameters in the first mathematical model according to the loss value by using an optimization algorithm; iteratively performing the step of inputting an environmental factor feature vector sample into the initialized first mathematical model to obtain an adjustment factor sample until a preset ending condition is reached; constructing a base station signal strength adjustment factor calculation model based on the first mathematical model and the plurality of optimal parameters therein.

[0007] In one embodiment, the constructing the first mathematical model comprises: constructing a first expression according to an environmental factor feature vector; the first expression is used to capture local changes in environmental factors; constructing a second expression according to an environmental factor feature vector; the second expression is used to simulate the periodic influence of environmental factors; constructing a first mathematical model error term; adding the first expression, the second expression, and the first mathematical model error term to obtain a first objective function; constructing the first mathematical model according to the first objective function.

[0008] In one embodiment, the determining the target base station signal strength according to the adjustment factor and the initial base station signal strength comprises: inputting the adjustment factor and the initial base station signal strength into a base station signal strength adjustment calculation model to obtain a target base station signal strength output by the base station signal strength adjustment calculation model; The base station signal strength adjustment calculation model is obtained by training in the following way: constructing a second mathematical model; the second mathematical model is used to describe the relationship between the adjustment factor and the base station signal strength; solving the optimal parameters in the second mathematical model through adjustment factor samples; constructing a base station signal strength adjustment calculation model based on the second mathematical model and the optimal parameters therein.

[0009] In one embodiment, the user positioning method further comprises: The constructing the second mathematical model comprises: adjusting the original base station signal strength according to the adjustment factor to obtain an adjusted base station signal strength; Construct the error term of the second mathematical model; The original base station signal strength, the adjusted base station signal strength, and the error term of the second mathematical model are added together to obtain the second objective function; Based on the second objective function, construct a second mathematical model.

[0010] In one embodiment, determining the location information of the user equipment based on the signal strength of the target base station includes: Based on the signal strength of the target base station, a match is made in the fingerprint database to obtain the location information of the user equipment; the fingerprint database is used to store the signal strength and location information of base stations with correlation.

[0011] Secondly, the present invention also provides a user positioning device, comprising: The acquisition module is used to acquire the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location; The adjustment factor calculation module is used to input the environmental factor feature vector into the base station signal strength adjustment factor calculation model to obtain the adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model is used to simulate the impact of environmental changes on the base station signal strength and generate the adjustment factor under the current environmental conditions; A base station signal strength adjustment module is used to determine the target base station signal strength based on the adjustment factor and the initial base station signal strength. The positioning module is used to determine the location information of the user equipment based on the signal strength of the target base station.

[0012] Thirdly, the present invention provides an electronic device, the electronic device including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the user positioning methods described above.

[0013] Fourthly, the present invention also provides a non-transitory computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the user location methods described above.

[0014] Fifthly, the present invention also provides a computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, and which, when executed by the processor, implements the steps of any of the user location methods described above.

[0015] The user positioning method, device, electronic device, storage medium, and program product provided by this invention obtain the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location. It uses a base station signal strength adjustment factor calculation model to simulate the impact of environmental changes on signal strength, generates an adjustment factor under the current environmental conditions, reflects the actual changes in base station signal strength under specific environmental conditions, and then dynamically corrects the collected real-time base station signal strength based on the adjustment factor. This effectively solves the problem of uncertain base station signal strength in complex and ever-changing environments, thereby improving the accuracy and stability of positioning methods based on base station signal strength. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the user location method provided by the present invention.

[0018] Figure 2 This is a schematic diagram of the user positioning device provided by the present invention.

[0019] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0021] The terms "first," "second," etc., used in this invention are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein.

[0022] The following is combined Figures 1-3 This invention describes the user location method, apparatus, electronic device, storage medium, and program product provided by the present invention.

[0023] It should be noted that the user positioning method provided in this embodiment of the invention is implemented based on a user positioning device. The user positioning method provided in this embodiment of the invention can be applied to various application scenarios, such as employee check-in scenarios in parks or indoor spaces, large-scale open or remote examination scenarios, etc. In these application scenarios, users carry user devices. The user devices receive base station signal strength, and an adjustment factor is introduced to consider the impact of changes in environmental conditions. Based on the adjustment factor, the initial base station signal strength, which did not consider environmental factors, is dynamically corrected. This accurately calculates the target base station signal strength after being affected by the actual environment, significantly improving the accuracy and stability of the positioning system based on base station signal strength.

[0024] This invention describes the user positioning method using a user positioning device as the execution subject as an example.

[0025] Combination Figure 1 , Figure 1 This is a flowchart illustrating the user location method provided by the present invention.

[0026] like Figure 1 As shown, the method includes the following: Step 101: Obtain the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location; Step 102: Input the environmental factor feature vector into the base station signal strength adjustment factor calculation model to obtain the adjustment factor output by the base station signal strength adjustment factor calculation model; Step 103: Determine the target base station signal strength based on the adjustment factor and the initial base station signal strength; Step 104: Determine the location information of the user equipment based on the signal strength of the target base station.

[0027] Specifically, first, it needs to be confirmed that the user's device (such as a smartphone, computer, etc.) supports reading base station signal strength; most modern mobile devices have this function. It also needs to be ensured that the relevant permissions have been enabled on the user's device. After the relevant configurations are completed, the signal strength from multiple nearby base stations can be measured through the relevant network interface, and the signal strength of these nearby base stations can be used as the base station signal strength received by the user's device. Base station signal strength refers to the strength of the wireless signal received by a mobile device from a base station in a cellular network. It is an important indicator for measuring the coverage and quality of mobile communication networks, and is usually expressed in decibels (dB) and milliwatts (mW).

[0028] However, changes in environmental factors can significantly affect the propagation characteristics of wireless signals. The base station signal strength measured in real time by user equipment may show fluctuations and instability, resulting in inaccurate measurements of the base station signal strength.

[0029] Environmental factors include various dimensions such as weather conditions, building density, and terrain features. Weather conditions include variations in rainfall, temperature, humidity, and wind speed. In adverse weather conditions, signal attenuation in the atmosphere may increase, thus affecting signal strength. Building obstructions may block or absorb wireless signals, leading to weaker signal strength; for example, signal strength is often affected when users are indoors or in densely built-up areas. Terrain features can also cause signal obstruction or reflection; for example, mountainous or hilly terrain may cause signal obstruction or reflection, affecting signal strength. Therefore, it is necessary to comprehensively consider the impact of multiple environmental factors on the real-time base station signal strength measured by user equipment.

[0030] First, the user equipment measures the initial base station signal strength received at the current time and obtains the initial base station signal strength received by the user equipment at the current time, which is used as the basic data for subsequent dynamic correction.

[0031] It also acquires environmental factors from different dimensions through various Application Programming Interfaces (APIs). First, it determines the user's device location based on network positioning. Then, it obtains the current weather information for the location through the weather API, including but not limited to rainfall, temperature, humidity, and wind speed. It also obtains information about surrounding buildings and terrain features through the map API, and so on. The acquired environmental factors from different dimensions are then integrated to form an environmental factor feature vector.

[0032] Furthermore, the environmental factor feature vector is input into the base station signal strength adjustment factor calculation model. The base station signal strength adjustment factor calculation model can simulate the impact of environmental factor changes on base station signal strength and generate the adjustment factor under the current environmental conditions.

[0033] Furthermore, based on the adjustment factor under the current environmental conditions, the obtained real-time initial base station signal strength is corrected. Specifically, the adjustment factor and the initial base station signal strength can be input into the base station signal strength adjustment calculation model, and the corrected target base station signal strength can be calculated through the relationship between the adjustment factor and the initial base station signal strength defined in the model.

[0034] Furthermore, based on the signal strength of the target base station, the corresponding location information is matched in a pre-built fingerprint database, and the matched location information is determined as the location information of the user equipment.

[0035] The user positioning method provided by this invention obtains the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location. It then uses a base station signal strength adjustment factor calculation model to simulate the impact of environmental changes on signal strength, generates an adjustment factor under the current environmental conditions, reflects the actual changes in base station signal strength under specific environmental conditions, and then dynamically corrects the collected real-time base station signal strength based on the adjustment factor. This effectively solves the problem of uncertain base station signal strength in complex and ever-changing environments, thereby improving the accuracy and stability of positioning methods based on base station signal strength.

[0036] In some embodiments, the base station signal strength adjustment factor calculation model is trained in the following manner: Construct a first mathematical model; the first mathematical model is used to describe the relationship between the feature vectors of environmental factors and the adjustment factors. Initialize multiple parameters in the first mathematical model; Input the environmental factor feature vector samples into the initialized first mathematical model to obtain the adjustment factor samples; Calculate the loss value based on the adjusted factor sample; Using an optimization algorithm, multiple parameters in the first mathematical model are optimized based on the loss value; The step of iteratively executing the input of environmental factor feature vector samples into the initialized first mathematical model to obtain adjustment factor samples continues until the preset termination condition is met. Based on the first mathematical model and its multiple optimal parameters, a base station signal strength adjustment factor calculation model is constructed.

[0037] It should be noted that before model training, model training data needs to be acquired and a sample library established. User information is obtained from multiple fixed locations within the target area, such as turnstiles and fingerprint check-in points in a park. Based on the user information, the base station signal strength samples received by the user's device are automatically associated with these fixed locations. Specifically, the signal strength is collected in real time under different weather conditions without adjustment, and this is used as the original base station signal strength sample. Furthermore, the timestamp, location, and multi-dimensional environmental factors at the time of acquiring the base station signal strength sample are recorded simultaneously, and these multi-dimensional environmental factors are integrated into an environmental factor feature vector sample.

[0038] The collected base station signal strength samples are further correlated with the corresponding location and environmental factor feature vector samples, and data preprocessing is performed. First, the data is cleaned, outliers are identified and removed or filled in. Data deviating from the normal range can be identified using the Z-score method, and missing values ​​are handled using the mean imputation method. Then, duplicate data is removed to ensure the uniqueness and accuracy of the dataset. Finally, the data is standardized; for example, base station signal strength samples are converted to numerical format, location information is converted to latitude and longitude format, and environmental factor feature vector samples are converted to numerical vector format. Lasso feature selection can also be used to reduce unnecessary features. While minimizing information loss, a concise and interpretable training dataset is formed, and a sample library is constructed from this training dataset. During model training, the required training data can be extracted from the sample library.

[0039] Specifically, based on wireless propagation theory and nonlinear models, a first mathematical model is designed to describe the relationship between the characteristic vector of environmental factors and the adjustment factor. The first mathematical model is initialized by initializing multiple parameters, that is, assigning initial values ​​to multiple parameters of the first mathematical model. These initial values ​​can be random values ​​or estimates based on domain knowledge.

[0040] Furthermore, the environmental factor feature vector samples obtained from the sample library are input into the initialized first mathematical model to obtain adjustment factor samples. Since the model adopts unsupervised learning, the desired adjustment factor can be defined through the intrinsic properties of the data or the reconstruction objective.

[0041] Furthermore, the least squares method is used as the loss function. The loss value is calculated based on the adjustment factor samples calculated by the first mathematical model and their corresponding expected adjustment factors to measure the error between the model's predicted values ​​and the expected values. The loss function can be expressed as: in, It is the model's predicted value for the j-th sample. is the expected value, and m is the sample size.

[0042] The model parameters are iteratively updated using gradient descent or other optimization algorithms (such as Adam, L-BFGS, etc.) to minimize the loss function.

[0043] The model performs iterative steps such as prediction, loss calculation, and parameter optimization until the preset termination condition is met, that is, until the loss function converges or the predetermined number of iterations is reached, thus solving for multiple optimal parameters in the model.

[0044] Finally, based on the constructed first mathematical model and its multiple optimal parameters, a calculation model for the base station signal strength adjustment factor is constructed.

[0045] This invention constructs and trains a first mathematical model to obtain a base station signal strength adjustment factor calculation model. This model can accurately simulate the impact of environmental changes on base station signal strength, generate an accurate adjustment factor, and then dynamically correct the collected base station signal strength based on the adjustment factor, significantly improving the accuracy and stability of the positioning system based on base station signal strength.

[0046] Based on the above, the construction of the first mathematical model includes: Based on the feature vectors of environmental factors, a first expression is constructed; the first expression is used to capture local changes in environmental factors. Based on the characteristic vector of environmental factors, a second expression is constructed; the second expression is used to simulate the periodic effects of environmental factors. Construct the error term of the first mathematical model; The first objective function is obtained by adding the first expression, the second expression, and the error term of the first mathematical model. Based on the first objective function, construct the first mathematical model.

[0047] Specifically, a first objective function is constructed that can describe the relationship between the feature vector of environmental factors and the adjustment factor: in, It is the adjustment factor of the model output; It is the feature vector of environmental factors input to the model. Each component represents environmental factors in different dimensions, including rainfall, humidity, temperature, wind speed, building information, terrain features, and other environmental factors. It is each environmental factor The mean; These are parameters to be determined. This is the first mathematical model error term, used to adjust the baseline signal strength. These are all the parameters mentioned above that need optimization. First expression The second expression is used to capture local changes. Periodicity and oscillation behavior were introduced to simulate the periodic effects of factors such as weather.

[0048] Based on the constructed first objective function, construct the first mathematical model.

[0049] Based on wireless propagation theory and nonlinear models, this invention constructs a flexible first mathematical model, which is then trained into a base station signal strength adjustment factor calculation model. This model can capture local changes, simulate the smoothing effect of environmental factors on signal strength, and introduce periodic and oscillatory behavior terms to simulate the periodic effect of environmental factors, thereby more accurately capturing the impact of environmental changes on signal strength.

[0050] In some embodiments, the base station signal strength adjustment calculation model is trained in the following manner: A second mathematical model is constructed; this second mathematical model is used to describe the relationship between the adjustment factor and the base station signal strength. By adjusting the factor samples, the optimal parameters in the second mathematical model can be obtained; Based on the second mathematical model and its optimal parameters, a base station signal strength adjustment calculation model is constructed.

[0051] Specifically, a second mathematical model is designed to describe the relationship between the adjustment factor and the base station signal strength. The second mathematical model is initialized by initializing the loss term parameters in the second mathematical model, that is, assigning initial values ​​to the loss term parameters of the first mathematical model. These initial values ​​can be random values ​​or estimates based on domain knowledge.

[0052] Furthermore, the adjustment factor samples obtained in the above process are input into the initialized second mathematical model to obtain the target base station signal strength samples. Since the model uses unsupervised learning, the desired base station signal strength can be defined through the inherent properties of the data or the reconstruction target.

[0053] Furthermore, the least squares method is used as the loss function. The loss value is calculated based on the target base station signal strength sample calculated by the second mathematical model and its corresponding expected base station signal strength, so as to measure the error between the model prediction value and the expected value.

[0054] The model parameters are iteratively updated using gradient descent or other optimization algorithms to minimize the loss function.

[0055] The process iteratively executes steps such as model prediction, loss value calculation, and parameter optimization until the preset termination condition is met, that is, until the loss function converges or the predetermined number of iterations is reached, to solve for the optimal parameters in the model, that is, the optimal loss term parameters.

[0056] Finally, based on the constructed second mathematical model and its optimal parameters, a calculation model for base station signal strength adjustment is constructed.

[0057] This invention, through the construction and training of a second mathematical model, ultimately obtains a base station signal strength adjustment calculation model. This model can dynamically correct the real-time base station signal strength collected by the user equipment to reflect the impact of the actual environment on the signal strength, effectively solving the problem of uncertain signal strength in complex and ever-changing environments, thereby improving positioning accuracy.

[0058] Based on the above, the construction of the second mathematical model includes: The original base station signal strength is adjusted according to the adjustment factor to obtain the adjusted base station signal strength; Construct the error term of the second mathematical model; The original base station signal strength, the adjusted base station signal strength, and the error term of the second mathematical model are added together to obtain the second objective function; Based on the second objective function, construct a second mathematical model.

[0059] Specifically, a second objective function is constructed that can describe the relationship between the adjustment factor and the base station signal strength: in, This represents the target base station signal strength output by the model, which is the expected base station signal strength after applying the base station signal strength adjustment factor. This represents the original base station signal strength, that is, the base station signal strength collected in real time under different weather conditions without any adjustment. It is an adjustment factor. This is the base station signal strength after adjustment by the adjustment factor; It is the second mathematical model error term, used to adjust the baseline signal strength, and is the parameter to be optimized mentioned above.

[0060] Understandable, when This indicates a need to enhance base station signals to compensate for signal loss. This indicates the additional signal gain resulting from improved environmental conditions.

[0061] Based on the constructed second objective function, a second mathematical model is constructed.

[0062] In this embodiment of the invention, a second mathematical model is built and then trained into a base station signal strength adjustment calculation model. This model can accurately reflect the impact of environmental changes on base station signal strength, generate more accurate target base station signal strength, significantly improve the accuracy and stability of the positioning system, and perform particularly well under complex environmental conditions.

[0063] In some embodiments, determining the location information of the user equipment based on the signal strength of the target base station includes: Based on the signal strength of the target base station, a match is made in the fingerprint database to obtain the location information of the user equipment; the fingerprint database is used to store the signal strength and location information of base stations with correlation.

[0064] It should be noted that the fingerprint database is pre-built. Through the above process, the target base station signal strength sample, after being corrected from the original base station signal strength sample, can be obtained. Furthermore, the original base station signal strength sample is already associated with fixed-point location information upon acquisition; therefore, the target base station signal strength sample can also be associated with its corresponding fixed-point location information. The associated target base station signal strength sample and its corresponding fixed-point location information are stored in the fingerprint database for subsequent matching of user location information.

[0065] Specifically, based on the signal strength of the target base station, the corresponding location information is matched in a pre-built fingerprint database, and the matched location information is determined as the location information of the user equipment.

[0066] This invention determines the location information of user equipment by matching the target base station signal strength with the base station signal strength and location information stored in the fingerprint database. This solves the problem of base station signal strength deviation caused by environmental factors and improves the accuracy and stability of positioning.

[0067] The user positioning device provided by the present invention is described below. The user positioning device described below and the user positioning method described above can be referred to in correspondence.

[0068] Reference Figure 2 , Figure 2 This is a schematic diagram of the user positioning device provided by the present invention.

[0069] The user positioning device includes: The acquisition module 210 is used to acquire the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of the location.

[0070] The adjustment factor calculation module 220 is used to input the environmental factor feature vector into the base station signal strength adjustment factor calculation model to obtain the adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model is used to simulate the impact of environmental changes on the base station signal strength and generate the adjustment factor under the current environmental conditions.

[0071] The base station signal strength adjustment module 230 is used to determine the target base station signal strength based on the adjustment factor and the initial base station signal strength.

[0072] The positioning module 240 is used to determine the location information of the user equipment based on the signal strength of the target base station.

[0073] The user positioning device provided by this invention obtains the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location. It uses a base station signal strength adjustment factor calculation model to simulate the impact of environmental changes on signal strength, generates an adjustment factor under the current environmental conditions, reflects the actual changes in base station signal strength under specific environmental conditions, and then dynamically corrects the collected real-time base station signal strength based on the adjustment factor. This effectively solves the problem of uncertain base station signal strength in complex and ever-changing environments, thereby improving the accuracy and stability of positioning methods based on base station signal strength.

[0074] Furthermore, the user positioning device is also used for: Construct a first mathematical model; the first mathematical model is used to describe the relationship between the feature vectors of environmental factors and the adjustment factors. Initialize multiple parameters in the first mathematical model; Input the environmental factor feature vector samples into the initialized first mathematical model to obtain the adjustment factor samples; Calculate the loss value based on the adjusted factor sample; Using an optimization algorithm, multiple parameters in the first mathematical model are optimized based on the loss value; The step of iteratively executing the input of environmental factor feature vector samples into the initialized first mathematical model to obtain adjustment factor samples continues until the preset termination condition is met. Based on the first mathematical model and its multiple optimal parameters, a base station signal strength adjustment factor calculation model is constructed.

[0075] Furthermore, the user positioning device is also used for: Based on the feature vectors of environmental factors, a first expression is constructed; the first expression is used to capture local changes in environmental factors. Based on the characteristic vector of environmental factors, a second expression is constructed; the second expression is used to simulate the periodic effects of environmental factors. Construct the error term of the first mathematical model; The first objective function is obtained by adding the first expression, the second expression, and the error term of the first mathematical model. Based on the first objective function, construct the first mathematical model.

[0076] Furthermore, the user positioning device is also used for: A second mathematical model is constructed; this second mathematical model is used to describe the relationship between the adjustment factor and the base station signal strength. By adjusting the factor samples, the optimal parameters in the second mathematical model can be obtained; Based on the second mathematical model and its optimal parameters, a base station signal strength adjustment calculation model is constructed.

[0077] Furthermore, the user positioning device is also used for: The construction of the second mathematical model includes: The original base station signal strength is adjusted according to the adjustment factor to obtain the adjusted base station signal strength; Construct the error term of the second mathematical model; The original base station signal strength, the adjusted base station signal strength, and the error term of the second mathematical model are added together to obtain the second objective function; Based on the second objective function, construct a second mathematical model.

[0078] Furthermore, the positioning module 240 is also used for: Determining the location information of the user equipment based on the signal strength of the target base station includes: Based on the signal strength of the target base station, a match is made in the fingerprint database to obtain the location information of the user equipment; the fingerprint database is used to store the signal strength and location information of base stations with correlation.

[0079] It should be noted that the user positioning device provided by the present invention can execute the user positioning method described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0080] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 3 As shown, the electronic device may include a processor 310, a communications interface 320, a memory 330, and a communication bus 340, wherein the processor 310, communications interface 320, and memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute a user positioning method. This method includes: acquiring the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location; inputting the environmental factor feature vector into a base station signal strength adjustment factor calculation model to obtain an adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model is used to simulate the impact of environmental changes on the base station signal strength to generate an adjustment factor under the current environmental conditions; determining the target base station signal strength based on the adjustment factor and the initial base station signal strength; and determining the location information of the user equipment based on the target base station signal strength.

[0081] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, 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 a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the user positioning method provided in the above embodiments, the method comprising: acquiring the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of the location; inputting the environmental factor feature vector into a base station signal strength adjustment factor calculation model to obtain an adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model being used to simulate the impact of environmental changes on the base station signal strength to generate an adjustment factor under the current environmental conditions; determining the target base station signal strength based on the adjustment factor and the initial base station signal strength; and determining the location information of the user equipment based on the target base station signal strength.

[0083] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the user positioning method provided in the above embodiments. The method includes: acquiring the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location; inputting the environmental factor feature vector into a base station signal strength adjustment factor calculation model to obtain an adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model is used to simulate the impact of environmental changes on the base station signal strength, generating an adjustment factor under the current environmental conditions; determining the target base station signal strength based on the adjustment factor and the initial base station signal strength; and determining the location information of the user equipment based on the target base station signal strength.

[0084] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0085] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A user location method, characterized in that, include: Obtain the initial base station signal strength received by the user equipment at the current time and the feature vector of environmental factors in its location; The environmental factor feature vector is input into the base station signal strength adjustment factor calculation model to obtain the adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model is used to simulate the impact of environmental changes on base station signal strength and generate the adjustment factor under the current environmental conditions; The target base station signal strength is determined based on the adjustment factor and the initial base station signal strength. The location information of the user equipment is determined based on the signal strength of the target base station.

2. The user positioning method according to claim 1, characterized in that, The base station signal strength adjustment factor calculation model was trained in the following way: Construct a first mathematical model; the first mathematical model is used to describe the relationship between the feature vectors of environmental factors and the adjustment factors. Initialize multiple parameters in the first mathematical model; Input the environmental factor feature vector samples into the initialized first mathematical model to obtain the adjustment factor samples; Calculate the loss value based on the adjusted factor sample; Using an optimization algorithm, multiple parameters in the first mathematical model are optimized based on the loss value; The step of iteratively executing the input of environmental factor feature vector samples into the initialized first mathematical model to obtain adjustment factor samples continues until the preset termination condition is met. Based on the first mathematical model and its multiple optimal parameters, a base station signal strength adjustment factor calculation model is constructed.

3. The user positioning method according to claim 2, characterized in that, The construction of the first mathematical model includes: Based on the feature vectors of environmental factors, a first expression is constructed; the first expression is used to capture local changes in environmental factors. Based on the characteristic vector of environmental factors, a second expression is constructed; the second expression is used to simulate the periodic effects of environmental factors. Construct the error term of the first mathematical model; The first objective function is obtained by adding the first expression, the second expression, and the error term of the first mathematical model. Based on the first objective function, construct the first mathematical model.

4. The user positioning method according to claim 3, characterized in that, The step of determining the target base station signal strength based on the adjustment factor and the initial base station signal strength includes: The adjustment factor and the initial base station signal strength are input into the base station signal strength adjustment calculation model to obtain the target base station signal strength output by the base station signal strength adjustment calculation model. The base station signal strength adjustment calculation model was trained in the following way: A second mathematical model is constructed; this second mathematical model is used to describe the relationship between the adjustment factor and the base station signal strength. By adjusting the factor samples, the optimal parameters in the second mathematical model can be obtained; Based on the second mathematical model and its optimal parameters, a base station signal strength adjustment calculation model is constructed.

5. The user positioning method according to claim 4, characterized in that, The construction of the second mathematical model includes: The original base station signal strength is adjusted according to the adjustment factor to obtain the adjusted base station signal strength; Construct the error term of the second mathematical model; The original base station signal strength, the adjusted base station signal strength, and the error term of the second mathematical model are added together to obtain the second objective function; Based on the second objective function, construct a second mathematical model.

6. The user positioning method according to any one of claims 1-5, characterized in that, Determining the location information of the user equipment based on the signal strength of the target base station includes: Based on the signal strength of the target base station, a match is made in the fingerprint database to obtain the location information of the user equipment; the fingerprint database is used to store the signal strength and location information of base stations with correlation.

7. A user positioning device, characterized in that, include: The acquisition module is used to acquire the initial base station signal strength received by the user equipment at the current time and the environmental factor feature vector of its location; The adjustment factor calculation module is used to input the environmental factor feature vector into the base station signal strength adjustment factor calculation model to obtain the adjustment factor output by the base station signal strength adjustment factor calculation model; the base station signal strength adjustment factor calculation model is used to simulate the impact of environmental changes on the base station signal strength and generate the adjustment factor under the current environmental conditions; A base station signal strength adjustment module is used to determine the target base station signal strength based on the adjustment factor and the initial base station signal strength. The positioning module is used to determine the location information of the user equipment based on the signal strength of the target base station.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the user location method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, wherein a computer program is stored on the non-transitory computer-readable storage medium, characterized in that, When the computer program is executed by a processor, it implements the steps of the user location method as described in any one of claims 1 to 6.

10. A computer program product, the computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the user location method as described in any one of claims 1 to 6.

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