Positioning method and fingerprint data generation method

Abstract

A positioning method and a fingerprint data generation method. The positioning method comprises: on the basis of satellite positioning data received by a terminal, acquiring an initial satellite positioning location of the terminal (S101); acquiring candidate positioning points, which are located within a set distance threshold around the initial satellite positioning location (S102); for each candidate positioning point, acquiring satellite prediction data of the candidate positioning point (S103); by means of satellite prediction data and satellite observation data of the candidate positioning points, obtaining scores of the candidate positioning points (S104); and on the basis of the scores of the candidate positioning points, determining a final positioning point of the terminal (S105). The method can improve the accuracy of satellite positioning in an outdoor environment.

Description

Positioning method and fingerprint data generation method

[0001] The present disclosure claims priority to the Chinese patent application No. 202410822121.8, filed on June 24, 2024, and entitled "Positioning method and fingerprint data generation method", the entire content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to the technical field of positioning, and in particular, to a positioning method and a fingerprint data generation method. BACKGROUND

[0003] GNSS (Global Navigation Satellite System) is a general term for the current main satellite positioning and navigation system, mainly including GPS (Global Positioning System) and satellite navigation system. A terminal supporting satellite positioning can determine its positioning position by receiving satellite positioning signals.

[0004] However, the accuracy of satellite positioning is greatly related to the quality of satellite positioning signals received by the terminal. In urban areas with many high-rise buildings or outdoor areas such as valleys with many high mountains, satellite positioning signals will appear reflection, refraction, diffraction and other phenomena when encountering high mountains, high-rise buildings or thick clouds, which will cause the quality of satellite positioning signals received by the terminal to decrease, and further affect the positioning accuracy of the terminal. The lower the positioning accuracy is, the greater the deviation between the positioning position of the terminal obtained by the satellite positioning signal and its real geographical position is. Therefore, how to improve the satellite positioning accuracy in outdoor environment is a technical problem to be solved by those skilled in the art. SUMMARY

[0005] In order to solve the problems in the related art, the embodiments of the present disclosure provide a positioning method and a fingerprint data generation method.

[0006] In a first aspect, the embodiments of the present disclosure provide a positioning method.

[0007] Specifically, the positioning method is used for positioning a terminal in an outdoor environment, and includes:

[0008] obtaining a satellite positioning initial position of the terminal based on satellite positioning data received by the terminal;

[0009] obtaining a candidate positioning point located within a set distance threshold around the satellite positioning initial position;

[0010] obtaining satellite prediction data of the candidate positioning point for each candidate positioning point;

[0011] obtaining a score of the candidate positioning point by satellite prediction data of the candidate positioning point and satellite observation data;

[0012] determining a final positioning point of the terminal based on the score of the candidate positioning point.

[0013] In a second aspect, a method for generating fingerprint data is provided, including:

[0014] obtaining real pseudo-range residuals corresponding to m angle combinations in a target geographic area based on satellite positioning data measured in the target geographic area, the angle combinations including an azimuth angle and an elevation angle, and m being equal to a number of the azimuth angles multiplied by a number of the elevation angles;

[0015] generating m Gaussian models based on the real pseudo-range residuals corresponding to the m angle combinations in the target geographic area, one Gaussian model being used to represent real pseudo-range residuals of one angle combination in the target geographic area.

[0016] In a third aspect, an electronic device is provided, including a processor and a memory, the memory storing computer instructions executable by the processor, the computer instructions being executed by the processor to cause the electronic device to perform the method provided in the first aspect or the second aspect.

[0017] In a fourth aspect, a computer readable storage medium is provided, the computer readable storage medium storing computer executable instructions, the computer executable instructions being executed by a processor to implement the method provided in the first aspect or the second aspect.

[0018] In a fifth aspect, a computer program product is provided, including computer instructions, the computer instructions being executed by a processor to implement the method provided in the first aspect or the second aspect.

[0019] According to the technical scheme provided by the embodiment of the present disclosure, based on the satellite positioning data received by the terminal, the satellite positioning initial position of the terminal is obtained. Since the real position of the terminal is usually located near the satellite positioning initial position, the present disclosure obtains the candidate positioning points located within the set distance threshold around the satellite positioning initial position. Then, for each candidate positioning point, satellite prediction data of the candidate positioning point is obtained, and the score of the candidate positioning point is obtained through the satellite prediction data and satellite observation data of the candidate positioning point. Since the gap between the candidate positioning point and the real position of the terminal in the real world can be known through the satellite prediction data and satellite observation data of the candidate positioning point, the present disclosure characterizes the gap through the scoring of the candidate positioning point. Therefore, even if the surrounding environment blocks causes satellite signals to be reflected, refracted, and the like, based on the scores of these candidate positioning points, the position of the terminal can be accurately positioned, and the accuracy of outdoor positioning is ensured.

[0020] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0021] Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of the non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:

[0022] FIG. 1 shows a flowchart of a positioning method according to an embodiment of the present disclosure;

[0023] FIG. 2 shows a flowchart of a fingerprint data generation method according to an embodiment of the present disclosure;

[0024] FIG. 3 shows a structural block diagram of a positioning device according to an embodiment of the present disclosure;

[0025] FIG. 4 shows a structural block diagram of a fingerprint data generation device according to an embodiment of the present disclosure;

[0026] FIG. 5 shows a structural block diagram of an electronic device according to an embodiment of the present disclosure;

[0027] FIG. 6 shows a structural schematic diagram of a computer system suitable for implementing the method according to the embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings, so that those skilled in the art can easily implement them. In addition, parts irrelevant to the description of the exemplary embodiments are omitted in the drawings for the sake of clarity.

[0029] In the present disclosure, it should be understood that terms such as "include" or "have" are intended to indicate that there are features, numbers, steps, actions, parts or combinations thereof disclosed in the specification, and do not exclude the possibility that one or more other features, numbers, steps, actions, parts or combinations thereof exist or are added.

[0030] In addition, it should be further noted that the embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0031] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present disclosure are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.

[0032] As described above, in urban areas with more high-rise buildings or outdoor areas such as valleys with more high mountains, satellite positioning signals will appear reflection, refraction, diffraction and other phenomena when encountering high mountains, high-rise buildings or thick clouds, which will cause the quality of satellite positioning signals received by the terminal to decline, and further affect the positioning accuracy of the terminal. The lower the positioning accuracy is, the greater the deviation between the positioning position of the terminal obtained through the satellite positioning signal and the real geographical position of the terminal in the real world is. Therefore, how to improve the satellite positioning accuracy in the outdoor complex environment is a technical problem to be solved by those skilled in the art.

[0033] To this end, the present disclosure provides a positioning method, the principle of which is to obtain candidate positioning points located around the initial position of the terminal in satellite positioning, to determine the gap between the candidate positioning points and the real position of the terminal through satellite prediction data of the candidate positioning points and satellite observation data actually measured by the terminal in the real world, and to determine the final positioning point of the terminal from the position of the candidate positioning points based on the gap. Since the gap between the candidate positioning points and the real position of the terminal can be determined through satellite prediction data of the candidate positioning points and satellite observation data actually measured by the terminal in the real world, even if the outdoor environment where the terminal is located appears satellite signal reflection, refraction and other phenomena, resulting in poor quality of the positioning satellite signal received by the terminal, the present disclosure can still accurately position the position of the terminal.

[0034] In a possible implementation, the positioning method is applicable to terminals such as a mobile phone, a portable Android device (PAD), a smart watch, and a vehicle-mounted device (vehicle machine) that can perform positioning. When the terminal needs to determine its position to provide a location-based service such as a pickup point recommendation service of a network car-hailing or a navigation (driving navigation or outdoor walking navigation) service to a user, the positioning method provided by the present disclosure can be performed to determine the position of the terminal.

[0035] FIG. 1 shows a flowchart of a positioning method according to an embodiment of the present disclosure, which includes the following steps S101-S105:

[0036] In step S101, an initial satellite positioning position of the terminal is obtained based on satellite positioning data received by the terminal.

[0037] The satellite positioning data of the present disclosure includes a satellite number, a satellite signal timestamp, and the like. Step S101 can be implemented based on existing satellite positioning technology, which is not limited by the present disclosure. Since the present disclosure needs to obtain the initial satellite positioning position of the terminal by using satellite positioning data of the terminal device, the positioning method provided by the present disclosure is applicable to terminals that are in an outdoor environment and can receive satellite positioning signals.

[0038] When the satellite signal is reflected or refracted in an outdoor environment (such as a high-rise area, a canyon, a mountain, or thick clouds) where the terminal is located, the quality of the satellite positioning data received by the terminal will be affected. However, in most cases, the position of the terminal can still be obtained based on the satellite positioning data, but the accuracy of the position will be greatly different from the real position of the terminal in the real world. If the position is directly output to a service that needs to use the position, the quality of the service will be poor, and the user experience will be affected.

[0039] In step S102, a candidate positioning point within a set distance threshold around the initial satellite positioning position is obtained.

[0040] As described above, although the initial satellite positioning position may drift, the difference between the real position of the terminal in the real world and the initial satellite positioning position will not be very large. Therefore, the present disclosure takes the initial satellite positioning position as a reference to obtain the candidate positioning point by scattering points within the set distance threshold around the initial satellite positioning position. The candidate positioning point can be obtained by uniformly scattering points around the initial satellite positioning position, for example, a plurality of candidate positioning points can be obtained by uniformly scattering points at an interval of 2 m within a range of 30 m (Meter, m) around the initial satellite positioning position.

[0041] In step S103, satellite prediction data of each candidate positioning point is obtained;

[0042] In step S104, a score of each candidate positioning point is obtained by the satellite prediction data and satellite observation data of the candidate positioning point;

[0043] The disclosure obtains satellite prediction data corresponding to each candidate positioning point, that is, satellite data that can be observed in the real world by the candidate positioning point. Satellite observation data is satellite data observed by the terminal at the real position in the real world at the moment. Therefore, the difference between the candidate positioning point and the real position of the terminal in the real world can be determined by the satellite prediction data and satellite observation data of the candidate positioning point, and the disclosure represents the difference by scoring the candidate positioning point. For example, the smaller the difference between the candidate positioning point and the real position of the terminal in the real world, the higher the score, and vice versa.

[0044] In step S105, the final positioning point of the terminal is determined based on the score of the candidate positioning point;

[0045] One embodiment of step S105 is to determine the candidate positioning point with the highest score as the final positioning point of the terminal. Another embodiment is to select the n candidate positioning points with the highest scores, and determine the relative center point of the n candidate positioning points as the final positioning point of the terminal. Any embodiment that can reasonably determine the final positioning point of the terminal based on the score of the candidate positioning point is within the scope of the disclosure, and the disclosure does not exhaust all embodiments.

[0046] FIG. 1 shows a positioning method provided by the disclosure, which can ensure accurate positioning of a terminal in the outdoor. Since positioning is usually divided into outdoor positioning and indoor positioning, the technologies used in the two scenarios are quite different. In order to ensure that the correct technology is used for positioning, the method provided by the embodiments of the disclosure can further include the following steps when implemented:

[0047] If the terminal is in the outdoor and the satellite positioning signal quality is poor, the positioning method provided by the embodiments can be executed. If the terminal is not in the outdoor but in the indoor, other positioning methods suitable for the indoor can be executed.

[0048] The satellite positioning data received by the terminal can be used to determine whether the terminal is outdoors. For example, the number of satellites searched by the terminal based on the satellite positioning data, the carrier-to-noise ratio of the satellite signal, and the like can be used to determine whether the terminal is outdoors. Generally, compared with the outdoor environment, when the terminal is located indoors, the number of satellites that can be searched is small or zero, and the carrier-to-noise ratio is small. Therefore, the satellite positioning data received by the terminal can be used to determine whether the terminal is outdoors. In an example, a trained model can be used to identify whether the terminal is outdoors. The input of the model is the satellite positioning data received by the terminal, and the output includes a prediction result of whether the terminal is outdoors and a confidence level. For example, when the confidence level of the output result that the terminal is outdoors is greater than 60%, it is determined that the terminal is outdoors. In this case, the positioning method provided by the present disclosure can be performed.

[0049] The satellite positioning initial position of the terminal can be obtained based on the satellite positioning data received by the terminal. Since the real position of the terminal is generally located near the satellite positioning initial position, the present disclosure obtains candidate positioning points located within a set distance threshold around the satellite positioning initial position. Then, for each candidate positioning point, satellite prediction data of the candidate positioning point is obtained. The score of the candidate positioning point is obtained based on the satellite prediction data and the satellite observation data of the candidate positioning point. Since the satellite prediction data and the satellite observation data of the candidate positioning point can be used to determine the difference between the candidate positioning point and the real position of the terminal in the real world, the present disclosure uses the score of the candidate positioning point to represent the difference. Therefore, even if the surrounding environment blocks the satellite signal and causes reflection, refraction, or the like, the position of the terminal can be accurately positioned based on the scores of the candidate positioning points, thereby ensuring the accuracy of outdoor positioning.

[0050] The positioning method described above will be described in detail in combination with different embodiments.

[0051] In a first embodiment, the satellite prediction data includes predicted pseudorange. Specifically,

[0052] In step S103, for each candidate positioning point, satellite prediction data of the candidate positioning point is obtained. The following implementation can be used:

[0053] The current satellite ephemeris information is obtained. The sky obstruction information is generated based on the position of the candidate positioning point and the three-dimensional building data around the position. The satellites are marked as visible satellites and / or invisible satellites based on the sky obstruction information and the satellite ephemeris information. The predicted pseudorange of the visible satellites and / or the predicted pseudorange of the invisible satellites are calculated based on the satellite ephemeris information and the position of the candidate positioning point.

[0054] The satellite ephemeris information is also referred to as two-line orbital element (TLE) of the satellite. The current satellite ephemeris information refers to satellite ephemeris information at the time of performing positioning. The current satellite ephemeris information records positions of each satellite in the sky at the time of positioning.

[0055] The skyMask information represents information about a blocking condition of the sky by a blocking object at a geographic location in the real world. The blocking object can be represented by a height angle corresponding to a 0-360-degree azimuth angle as the skyMask. For example, a 360-dimensional array can be generated, and each dimension records a height angle of a blocking object at an azimuth angle. Details about the skyMask acquisition method are described below.

[0056] In this embodiment, based on the sky blocking information at the candidate positioning point and the current satellite ephemeris information, the relative positional relationship between the candidate positioning point and surrounding buildings and each satellite can be determined. Based on the relative positional relationship, a satellite in the sky that is blocked by a building and cannot be seen from the candidate positioning point is marked as an invisible satellite, and a satellite that can be seen from the candidate positioning point and is not blocked by a building is marked as a visible satellite.

[0057] In this embodiment, based on the positions of each satellite in the sky recorded in the satellite ephemeris information and the position of the candidate positioning point, the predicted pseudorange between the satellite and the candidate positioning point can be calculated, that is, the predicted pseudorange of the visible satellite and / or the predicted pseudorange of the invisible satellite at the candidate positioning point can be determined.

[0058] The satellite observation data includes an observed pseudorange. In step S104, the score of the candidate positioning point is obtained based on the satellite prediction data and the satellite observation data at the candidate positioning point. The following embodiments can be used:

[0059] Based on the satellite positioning data received by the terminal, the observed pseudorange of the satellite is obtained.

[0060] Based on the predicted pseudorange of the visible satellite and / or the predicted pseudorange of the invisible satellite, and the observed pseudorange of the satellite, the pseudorange residual of the visible satellite and / or the invisible satellite is obtained.

[0061] The candidate positioning point is scored based on a first proportion of the visible satellites with a pseudorange residual of 0 and / or a second proportion of the invisible satellites with a pseudorange residual greater than 0. The first proportion is the ratio of the number of visible satellites with a pseudorange residual of 0 to the total number of visible satellites. The second proportion is the ratio of the number of invisible satellites with a pseudorange residual greater than 0 to the total number of invisible satellites.

[0062] Among them, the satellite positioning data of the present disclosure includes satellite number, satellite signal timestamp, etc., the satellite signal timestamp includes satellite signal broadcast timestamp (carried in the satellite signal corresponding to the satellite number, the timestamp is determined according to the clock on the satellite corresponding to the satellite number) and satellite signal receiving timestamp (the target device determines the time when the satellite signal corresponding to the satellite number is received with its own device clock). The terminal can calculate the observed pseudo-range of the satellite corresponding to the satellite number in the real world by multiplying the time difference between the satellite signal broadcast timestamp and the satellite signal receiving timestamp received in the real world real position by the speed of light. Since the distance between the satellite and the terminal calculated by using this time difference does not consider factors such as atmospheric refraction delay, it is not the actual distance between the satellite and the terminal, so it is called observed pseudo-range.

[0063] The pseudo-range residual refers to the difference between the observed pseudo-range between the terminal and the satellite and the actual distance. In actual application, it is found that the pseudo-range residual of the visible satellite measured by the terminal in the real world real position is a small error (very small error is recorded as 0) of 0, and the pseudo-range residual of the invisible satellite is a positive value.

[0064] Therefore, for each candidate positioning point, in order to determine the gap between the candidate positioning point and the real position of the terminal in the real world, and further score the candidate positioning point, the difference between the predicted pseudo-range of each satellite at the candidate positioning point and the observed pseudo-range of each satellite measured by the terminal at the real position of the terminal in the real world can be used as the pseudo-range residual of each satellite at the candidate positioning point. The satellites at the candidate positioning point can be divided into visible satellites and invisible satellites. The pseudo-range residual of the visible satellites at the candidate positioning point can be obtained. The ratio of the number of visible satellites with a pseudo-range residual of 0 to the total number of visible satellites is calculated as a first ratio. If the first ratio is higher, it means that the similarity between the satellite predicted pseudo-range of the visible satellite corresponding to the candidate positioning point and the satellite predicted pseudo-range of the visible satellite measured by the terminal at the real position of the terminal in the real world is higher. It means that the candidate positioning point is closer to the real position of the terminal in the real world. The score of the candidate positioning point can be higher. Otherwise, the score of the candidate positioning point can be lower. Alternatively, the pseudo-range residual of the invisible satellites at the candidate positioning point can also be obtained. The ratio of the number of invisible satellites with a pseudo-range residual greater than 0 to the total number of invisible satellites is calculated as a second ratio. If the second ratio is higher, it means that the similarity between the satellite predicted pseudo-range of the invisible satellite corresponding to the candidate positioning point and the satellite predicted pseudo-range of the invisible satellite measured by the terminal at the real position of the terminal in the real world is higher. It means that the candidate positioning point is closer to the real position of the terminal in the real world. The score of the candidate positioning point can be higher. Otherwise, the score of the candidate positioning point can be lower. Alternatively, the first ratio and the second ratio can be used to comprehensively determine the score of the candidate positioning point. For example, the average of the first ratio and the second ratio can be calculated. The higher the average, the higher the score of the candidate positioning point. The lower the average, the lower the score of the candidate positioning point.

[0065] In the first embodiment, step S105 can adopt the implementation described above, which will not be described again. In addition, in order to reduce repetitive content, if different embodiments adopt the same implementation, the present disclosure only describes it once and does not repeat the description.

[0066] In the second embodiment, the satellite prediction data includes predicted pseudo-range, specifically:

[0067] In step S103, for each candidate positioning point, the acquisition of satellite prediction data of the candidate positioning point can adopt the following implementation:

[0068] Based on the satellite ephemeris information and the position of the candidate positioning point, the predicted pseudo-range of the satellite is calculated.

[0069] The current satellite ephemeris information records the positions of each satellite in the sky at the positioning time. Based on the positions of each satellite in the sky and the position of the candidate positioning point, the predicted pseudo-range between each satellite and the candidate positioning point can be calculated.

[0070] In step S104, the score of the candidate positioning point is obtained based on the satellite prediction data and the satellite observation data of the candidate positioning point. The following implementation can be used:

[0071] Based on the satellite positioning data received by the terminal, the observed pseudo-range of the satellite is obtained.

[0072] Based on the predicted pseudo-range of the satellite and the observed pseudo-range of the satellite, the actual pseudo-range residual of the satellite is obtained.

[0073] Based on the position of the candidate positioning point and the satellite ephemeris information, the real pseudo-range residual of the satellite is obtained through a pre-established pseudo-range residual fingerprint library.

[0074] For each satellite, the matching degree of the satellite is obtained according to the actual pseudo-range residual and the real pseudo-range residual of the satellite.

[0075] The matching degrees of all satellites are fused, and the score of the candidate positioning point is obtained based on the fused matching degrees.

[0076] According to the first embodiment described above, the terminal can obtain the observed pseudo-range of the satellite based on the satellite positioning data received by the terminal. For each candidate positioning point, the difference between the predicted pseudo-range of each satellite and the observed pseudo-range of the satellite can be calculated to obtain the actual pseudo-range residual of the satellite.

[0077] The pseudo-range residual fingerprint library includes the real pseudo-range residual of the satellite when the satellite runs to each corresponding position in the sky at each geographic location. The real pseudo-range residual in the pseudo-range residual fingerprint library is obtained by actual measurement in advance.

[0078] In this implementation, the current satellite ephemeris information records the positions of each satellite in the sky at the time of positioning. For each candidate positioning point, the real pseudo-range residual of the satellite when the satellite runs to the position in the sky at the time of positioning can be obtained based on the position of the candidate positioning point and the positions of each satellite in the sky at the time of positioning.

[0079] In this embodiment, the candidate positioning point corresponds to multiple satellites. For each satellite, the matching degree between the actual pseudorange residual and the true pseudorange residual can be calculated. This matching degree is used as the satellite's matching degree. The matching degrees of all satellites are fused, and the score of the candidate positioning point is obtained based on the fused matching degree. For example, the matching degrees of each satellite can be weighted and averaged or arithmetic averaged to obtain the fused matching degree. The higher the fused matching degree, the closer the candidate positioning point is to the terminal's true location, and the higher the score of the candidate positioning point. The fused matching degree can be directly used as the score of the candidate positioning point, or the score corresponding to the matching degree range in which the fused matching degree falls can be used as the score of the candidate positioning point according to a pre-set correspondence between the fused matching degree range and the score. Any implementation method that can reasonably obtain the score of the candidate positioning point based on the fused matching degree is within the scope of this disclosure, and this disclosure will not exhaustively describe various implementation methods.

[0080] In one possible implementation, the pseudorange residual fingerprint database records a Gaussian model, which is used to characterize the true pseudorange residual of satellites in a geographic area at a combination of angles, including azimuth and elevation.

[0081] Accordingly, the step S104, which involves obtaining a portion of the satellite's true pseudorange residual based on the candidate positioning point's location and the satellite ephemeris information using a pre-established pseudorange residual fingerprint database, can be implemented using the following method:

[0082] Based on the satellite's three-dimensional coordinates and the candidate positioning points' three-dimensional coordinates from the satellite ephemeris information, the satellite's elevation angle and azimuth angle are calculated.

[0083] Based on the position of the candidate positioning point, the elevation angle and azimuth angle of the satellite, the true pseudorange residual of the satellite is obtained from the Gaussian model.

[0084] In this embodiment, the geographical area can be a grid area divided according to a predetermined rule, for example, the geographical area can be divided into grids with a grid size of 2m*2m.

[0085] One Gaussian model records the true pseudorange residuals corresponding to a combination of elevation and azimuth angles for a geographic region. The elevation and azimuth angles in the Gaussian model can be integers. For example, the elevation angle can range from 1 to 90 degrees (90 values), and the azimuth angle can range from 1 to 360 degrees (360 values). Therefore, the Gaussian model records 90 elevation angles and 360 azimuth angle combinations, resulting in a total of 90 * 360 possible true pseudorange residuals. The method for obtaining the Gaussian model will be explained in detail later.

[0086] In this embodiment, based on the three-dimensional coordinates of the satellite in the satellite ephemeris information and the coordinates of the candidate positioning point, the elevation angle and the azimuth angle of the candidate positioning point relative to the satellite can be calculated, based on the position of the candidate positioning point, the geographical region where the candidate positioning point is located can be determined, the pseudo-range residual fingerprint library is searched, the geographical region where the candidate positioning point is located can be obtained, and the angle combination is the elevation angle and the azimuth angle corresponding to the Gaussian model of the satellite, and the real pseudo-range residual of the satellite can be obtained from the corresponding Gaussian model.

[0087] In a third embodiment, the satellite prediction data includes predicted visibility, and the satellite observation data includes observed visibility of the satellite. Specifically:

[0088] In step S103, for each candidate positioning point, satellite prediction data of the candidate positioning point is obtained, which can use the following embodiments:

[0089] Obtain the current satellite ephemeris information;

[0090] Generate sky obstruction information according to the position of the candidate positioning point and three-dimensional building data around the position;

[0091] Obtain the predicted visibility of the satellite based on the sky obstruction information and the satellite ephemeris information.

[0092] The process of generating the sky obstruction information according to the position of the candidate positioning point and the three-dimensional building data around the position can refer to the description of the related embodiments, which will not be repeated here.

[0093] The predicted visibility is the predicted visibility of the satellite, for example, the predicted visibility can be the predicted satellite signal carrier-to-noise ratio of each satellite received at the candidate positioning point, or the length of all direct and reflected paths of the satellite signal of each satellite reaching the candidate positioning point.

[0094] For example, the SDM (Shadow Matching) algorithm can be used to predict the satellite signal carrier-to-noise ratio of each satellite received at the candidate positioning point based on the sky obstruction information, the position of the candidate positioning point, and the satellite position recorded in the satellite ephemeris information; or the RT (Ray Tracing) algorithm can be used to predict the length of all direct and reflected paths of the satellite signal of each satellite reaching the candidate positioning point based on the sky obstruction information and the satellite position recorded in the satellite ephemeris information.

[0095] In step S104, the score of the candidate positioning point is obtained by the satellite prediction data and the satellite observation data of the candidate positioning point, which can use the following embodiments:

[0096] obtaining an observation visibility of the satellite based on satellite positioning data received by the terminal;

[0097] obtaining a score of the candidate positioning point according to the predicted visibility and the observation visibility of the satellite.

[0098] In this embodiment, when the predicted visibility is a carrier-to-noise ratio of each satellite signal received at the candidate positioning point, the observation visibility of the satellite is a carrier-to-noise ratio of each satellite signal of the satellite observed in the real world by the terminal, where the satellite positioning data received by the terminal includes a received satellite signal, and a ratio of a carrier power and a noise power of the received satellite signal is the carrier-to-noise ratio of the satellite signal.

[0099] For each candidate positioning point, a similarity between the predicted carrier-to-noise ratio of each satellite signal received at the candidate positioning point and the carrier-to-noise ratio of each satellite signal currently received by the terminal can be calculated, the higher the similarity, the smaller the gap between the candidate positioning point and the real position of the terminal, and the higher the score of the candidate positioning point.

[0100] In this embodiment, when the predicted visibility is a length of all direct and reflected paths of each satellite signal to the candidate positioning point, the observation visibility of the satellite is a satellite observation pseudo-range observed in the real world by the terminal (for the calculation process of the satellite observation pseudo-range, refer to the related description of the first embodiment, which will not be described here). For a candidate positioning point, for each satellite, the length of all direct and reflected paths is traversed, and the length of the path with the smallest error of the satellite observation pseudo-range is selected, and the difference between the two is the pseudo-range residual of the satellite. Thus, for each candidate positioning point, the square values of the pseudo-range residuals of all satellites can be added to obtain the overall error of the candidate positioning point, the smaller the overall error, the more similar the predicted propagation path length for the candidate positioning point to the satellite observation pseudo-range observed in the real world by the terminal, and the smaller the gap between the candidate positioning point and the real position of the terminal in the real world, and the higher the score of the candidate positioning point.

[0101] For the foregoing embodiments using SkyMask, the present disclosure can further include, on the basis of the method of the foregoing embodiments:

[0102] obtaining a three-dimensional map coverage of a predetermined area matched with the candidate positioning point based on pre-prepared three-dimensional map data, the predetermined area being an area with a distance less than a predetermined value from the candidate positioning point;

[0103] obtaining three-dimensional building data around the position of the candidate positioning point in response to the three-dimensional map coverage of the predetermined area being greater than a predetermined threshold.

[0104] In this embodiment, the three-dimensional map coverage rate in a predetermined area (for example, a predetermined area with a predetermined value of 300 m) around the candidate positioning point can be queried from the pre-prepared three-dimensional map data according to the position of the candidate positioning point. If the three-dimensional map coverage rate is greater than a predetermined threshold, it indicates that the three-dimensional building data around the position of the candidate positioning point is valid, and the three-dimensional building data around the position of the candidate positioning point can be obtained from the pre-prepared three-dimensional map data, and then the sky obstruction information of the candidate positioning point is determined in combination with the position of the candidate positioning point.

[0105] It should be noted that if the three-dimensional map coverage rate is less than or equal to a predetermined threshold, it indicates that the three-dimensional building data around the position of the candidate positioning point can be missing, and the terminal can prompt the user to turn on the camera of the terminal and obtain the surrounding image information and the corresponding shooting angle information at the real position of the terminal in a way of taking pictures in a circle. Based on the environmental image information and the corresponding shooting angle information taken by the shooting device on the terminal, the sky obstruction information of the candidate positioning point is obtained. The shooting angle information refers to the direction when taking the surrounding image. The pointing information when taking the picture is measured by sensors such as gyroscopes, compasses, etc. on the terminal, and the heading information of satellite positioning can be obtained, so that the shooting angle information can be obtained. According to the environmental image information and the corresponding shooting angle information, the current sky obstruction information of the terminal can be extracted, and the current sky obstruction information of the terminal can be used as the sky obstruction information of the candidate positioning point. In this way, the sky obstruction information at the real position of the terminal is obtained by visual reconstruction of the surrounding image taken by the terminal at the real position, and the sky obstruction information of the candidate positioning point is obtained. The camera advantage of the terminal is fully utilized. Even if the three-dimensional map is missing or the three-dimensional map is low in accuracy, the sky obstruction information can be quickly reconstructed by the user in a way of taking pictures in a circle, and then the distance between each candidate positioning point and the real position of the terminal is accurately predicted according to the sky obstruction information, the scores of each candidate positioning point are obtained, and the final positioning point of the terminal is accurately determined, which greatly expands the available range of the scheme.

[0106] Based on the foregoing embodiments provided by the present disclosure, the foregoing three embodiments can be combined in any manner to determine the score of each candidate positioning point, and more accurate positioning of the terminal can be achieved based on the score of each candidate positioning point. For example, any two embodiments can be combined to determine the score of each candidate positioning point. In this case, for a candidate positioning point, the scores of the candidate positioning point obtained by the two embodiments can be combined to obtain the score of the candidate positioning point. For example, when the first embodiment is used to score the candidate positioning point based on the first proportion of the pseudorange residual of the visible satellite being 0 and / or the second proportion of the pseudorange residual of the invisible satellite being greater than 0, the second embodiment is used to score the candidate positioning point based on the fusion matching degree of the satellite, and then the two scores of the candidate positioning point are weighted and averaged to obtain the score of the candidate positioning point. Alternatively, the three embodiments can be combined to achieve more accurate positioning of the terminal. In this case, the same candidate positioning point can be scored by using the scoring scheme provided by each of the three embodiments, and then the three scores are weighted and averaged to obtain the score of the candidate positioning point.

[0107] As described above, the true pseudorange residual of the satellite can be obtained through the pseudorange residual fingerprint library in the second embodiment of the present disclosure. To this end, the present disclosure provides a fingerprint data generation method by which the pseudorange residual fingerprint library can be generated.

[0108] FIG. 2 shows a flowchart of a fingerprint data generation method according to an embodiment of the present disclosure. As shown in FIG. 2, the method includes the following steps:

[0109] In step S201, based on the satellite positioning data actually measured in a target geographic region, the true pseudorange residual corresponding to m angle combinations in the target geographic region is obtained, the angle combinations including an azimuth angle and an elevation angle, and m is equal to the number of azimuth angles multiplied by the number of elevation angles;

[0110] In step S202, m Gaussian models are generated according to the true pseudorange residual corresponding to m angle combinations in the target geographic region, and one Gaussian model is used to represent the true pseudorange residual of the target geographic region in one angle combination.

[0111] The fingerprint data generation method is applicable to a computer, a computing device, a server, a server cluster, or the like that can generate fingerprint data.

[0112] The target geographic region can be a grid region divided according to a predetermined rule. For example, the target geographic region can be a grid divided according to a 2m*2m grid size.

[0113] The Gaussian model records the corresponding real pseudo-range residuals of different combinations of elevation angles and azimuth angles at the target geographic region. The elevation angles and azimuth angles in the Gaussian model can be integers. For example, the elevation angles can be 1-90 degrees, and there are 90 values in total. The azimuth angles can be 1-360 degrees, and there are 360 values in total. The Gaussian model records the corresponding real pseudo-range residuals of 90 elevation angles and 360 azimuth angles, that is, the corresponding real pseudo-range residuals of 90*360 combinations of angles.

[0114] In this embodiment, the satellite initial positioning point of the device can be determined by using an existing satellite positioning technology (such as PPP (Precise Point Positioning), RTK (Real Time Kinematic), SPP (Standard Point Positioning), or the like), and then the satellite initial positioning point is calibrated to the corresponding road according to a route matching method to obtain the position of the calibrated positioning point. Based on the satellite positioning data measured at the calibrated positioning point uploaded by the device, the satellite observation pseudo-range can be calculated. Based on the position of the calibrated positioning point and the position in the sky in the current satellite ephemeris information, the satellite actual distance can be obtained. The difference between the satellite actual distance and the satellite observation pseudo-range is determined as the real pseudo-range residual. In this way, for a geographic region, the real pseudo-range residuals of satellites corresponding to a large number of calibrated positioning points in the geographic region can be obtained. The measured time is different, and the azimuth angle and the elevation angle of the satellite are also different. Therefore, the real pseudo-range residuals of the satellite at different angle combinations can be obtained.

[0115] In this embodiment, the real pseudo-range residuals corresponding to each angle combination in a geographic region are fitted to obtain a Gaussian model. In this way, m Gaussian models can be obtained for each geographic region. The Gaussian model includes n individual Gaussian models, that is, Gaussian model GMM(p, e, a) = a1*G(u1, sigma1) + a2*G(u2, sigma2) + … + an*G(uni, sigmai), where G(u, sigma) represents a Gaussian model with mean u and standard deviation sigma, and a represents the weight of the Gaussian model G(u, sigma). n *G(u n ,sigma n ), where G(u n ,sigma n ) represents a Gaussian model with mean u n and standard deviation sigma n , and a n represents the weight of the Gaussian model G(u n ,sigma nprobability of the candidate positioning point being in the geographic region, p represents a position of the geographic region, e and a represent an angle combination of an azimuth angle a and an elevation angle e, there is only one direct path and several reflection paths of the pseudorange propagation path from the satellite in a fixed direction at a fixed position, n is the number of the pseudorange propagation paths of the satellite at the angle combination of the azimuth angle a and the elevation angle e at the position p, u n is a center point of the pseudorange residual error on the n-th pseudorange propagation path, and sigma n is a standard deviation of the pseudorange residual error on the n-th pseudorange propagation path; thus, a Gaussian model can be used to represent the real pseudorange residual error distribution of a geographic region corresponding to different angle combinations, and several Gaussian models constitute the pseudorange residual error fingerprint library.

[0116] In this embodiment, based on the three-dimensional coordinates of the satellite in the satellite ephemeris information and the three-dimensional coordinates of the candidate positioning point, the elevation angle and the azimuth angle of the candidate positioning point relative to the satellite can be calculated, the geographic region where the candidate positioning point is located can be determined based on the position of the candidate positioning point, the geographic region where the candidate positioning point is located can be obtained by searching the pseudorange residual error fingerprint library, the Gaussian model corresponding to the elevation angle and the azimuth angle of the satellite, and the real pseudorange residual error of the satellite can be obtained from the corresponding Gaussian model.

[0117] FIG. 3 shows a structural block diagram of a positioning device according to an embodiment of the present disclosure. The device can be realized as part or all of an electronic device through software, hardware, or a combination of both. As shown in FIG. 3, the positioning device includes:

[0118] An initial positioning module 301 configured to obtain a satellite positioning initial position of the terminal based on satellite positioning data received by the terminal;

[0119] A candidate obtaining module 302 configured to obtain a candidate positioning point located within a set distance threshold around the satellite positioning initial position;

[0120] A prediction module 303 configured to obtain satellite prediction data of each candidate positioning point;

[0121] A scoring module 304 configured to obtain a score of the candidate positioning point through the satellite prediction data and satellite observation data of the candidate positioning point;

[0122] A positioning module 305 configured to determine a final positioning point of the terminal based on the score of the candidate positioning point.

[0123] In a possible implementation, the prediction module 303 is configured to:

[0124] obtain current satellite ephemeris information;

[0125] generate sky occlusion information according to the position of the candidate positioning point and three-dimensional building data around the position;

[0126] mark the satellite as a visible satellite and / or an invisible satellite based on the sky occlusion information and the satellite ephemeris information;

[0127] calculate predicted pseudo-range of the visible satellite and / or predicted pseudo-range of the invisible satellite based on the satellite ephemeris information and the position of the candidate positioning point.

[0128] In a possible implementation, the scoring module 304 is configured to:

[0129] obtain observed pseudo-range of the satellite based on satellite positioning data received by the terminal;

[0130] obtain pseudo-range residual of the visible satellite and / or the invisible satellite based on the predicted pseudo-range of the visible satellite and / or the predicted pseudo-range of the invisible satellite, and the observed pseudo-range of the satellite;

[0131] score the candidate positioning point based on a first proportion of the visible satellite whose pseudo-range residual is 0 and / or a second proportion of the invisible satellite whose pseudo-range residual is greater than 0, wherein the first proportion is a ratio of the number of the visible satellite whose pseudo-range residual is 0 to the total number of the visible satellite; and the second proportion is a ratio of the number of the invisible satellite whose pseudo-range residual is greater than 0 to the total number of the invisible satellite.

[0132] In a possible implementation, the prediction module 303 is configured to:

[0133] calculate predicted pseudo-range of the satellite based on the satellite ephemeris information and the position of the candidate positioning point.

[0134] In a possible implementation, the scoring module 304 is configured to:

[0135] obtain observed pseudo-range of the satellite based on satellite positioning data received by the terminal;

[0136] obtain actual pseudo-range residual of the satellite based on the predicted pseudo-range of the satellite and the observed pseudo-range of the satellite;

[0137] obtain real pseudo-range residual of the satellite by a pre-established pseudo-range residual fingerprint library based on the position of the candidate positioning point and the satellite ephemeris information;

[0138] obtain matching degree of the satellite according to the actual pseudo-range residual and the real pseudo-range residual of the satellite for each satellite;

[0139] The matching degrees of all satellites are fused, and a score of the candidate positioning point is obtained based on the fused matching degrees.

[0140] In a possible implementation, the pseudorange residual fingerprint library records Gaussian models, one Gaussian model is used to represent the real pseudorange residual of a satellite of a geographic region at an angle combination, the angle combination includes an azimuth angle and an elevation angle; the scoring module 304 obtains the real pseudorange residual of a satellite by the pre-established pseudorange residual fingerprint library based on the position of the candidate positioning point and the satellite ephemeris information, including:

[0141] Based on the three-dimensional coordinates of the satellite in the satellite ephemeris information and the three-dimensional coordinates of the candidate positioning point, the elevation angle and the azimuth angle of the satellite are calculated.

[0142] Based on the position of the candidate positioning point, the elevation angle and the azimuth angle of the satellite, the real pseudorange residual of the satellite is obtained from the Gaussian model.

[0143] In a possible implementation, the prediction module 303 is configured to:

[0144] Obtain current satellite ephemeris information;

[0145] Generate sky occlusion information according to the position of the candidate positioning point and three-dimensional building data around the position;

[0146] Obtain the predicted visibility of the satellite based on the sky occlusion information and the satellite ephemeris information.

[0147] In a possible implementation, the scoring module 304 is configured to:

[0148] Obtain the observed visibility of the satellite based on the satellite positioning data received by the terminal;

[0149] Obtain the score of the candidate positioning point according to the predicted visibility and the observed visibility of the satellite.

[0150] In a possible implementation, the apparatus further includes:

[0151] A coverage acquisition module configured to acquire a three-dimensional map coverage of a predetermined region matched with the candidate positioning point based on pre-prepared three-dimensional map data, the predetermined region being a region with a distance less than a predetermined value from the candidate positioning point;

[0152] A data acquisition module configured to acquire three-dimensional building data around the position of the candidate positioning point in response to the three-dimensional map coverage of the predetermined region being greater than a predetermined threshold.

[0153] FIG. 4 shows a structural block diagram of a fingerprint data generation apparatus according to an embodiment of the present disclosure. The apparatus can be implemented by software, hardware, or a combination of both, as part of or all of an electronic device. As shown in FIG. 4, the fingerprint data generation apparatus includes:

[0154] a measurement module 401 configured to obtain real pseudorange residuals corresponding to m angle combinations of a target geographic area based on satellite positioning data measured in the target geographic area, the angle combinations including an azimuth angle and an elevation angle, m being equal to the number of azimuth angles multiplied by the number of elevation angles;

[0155] a generation module 402 configured to generate m Gaussian models according to the real pseudorange residuals corresponding to the m angle combinations of the target geographic area, one Gaussian model being used to represent the real pseudorange residuals of one angle combination of the target geographic area.

[0156] The technical terms and technical features mentioned in the apparatus embodiments are the same as or similar to those in the method embodiments. For the explanation and description of the technical terms and technical features involved in the apparatus, reference can be made to the explanation and description of the method embodiments, which will not be repeated here.

[0157] The present disclosure also discloses an electronic device. FIG. 5 shows a structural block diagram of an electronic device according to an embodiment of the present disclosure.

[0158] As shown in FIG. 5, the electronic device 500 includes a memory 501 and a processor 502, wherein the memory 501 is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor 502 to implement any one of the methods provided in the embodiments of the present disclosure.

[0159] FIG. 6 shows a structural schematic diagram of a computer system suitable for implementing the method according to the embodiments of the present disclosure.

[0160] As shown in FIG. 6, the computer system 600 includes a processing unit 601, which can perform various processes in the above embodiments according to programs stored in a Read-Only Memory (ROM) 602 or loaded from a storage portion 608 to a Random Access Memory (RAM) 603. Various programs and data required for the operation of the computer system 600 are also stored in the RAM 603. The processing unit 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An Input / Output (I / O) interface 605 is also connected to the bus 604.

[0161] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as necessary. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 610 as necessary, so that a computer program read out therefrom is installed in the storage section 608 as necessary. Among them, the processing unit 601 can be implemented as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a TPU (Tensor Processing Unit), a FPGA (Field Programmable Gate Array), a NPU (Neural network Processing Unit), etc.

[0162] In particular, according to embodiments of the present disclosure, the method described above can be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising computer instructions which, when executed by a processor, implement the method steps described above. In such embodiments, the computer program product can be downloaded and installed from a network by the communication section 609, and / or installed from the removable medium 611.

[0163] The flow and block diagrams in the drawings represent possible architectural, functional, and operational architectures of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block can represent a module, a segment, or a portion of code that comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or in the reverse order, depending on the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.

[0164] The units or modules described in the embodiments of the present disclosure can be implemented by software, or by programmable hardware. The described units or modules can also be arranged in a processor, and the names of the units or modules do not constitute a limitation on the units or modules themselves in some cases.

[0165] As another aspect, the present disclosure also provides a computer readable storage medium, which can be the computer readable storage medium included in the electronic device or the computer system in the above embodiments, or can exist separately and not be assembled into the device. The computer readable storage medium stores one or more computer-executable instructions, which are used by one or more processors to execute the method described in the present disclosure.

[0166] The above description is merely preferred embodiments of the present disclosure and a description of the applied technical principles. Those skilled in the art should understand that the inventive scope of the present disclosure is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by the combinations of the above technical features or equivalent features without departing from the inventive concept. For example, the above features can be replaced with the technical features disclosed in the present disclosure (but not limited to) having similar functions to form technical solutions.

Claims

1. A positioning method, wherein, The method for locating a terminal located outdoors includes: Based on the satellite positioning data received by the terminal, the initial satellite positioning position of the terminal is obtained; Obtain candidate positioning points located within a set distance threshold around the initial satellite positioning position; For each candidate location point, obtain the satellite prediction data of the candidate location point; The score of the candidate location is obtained by using satellite prediction data and satellite observation data of the candidate location; The final location of the terminal is determined based on the scores of the candidate location points.

2. The method according to claim 1, wherein, The acquisition of satellite prediction data for the candidate positioning points includes: Obtain the current satellite ephemeris information; Sky occlusion information is generated based on the location of the candidate location point and the three-dimensional building data around the location; Based on the sky obscuration information and the satellite ephemeris information, the satellites are marked as visible satellites and / or invisible satellites; Based on the satellite ephemeris information and the positions of the candidate positioning points, the predicted pseudorange of the visible satellite and / or the predicted pseudorange of the invisible satellite are calculated.

3. The method according to claim 2, wherein, The process of obtaining a score for the candidate location point using satellite prediction data and satellite observation data includes: Based on the satellite positioning data received by the terminal, the satellite observation pseudorange is obtained; Based on the predicted pseudorange of the visible satellite and / or the predicted pseudorange of the invisible satellite, and the observed pseudorange of the satellite, the pseudorange residuals of the visible satellite and / or the invisible satellite are obtained. The candidate positioning points are scored based on a first proportion of visible satellites with pseudorange residuals of 0 and / or a second proportion of invisible satellites with pseudorange residuals greater than 0, wherein the first proportion is the ratio of the number of visible satellites with pseudorange residuals of 0 to the total number of visible satellites; and the second proportion is the ratio of the number of invisible satellites with pseudorange residuals greater than 0 to the total number of invisible satellites.

4. The method according to claim 1, wherein, The acquisition of satellite prediction data for the candidate positioning points includes: Based on satellite ephemeris information and the positions of the candidate positioning points, the predicted pseudorange of the satellite is calculated.

5. The method according to claim 4, wherein, The process of obtaining a score for the candidate location point using satellite prediction data and satellite observation data includes: Based on the satellite positioning data received by the terminal, the satellite observation pseudorange is obtained; Based on the predicted pseudorange of the satellite and the observed pseudorange of the satellite, the actual pseudorange residual of the satellite is obtained; Based on the location of the candidate positioning point and the satellite ephemeris information, the true pseudorange residual of the satellite is obtained through a pre-established pseudorange residual fingerprint database. For each satellite, the matching degree of the satellite is obtained based on the actual pseudorange residual and the true pseudorange residual; The matching scores of all satellites are fused, and a score for the candidate location point is obtained based on the fused matching scores.

6. The method according to claim 5, wherein, The pseudorange residual fingerprint database records Gaussian models. A Gaussian model is used to characterize the true pseudorange residual of satellites in a geographic area at a combination of angles, including azimuth and elevation. The process of obtaining the true pseudorange residual of the satellite based on the position of the candidate positioning point and the satellite ephemeris information, through a pre-established pseudorange residual fingerprint database, includes: Based on the satellite's three-dimensional coordinates and the candidate positioning points in the satellite ephemeris information, calculate the satellite's elevation angle and azimuth angle; Based on the position of the candidate positioning point, the elevation angle and azimuth angle of the satellite, the true pseudorange residual of the satellite is obtained from the Gaussian model.

7. The method according to claim 1, wherein, Obtaining satellite prediction data for the candidate positioning points includes: Obtain the current satellite ephemeris information; Sky occlusion information is generated based on the location of the candidate location point and the three-dimensional building data around the location; Based on the sky obstruction information and the satellite ephemeris information, the predicted visibility of the satellite is obtained.

8. The method according to claim 7, wherein, The process of obtaining a score for the candidate location point using satellite prediction data and satellite observation data specifically includes: Based on the satellite positioning data received by the terminal, the observation visibility of the satellite is obtained; The candidate location points are scored based on the predicted and observed visibility of the satellite.

9. The method according to claim 2, 3, 7 or 8, wherein, The method further includes: Based on pre-made 3D map data, the 3D map coverage of a predetermined area matching the candidate positioning point is obtained, wherein the predetermined area is an area whose distance from the candidate positioning point is less than a predetermined value. In response to the fact that the 3D map coverage of the predetermined area is greater than a predetermined threshold, 3D building data around the location of the candidate positioning point are obtained.

10. The method according to claim 5 or 6, wherein, The method further includes: Based on the satellite positioning data measured in the target geographic area, the true pseudorange residuals corresponding to m angle combinations in the target geographic area are obtained. The angle combinations include azimuth and elevation angles, and m is equal to the number of azimuth angles multiplied by the number of elevation angles. Based on the true pseudorange residuals corresponding to m angle combinations of the target geographic region, m Gaussian models are generated. Each Gaussian model is used to characterize the true pseudorange residual of an angle combination of the target geographic region.

11. A method for generating fingerprint data, wherein, include: Based on the satellite positioning data measured in the target geographic area, the true pseudorange residuals corresponding to m angle combinations in the target geographic area are obtained. The angle combinations include azimuth and elevation angles, and m is equal to the number of azimuth angles multiplied by the number of elevation angles. Based on the true pseudorange residuals corresponding to m angle combinations of the target geographic region, m Gaussian models are generated. Each Gaussian model is used to characterize the true pseudorange residual of an angle combination of the target geographic region.

12. An electronic device, wherein, include: Processor, and memory; The memory stores computer instructions that can be executed by the processor; The computer instructions are executed by the processor to cause the electronic device to perform the method of any one of claims 1-11.

13. A computer-readable storage medium, wherein, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-11.

14. A computer program product, wherein, Includes computer instructions that, when executed by a processor, implement the method as described in any one of claims 1-11.

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