CN116068604A

CN116068604A - Fusion positioning method, fusion positioning device, computer equipment, storage medium and program product

Info

Publication number: CN116068604A
Application number: CN202310141940.1A
Authority: CN
Inventors: 程宇航
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2023-02-13
Filing date: 2023-02-13
Publication date: 2023-05-05

Abstract

The application discloses a fusion positioning method, a fusion positioning device, computer equipment, a storage medium and a program product, and relates to the field of maps. The method comprises the following steps: determining satellite distribution characteristics of each satellite observed under the position of the positioning equipment; determining a positioning accuracy value of a satellite positioning result based on satellite distribution characteristics, wherein the satellite positioning result is determined based on observed satellite signals of all satellites; determining satellite positioning weight of a satellite positioning result in a fusion positioning process based on the positioning precision value, wherein the satellite positioning weight and the positioning precision value are in a negative correlation; and determining a fusion positioning result of the positioning equipment based on the satellite positioning weight and the satellite positioning result. The method can enable the satellite positioning weight in the fusion positioning process to be consistent with the actual positioning error of the satellite positioning result, thereby improving the accuracy of the fusion positioning result.

Description

Fusion positioning method, fusion positioning device, computer equipment, storage medium and program product

Technical Field

The present disclosure relates to the field of maps, and in particular, to a fusion positioning method, apparatus, computer device, storage medium, and program product.

Background

A global satellite navigation system (the Global Navigation Satellite System, GNSS), also known as a global navigation satellite system, is an air-based radio navigation positioning system that can provide all-weather three-dimensional coordinates and velocity and time information to a user at any location on the earth's surface or near earth space.

In the positioning process by using the GNSS, in order to improve the positioning accuracy, the observation data of multiple directions such as the GNSS, an inertial navigation system (Inertial Navigation System, INS) and a visual camera are fused, and the fusion positioning is performed based on an optimization algorithm such as filtering, and in the fusion positioning process, if the GNSS positioning result has deviation, the accuracy of the fusion positioning result is affected.

Obviously, how to estimate the accuracy of the GNSS positioning results is a key to improve the accuracy of the fusion positioning results.

Disclosure of Invention

The embodiment of the application provides a fusion positioning method, a fusion positioning device, computer equipment, a storage medium and a program product. The technical scheme is as follows:

in one aspect, an embodiment of the present application provides a fusion positioning method, where the method includes:

determining satellite distribution characteristics of each satellite observed under the position of the positioning equipment;

Determining a positioning accuracy value of a satellite positioning result based on the satellite distribution characteristics, wherein the satellite positioning result is determined based on the observed satellite signals of each satellite;

determining satellite positioning weight of the satellite positioning result in the fusion positioning process based on the positioning precision value, wherein the satellite positioning weight and the positioning precision value are in a negative correlation;

and determining a fusion positioning result of the positioning equipment based on the satellite positioning weight and the satellite positioning result.

In another aspect, embodiments of the present application provide a fusion positioning device, the device including:

the determining module is used for determining satellite distribution characteristics of all satellites observed under the position of the positioning equipment;

the determining module is further configured to determine a positioning accuracy value of a satellite positioning result based on the satellite distribution characteristics, where the satellite positioning result is determined based on the observed satellite signals of the satellites;

the determining module is further configured to determine a satellite positioning weight of the satellite positioning result in the fusion positioning process based on the positioning precision value, where the satellite positioning weight and the positioning precision value have a negative correlation;

And the fusion positioning module is used for determining a fusion positioning result of the positioning equipment based on the satellite positioning weight and the satellite positioning result.

In another aspect, embodiments of the present application provide a computer device, where the computer device includes a processor and a memory, where the memory stores at least one section of program, and the at least one section of program is loaded and executed by the processor to implement the fusion positioning method according to the above aspect.

In another aspect, the present application provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the fusion positioning method provided in the above aspect.

In the embodiment of the application, satellite distribution characteristics of all satellites observed at the position of the positioning equipment are analyzed, and the positioning precision value of the satellite positioning result is determined based on the satellite distribution characteristics, so that the satellite positioning weight of the satellite positioning result in the fusion positioning process is determined based on the positioning precision value, and the credibility of the satellite positioning result in the fusion positioning process is quantized; the satellite positioning weight determination process is related to satellite distribution characteristics of satellites participating in satellite positioning result calculation, and the satellite distribution characteristics influence the accuracy of the satellite positioning result, so that the satellite positioning weight in the fusion positioning process is consistent with the actual positioning error of the satellite positioning result, and the accuracy of the fusion positioning result is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 illustrates a schematic diagram of an implementation environment provided by an exemplary embodiment of the present application;

FIG. 2 illustrates a flow chart of a fusion positioning method provided by an exemplary embodiment of the present application;

FIG. 3 illustrates a process diagram of fusion positioning provided in an exemplary embodiment of the present application;

FIG. 4 illustrates a flow chart of a fusion positioning method provided in another exemplary embodiment of the present application;

FIG. 5 illustrates a satellite view schematic diagram illustrating one exemplary embodiment of the present application;

FIG. 6 illustrates a process diagram of fusion positioning provided in accordance with another exemplary embodiment of the present application;

FIG. 7 illustrates a training method of a positioning accuracy estimation model shown in an exemplary embodiment of the present application;

FIG. 8 illustrates a flow chart of a fusion positioning method provided in another exemplary embodiment of the present application;

FIG. 9 illustrates a block diagram of a fusion positioning device provided in an exemplary embodiment of the present application;

fig. 10 shows a schematic structural diagram of a computer device according to an exemplary embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

First, the terms involved in the embodiments of the present application will be briefly described:

(1) Global satellite navigation system (the Global Navigation Satellite System, GNSS): also known as global navigation satellite systems, are space-based radio navigation positioning systems that provide users with all-weather three-dimensional coordinates and velocity and time information at any location on the earth's surface or near-earth space. Common systems are the four major satellite navigation systems GPS (Global Positioning System ), BDS (Beidou navigation Satellite, beidou navigation satellite), GLONASS and GALILEO. Satellite navigation systems have been widely used in navigation, communications, personnel positioning, consumer entertainment, mapping, vehicle management, and car navigation and information services, and the general trend is to provide high-precision services for real-time applications.

(2) Positioning equipment: electronic device for processing satellite signals and measuring the geometrical distance between the device and the satellite (pseudo-range observations) and the doppler effect of the satellite signals (doppler observations); the positioning device typically includes an antenna, a satellite signal loop, baseband signal processing, and the like. The positioning device is widely applied to the fields of map navigation, mapping, position service and the like, such as smart phone map navigation, high-precision geodetic survey, civil aviation and the like.

(3) Fusion positioning: one common fusion scheme is to fuse the observation data of GNSS/INS (inertial navigation system )/vision camera, and perform fusion positioning by adopting a filtering-based or optimization method. The GNSS positioning measurement noise covariance matrix is mainly assigned by a positioning solution standard deviation output by a GNSS positioning algorithm. The consistency between the measurement noise covariance matrix of the GNSS positioning and the actual precision of the GNSS positioning is one of important factors influencing the positioning accuracy of the fusion positioning algorithm.

Because the standard deviation of the GNSS positioning solution has poor consistency with the actual positioning error, two conditions which do not meet the expectations exist, namely, the actual positioning error of the GNSS meets the requirements, but the standard deviation of the GNSS positioning solution is larger than a threshold value, so that available GNSS positioning points are reduced; and secondly, the GNSS actual positioning error is larger than a threshold value, and the standard deviation of the GNSS positioning solution meets the requirement, so that the fusion positioning uses an incorrect GNSS positioning result. Both of these cases may result in a deterioration in positioning accuracy of the lane-level fusion positioning method.

In order to improve the positioning accuracy of a fusion positioning algorithm, the embodiment of the application provides a method for determining weights for GNSS based on satellite distribution characteristics. Referring to fig. 1, a schematic diagram of an implementation environment provided in an exemplary embodiment of the present application is shown, where the implementation environment includes: satellite device 110 and positioning device 120.

The satellite device 110 is a device having a satellite signal transmission function. The satellite device 110 in this embodiment is mainly an artificial satellite with navigation function. The common satellite positioning systems mainly comprise GPS, BDS, GLONASS and GALILEO four-large satellite navigation systems. The satellite positioning model is transmitted by the satellite device 110 such that the positioning device 120 determines its own spatial position based on the satellite positioning signals.

The positioning device 120 is an electronic device with a positioning function, and a global satellite navigation system positioning chip can be integrated in the positioning device 120 for processing satellite signals and performing accurate positioning. Optionally, the positioning device 120 typically includes functional components such as an antenna, satellite signal loop, baseband signal processing, and the like. The positioning device 120 may be a tablet computer, a portable notebook, a vehicle-mounted terminal, a smart phone, a POS device, or a desktop computer, which is not limited in this embodiment.

Optionally, in this embodiment, by analyzing satellite distribution characteristics of each satellite observed by a location where the positioning device is located, and determining a positioning accuracy value of a satellite positioning result based on the satellite distribution characteristics, a satellite positioning weight of the satellite positioning result in a fusion positioning process is determined based on the positioning accuracy value, so as to quantify the credibility of the satellite positioning result in the fusion positioning process; the satellite positioning weight determination process is related to satellite distribution characteristics of satellites participating in satellite positioning result calculation, and the satellite distribution characteristics influence the accuracy of the satellite positioning result, so that the satellite positioning weight in the fusion positioning process is consistent with the actual positioning error of the satellite positioning result, and the accuracy of the fusion positioning result is improved.

It should be noted that, before and during the process of collecting the relevant data of the user, the present application may display a prompt interface, a popup window or output a voice prompt message, where the prompt interface, popup window or voice prompt message is used to prompt the user to collect the relevant data currently, so that the present application only starts to execute the relevant step of obtaining the relevant data of the user after obtaining the confirmation operation of the user to the prompt interface or popup window, otherwise (i.e. when the confirmation operation of the user to the prompt interface or popup window is not obtained), the relevant step of obtaining the relevant data of the user is finished, i.e. the relevant data of the user is not obtained. In other words, all user data collected in the present application is collected with the consent and authorization of the user, and the collection, use and processing of relevant user data requires compliance with relevant laws and regulations and standards of the relevant country and region.

Referring to fig. 2, a flowchart of a fused positioning method according to an exemplary embodiment of the present application is shown, where the embodiment of the present application uses the positioning device 120 in the foregoing embodiment as an example, and the method includes:

in step 201, satellite distribution characteristics of each satellite observed under the location of the positioning device are determined.

In the GNSS positioning process, the positioning equipment calculates the current position coordinates of the positioning equipment by processing satellite signals; because the position of the positioning equipment changes at any time, and the satellite positions (satellite distribution), satellite signals (possibly blocked by obstacles) and the like observed by different positions are different, the positioning accuracy of GNSS positioning is affected; in order to make the positioning device clear about the GNSS positioning at the current location, in a possible implementation manner, in the process of fusion positioning, the positioning device obtains satellite distribution characteristics of each satellite observed at the location of the positioning device, and analyzes the satellite distribution characteristics to quantify the satellite signal quality involved in the calculation of the satellite positioning result, so as to estimate the positioning accuracy of the satellite positioning result.

Optionally, the satellite distribution feature may include feature values of multiple dimensions of the satellite, for example, a satellite altitude dimension, a satellite azimuth dimension, a satellite signal dimension, a satellite number dimension, a satellite precision attenuation factor dimension, and the like, where specific feature values included in the satellite distribution feature in the embodiment of the present application are not limited.

Step 202, determining a positioning accuracy value of a satellite positioning result based on the satellite distribution characteristics, wherein the satellite positioning result is determined based on the observed satellite signals of each satellite.

Optionally, after the positioning device obtains the satellite distribution characteristics of the currently observed satellite, a preset analysis algorithm may be used to analyze the satellite distribution characteristics to determine the quality of satellite signals corresponding to each observed satellite that participates in the calculation of the satellite positioning result, and the positioning accuracy value is used to quantify the positioning quality of the satellite positioning result.

The positioning accuracy value is used for representing the error between the satellite positioning result and the position of the real equipment where the positioning equipment is located, if the positioning accuracy value is smaller, the error between the satellite positioning result and the position of the real equipment is smaller, the satellite positioning result is more accurate (the reliability is higher), and correspondingly, higher satellite positioning weight can be set for the satellite positioning result; on the contrary, if the positioning accuracy value is larger, the error between the satellite positioning result and the real equipment is larger, the satellite positioning result is more inaccurate (the reliability is lower), and correspondingly, lower satellite positioning weight can be set for the satellite positioning result. It can be seen that the satellite positioning weight and the positioning accuracy value have a negative correlation.

Schematically, if the positioning accuracy value of the satellite positioning result a is 3m, and the positioning accuracy value of the satellite positioning result B is 10m, the satellite positioning result a is more accurate than the satellite positioning result B, and the satellite positioning weight of the satellite positioning result a is greater than the satellite positioning weight of the satellite positioning result B.

Optionally, if the positioning accuracy is used to determine the satellite positioning weight, the higher the positioning accuracy is, the smaller the positioning accuracy value is, the smaller the error between the satellite positioning result and the real equipment is, the more accurate the satellite positioning result is, and the higher the satellite positioning weight is correspondingly set for the satellite positioning result; on the contrary, if the positioning accuracy is lower, the positioning accuracy value is larger, the error between the satellite positioning result and the real equipment is larger, the satellite positioning result is inaccurate, and the satellite positioning weight is set for the satellite positioning result correspondingly. It can be seen that the satellite positioning weight and the satellite accuracy are in positive correlation.

Optionally, at least 4 non-coplanar satellites are required to determine the spatial location of the positioning device when determining satellite positioning results. Before determining the positioning accuracy value of the satellite positioning result based on the satellite distribution characteristics, firstly determining whether the condition for determining the satellite positioning result is met according to the acquired satellite positioning information, and if so, continuing to execute the subsequent steps of determining the positioning accuracy value and the like.

Alternatively, when determining satellite positioning results based on observed satellite signals of respective satellites, the positioning algorithm employed may include: pseudo-range measurements (measuring the propagation time of a ranging code signal transmitted by a satellite to reach a user receiver) and carrier phase measurements (measuring the phase difference between a satellite carrier signal with carrier doppler shift and a reference carrier signal generated by the receiver).

Step 203, determining satellite positioning weight of the satellite positioning result in the fusion positioning process based on the positioning precision value, wherein the satellite positioning weight and the positioning precision value are in a negative correlation.

In the fusion positioning process, the positioning device needs to fuse a GNSS positioning result (satellite positioning result) with other positioning results (such as an inertial navigation positioning result or a visual camera positioning result) so as to jointly determine the spatial position of the positioning device, and in the fusion process, the error between the satellite positioning result and the actual positioning result needs to be considered so as to determine the reliability of the satellite positioning result in the fusion process; in order to make the reliability of the satellite positioning result clear in the positioning fusion process, in a possible implementation manner, the positioning device may set a satellite positioning weight for the satellite positioning result in the fusion positioning process based on the positioning accuracy value of the satellite positioning result, where the greater the positioning accuracy value is, the greater the error of the satellite positioning result is, the lower the reliability of the satellite positioning result is, and the lower satellite positioning weight is correspondingly required to be set for the satellite positioning result; if the positioning accuracy value is smaller, the satellite positioning result error is smaller, the reliability of the satellite positioning result is higher, and correspondingly, higher satellite positioning weight needs to be set for the satellite positioning result, namely, the satellite positioning weight and the positioning accuracy value are in negative correlation.

Optionally, an operational relationship between the satellite positioning weight and the positioning accuracy value may be preset in the positioning device, so that the satellite positioning weight and the positioning accuracy value satisfy a negative correlation relationship; or, different satellite positioning weights can be set for positioning precision values in different ranges in the positioning equipment in advance, so that corresponding satellite positioning weights can be matched based on the range of the positioning precision values in the application process. Illustratively, if the positioning accuracy value of the satellite positioning result is 3m, the satellite positioning weight of the satellite positioning result may be set to 1, and if the positioning accuracy value of the satellite positioning result is 5m, the satellite positioning weight of the satellite positioning result may be set to 0.5.

Step 204, determining a fusion positioning result of the positioning device based on the satellite positioning weight and the satellite positioning result.

Optionally, after the positioning device determines the satellite positioning weight of the satellite positioning result, the reliability of the satellite positioning result in the fusion positioning process is determined, and the satellite positioning weight and the satellite positioning result can be input into a fusion positioning algorithm (the fusion positioning algorithm can be a filtering algorithm) together correspondingly, so as to obtain a fusion positioning result of the positioning device output by the fusion positioning algorithm.

As shown in fig. 3, a schematic diagram of a process of fusion positioning according to an exemplary embodiment of the present application is shown. In the process of fusion positioning, firstly, a positioning precision value 302 of a satellite positioning result 304 is estimated according to satellite distribution characteristics 301, and a satellite positioning weight 303 of the satellite positioning result 304 in the process of fusion positioning is determined based on the positioning precision value 302; further, the satellite positioning result 304, the satellite positioning weight 303, and other positioning results (inertial navigation positioning result and/or visual camera positioning result 305) are input together into the fusion positioning algorithm 306, and a fusion positioning result 307 output by the fusion positioning algorithm 306 can be obtained.

In summary, in this embodiment, by analyzing satellite distribution characteristics of each satellite observed by the location where the positioning device is located, and determining a positioning accuracy value of the satellite positioning result based on the satellite distribution characteristics, the satellite positioning weight of the satellite positioning result in the fusion positioning process is determined based on the positioning accuracy value, so as to quantify the credibility of the satellite positioning result in the fusion positioning process; the satellite positioning weight determination process is related to satellite distribution characteristics of satellites participating in satellite positioning result calculation, and the satellite distribution characteristics influence the accuracy of the satellite positioning result, so that the satellite positioning weight in the fusion positioning process is consistent with the actual positioning error of the satellite positioning result, and the accuracy of the fusion positioning result is improved.

In order to improve the accuracy of determining satellite distribution characteristics, satellites are projected into a satellite view (Skyplot) according to satellite altitude angles and satellite azimuth angles, and sub-distribution characteristics in each grid position are determined so as to comprehensively obtain satellite distribution characteristics of all satellites observed in the position.

Referring to fig. 4, a flowchart of a fused positioning method according to another exemplary embodiment of the present application is shown, where the embodiment of the present application uses the positioning device 120 in the foregoing embodiment as an example, and the method includes:

in step 401, satellite positioning information of each satellite observed by the positioning device is acquired.

Optionally, the satellite positioning information includes at least one of satellite number, satellite altitude, satellite azimuth, satellite signal-to-noise ratio, and satellite accuracy attenuation factor. Wherein the satellite dilution of precision (Dilution Of Precision, DOP) is an indicator of the quality of the position. In navigator, the concept of DOP is generally used to represent the magnification of the error, and the receiver of the positioning device will also generally output the precision factor along with the positioning result for reference by the user. Small DOP values represent a high probability of strong satellite geometry and accuracy. A high DOP value represents a lower probability of weak satellite geometry and accuracy. Alternatively, the general calculation types of DOP values may include: HDOP, VDOP, PDOP, etc.

Alternatively, after the receiver of the positioning device receives the satellite signals of the observed satellites, satellite positioning information related to the satellites may be output, so that the satellite distribution characteristics may be determined subsequently based on the satellite positioning information.

Optionally, the positioning device may receive satellite signals of multiple satellite systems, including satellite systems such as GPS, BDS, GLONASS, GALILEO, QZSS, and the number of visible satellites in the open environment may be up to 30 or more.

Step 402, determining satellite distribution characteristics of each satellite observed under the position of the positioning device based on the satellite positioning information.

In view of the influence of satellite distribution on satellite positioning accuracy, in order to be able to analyze the satellite distribution characteristics of the satellites currently observed by the positioning device, each of the satellites observed may be projected into a satellite view (Skyplot) according to the satellite altitude and the satellite azimuth, so that the corresponding satellite distribution characteristics may be subsequently analyzed based on the satellite view. In an illustrative example, step 402 may include steps 402A-402C.

Step 402A, determining grid positions of each satellite in the satellite view based on the satellite altitude and the satellite azimuth, wherein the number of grids in the satellite view containing the grid positions is determined by the satellite altitude range and the satellite azimuth range.

The satellite view is obtained by dividing the satellite altitude range and the satellite azimuth range. Since the satellite altitude range is 0-90 degrees and the satellite altitude range is 0-360 degrees, 4*6 =24 grid positions can be divided on the satellite view (Skyplot) according to the satellite altitude range and the satellite azimuth range.

Considering the influence of satellite distribution on satellite positioning accuracy, before extracting satellite distribution characteristics, the positioning device firstly determines grid positions of each satellite in a satellite view according to the observed satellite altitude and satellite azimuth of each satellite, namely, the satellite can be projected in the uniquely determined grid positions in the satellite view according to the satellite altitude and satellite azimuth of the satellite.

As shown in fig. 5, which illustrates a satellite view schematic diagram as shown in one exemplary embodiment of the present application. The satellite view 501 is divided into 24 grid locations 502, where the satellite altitude angle range is divided into 4 ranges: the satellite azimuth angle range is divided into 6 ranges by 0-15 degrees, 15-45 degrees, 45-60 degrees and 60-90 degrees: 0-60 degrees, 60-120 degrees, 120-180 degrees, 180-240 degrees, 240-300 degrees, 300-360 degrees, each range being 60 degrees, thereby obtaining 24 grid positions. If the satellite altitude of the satellite a is 15 degrees and the satellite azimuth is 60 degrees, the position of the satellite a in the satellite view may be as shown by the projection point a. If the satellite altitude of satellite B is 30 degrees. The satellite azimuth is 120 degrees, then the position of satellite B on the satellite view may be as shown by projection point B.

Alternatively, the present embodiment only takes the division of the satellite view into 24 grid positions as an example for illustration, and if the satellite view is to obtain finer satellite distribution characteristics, the satellite view may be divided into more grid positions, for example, 4*8 =32 grid positions, 5*6 =30 grid positions, or the like, and the present embodiment is not limited to specific grid positions. And the more grid positions, the more satellite distribution features are obtained.

Step 402B, determining a first sub-distribution characteristic of the grid location corresponding to the satellite based on satellite positioning information of the satellite included in the grid location.

In one possible implementation manner, after each satellite observed by the positioning device is projected to the satellite view according to the satellite altitude angle and the satellite azimuth angle, the satellite contained in each grid position can be determined, and further, according to satellite positioning information of the satellite contained in each grid position, a first sub-distribution feature of each grid position corresponding to the satellite is determined, and further, a feature value set of each grid position corresponding to the first sub-distribution feature is determined as the satellite distribution feature of each satellite observed by the positioning device.

Alternatively, by dividing the grid positions, the distribution position of each observed satellite may be defined according to the first sub-distribution characteristic of each grid position.

Optionally, because the first sub-distribution features corresponding to each grid position respectively need to be calculated, the number of the feature values contained in the satellite distribution features is determined by the number of grids of the grid positions and the feature value dimension contained in the satellite distribution feature values; illustratively, if the number of grids is 24, and the feature value dimension (the feature value dimension refers to the feature value category to be calculated) is 5, the satellite distribution feature includes 5×24=120 feature values.

Since positioning devices can observe satellites of different satellite systems, common satellite systems are roughly divided into: GPS, BDS, GLONASS, QZSS, etc. In order to further enrich the number of eigenvalues of the satellite eigenvalues, for each grid position, the distribution characteristics of different satellite systems in each grid position may also be calculated separately. In an illustrative example, step 402B may also include steps 402B 1-402B 3.

Step 402B1, dividing the satellites contained in the grid location into different satellite systems based on the satellite positioning information of the satellites contained in the grid location.

Step 402B2, determining a second sub-distribution characteristic of the satellite system in the grid location based on satellite positioning information of satellites of the same satellite system in the grid location.

Step 402B3, determining a set of second sub-distribution features corresponding to each satellite system in the grid position as a first sub-distribution feature corresponding to the satellite in the grid position, wherein the number of feature values of the satellite distribution features is determined by the number of grids and the number of system categories of the satellite systems.

When the first sub-distribution feature of the grid position is calculated, the satellites contained in the grid position can be divided according to different satellite systems based on satellite positioning information of the satellites contained in the grid position, so that different satellite sets are obtained, and the satellites in the same satellite set are the same satellite system in the same grid position.

Optionally, after different satellite systems are partitioned, for each grid position, based on satellite positioning information of satellites of the same satellite system in the grid position, a second sub-distribution feature of the same satellite system in the grid position can be calculated, and then a set of second sub-distribution features corresponding to each satellite system is determined as a first sub-distribution feature of a satellite corresponding to the grid position.

Optionally, since the distribution feature of each grid position corresponding to the satellite is further divided into different satellite systems for calculation, the number of feature values contained in the satellite distribution feature is determined by the grid position, the number of system categories of the satellite systems and the feature value dimension. Illustratively, if the grid position is 24, there are four satellite systems, and the eigenvalue dimension is 5, the number of eigenvalues included in the satellite distribution feature is 4×24×5=480.

Optionally, if in order to save the calculation amount in the satellite positioning process, it is unnecessary to divide different satellite systems for each grid position, so that the number of feature values of the satellite distribution features can be correspondingly reduced; if higher positioning accuracy (smaller positioning accuracy value) is required, the grid position may be further divided according to the satellite system, so as to increase the number of feature values contained in the satellite distribution feature.

Optionally, taking the second sub-distribution feature calculation process of the corresponding satellite of the same satellite system in the same grid position as an example, the positioning device may determine at least one of the number of satellites of the satellite system in the grid position, an average satellite altitude angle, an average signal-to-noise ratio, a target Wei Xingzhan ratio, and a satellite azimuth standard deviation based on satellite positioning information of the satellite of the same satellite system in the grid position, where the target Wei Xingzhan ratio refers to a ratio of the satellites whose signal-to-noise ratio is greater than a signal-to-noise ratio threshold. That is, the feature value dimensions included in the satellite distribution feature include 5 dimensions: satellite number, average satellite altitude, average signal to noise ratio, target Wei Xingzhan ratio, satellite azimuth standard deviation, etc.

If the grid location is not further divided into different satellite systems, then in the first sub-distribution feature: the number of satellites is the number of satellites contained in the grid position, the average satellite altitude is the average value of the satellite altitudes of the satellites contained in the grid position, the average signal-to-noise ratio is the average value of the satellite signal-to-noise ratios of the satellites contained in the grid position, the standard deviation of satellite azimuth angles is the standard deviation of the satellite azimuth angles of the satellites contained in the grid position, and the target Wei Xingzhan ratio is the duty ratio of the satellites with the satellite signal-to-noise ratios greater than the signal-to-noise ratio threshold value in the grid position. The signal to noise ratio threshold may be 30.

If the grid location is further divided into different satellite systems, for example, 4 satellite systems, the first sub-distribution feature includes 4 sets of second sub-distribution features, and the second sub-distribution features of the first satellite system: the number of satellites is the number of satellites contained in the first satellite system in the grid position, the average satellite altitude is the average value of the satellite altitude of the satellites contained in the first satellite system in the grid position, the average signal-to-noise ratio is the average value of the satellite signal-to-noise ratios of the satellites contained in the first satellite system in the grid position, the standard deviation of satellite azimuth angles is the standard deviation of satellite azimuth angles of the satellites contained in the first satellite system in the grid position, and the target Wei Xingzhan ratio is the duty ratio of the satellites with the satellite signal-to-noise ratio of the first satellite system greater than the signal-to-noise ratio threshold value in the grid position.

In step 402C, a set of first sub-distribution features corresponding to each grid position is determined as a satellite distribution feature, and a number of feature values of the satellite distribution feature is determined by the number of grids.

Optionally, after determining the first sub-distribution feature corresponding to each grid position, the set of first sub-distribution features corresponding to each grid position is the satellite distribution feature of each satellite observed by the positioning device.

Optionally, three values such as HDOP, VDOP, PDOP factors may be included in the satellite distribution characteristics. Illustratively, if the classification calculation is performed according to satellite systems, there are 4 satellite systems, the number of grids is 24, and the feature value dimension is 5, the satellite distribution feature includes 480+3=483 feature values.

And step 403, inputting the satellite distribution characteristics into a positioning precision estimation model to obtain a positioning precision value output by the positioning precision estimation model.

Optionally, a positioning precision estimation model is further deployed in the positioning device, and the positioning precision estimation model is obtained by training based on the sample satellite distribution characteristics and the sample labeling positioning precision value, so that the positioning precision estimation model can output the positioning precision value of the satellite positioning result reflected by the positioning precision estimation model based on the satellite distribution characteristics. In a possible implementation manner, after the positioning device extracts the satellite distribution characteristics of the satellite observed under the current position, the satellite distribution characteristics can be input into the positioning precision estimation model, and the positioning precision estimation model performs positioning precision value analysis to obtain the positioning precision value output by the positioning precision estimation model.

Optionally, the positioning accuracy estimation model may be a gradient lifting tree model (XGBoost) or another neural network model, and the specific structure of the positioning accuracy estimation model is not limited in this embodiment, and the specific model training process may refer to the following embodiments, which are not described herein.

Step 404, determining a weight coefficient of the satellite positioning result under the positioning precision value, wherein the weight coefficient and the positioning precision value are in a negative correlation.

Optionally, the satellite positioning weight is determined by a positioning precision value and a weight coefficient, the weight coefficient is determined by the positioning precision value, and the weight coefficient and the positioning precision value have a negative correlation relationship, that is, the larger the positioning precision value is, the smaller the weight coefficient is, the smaller the positioning precision value is, and the larger the weight coefficient is.

Optionally, a plurality of positioning precision ranges are partitioned based on availability of the satellite positioning result and application scenes of the satellite positioning result, and different weight coefficients are set for each positioning precision range. So that the weight coefficient of the satellite positioning result under the positioning precision value can be determined based on the relation between the positioning precision value and the positioning precision range. In an illustrative example, step 404 may also include step 404A and step 404B.

Step 404A, determining a positioning precision range in which the positioning precision value is located, wherein different positioning precision ranges correspond to different weight coefficients.

And 404B, determining the weight coefficient corresponding to the positioning precision range as the weight coefficient of the satellite positioning result under the positioning precision value.

Wherein, a plurality of positioning precision ranges are preset in the positioning equipment, and different positioning precision ranges correspond to different weight coefficients. When the weight coefficient is determined, the positioning equipment determines the positioning precision range in which the positioning precision value is positioned, and further determines the weight coefficient of the satellite positioning result under the current positioning precision value according to the weight coefficient corresponding to the positioning precision range.

In one illustrative example, the relationship between the positioning accuracy range and the weight coefficient may be as shown in table one.

List one

Positioning accuracy range	Weight coefficient
		0～3m	1
3～10m	0.5
		>10m	0.01

As can be seen from the first table, when the positioning accuracy value is greater than 10m, the weight of the satellite positioning result is reduced to the minimum (10 represents the available threshold of the satellite positioning result, that is, when the positioning accuracy value of the satellite positioning result is greater than 10m, the satellite positioning result is not available), and the weight coefficient corresponding to the positioning accuracy range is correspondingly set to be 0.01; when the positioning accuracy range is 3-10 m, the weight of the satellite positioning result is reduced (3 m can represent the accuracy requirement of the lane-level positioning scene on GNSS positioning, namely when the positioning accuracy value of the satellite positioning result is more than 3m, the satellite positioning result is not available in the lane-level positioning scene), and the weight coefficient corresponding to the positioning accuracy range is correspondingly set to be 0.5; when the positioning accuracy range is 0-3 m, the weight of the satellite positioning result is increased (3 m represents the accuracy requirement of the lane-level positioning scene on the satellite positioning result, and the lane-level positioning is considered to be available when the positioning accuracy value of the satellite positioning result is smaller than 3 m), and the weight coefficient corresponding to the accuracy range is correspondingly set to be 1.

Optionally, because the positioning accuracy value requirements on the satellite positioning result are different in different positioning application scenarios, for example, the positioning accuracy value requirements on the satellite positioning result in the lane-level positioning scenario is 0-3 m, in order to enable the fusion positioning method to be used in different positioning application scenarios, in other possible embodiments, the positioning device can dynamically adjust the positioning accuracy range according to the positioning application scenario of the fusion positioning result; in the fusion positioning process, the corresponding positioning equipment can acquire a positioning application scene of the fusion positioning result, and further divide different precision ranges based on the positioning precision requirement of the positioning application scene on the fusion positioning result, so that the weight coefficient corresponding to the satellite positioning result in the current positioning application scene can be dynamically determined according to the difference of the precision ranges.

Optionally, the relationship between the multiple positioning application scenes and the precision range may be preset in the positioning device, so that corresponding weight coefficients are adapted under different positioning application scenes. As shown in table two, it shows the relationship between the positioning application scenario and the accuracy range.

Watch II

Locating application scenarios	Precision range
		Scene 1	0～3m、3～10m、>10m
Scene 2	0～0.1m、0.1～10m、>10m
		Scene 3	0～1m、1～10m、>10m
…	…

As shown in the table two, if the current positioning application scene is scene 2, when the positioning accuracy value of the satellite positioning result is 0.05m, the corresponding weight coefficient is 1; if the positioning accuracy value of the satellite positioning result is 1m, the corresponding weight coefficient is 0.5; if the positioning accuracy value of the satellite positioning result is 20m, the corresponding weight coefficient is 0.01.

Step 405, determining satellite positioning weights of the satellite positioning results in the fusion positioning process based on the weight coefficient and the positioning accuracy value.

In one illustrative example, the satellite positioning weight calculation process may be as shown in equation (1).

Wherein p represents satellite positioning weight, std_prediction represents positioning accuracy value, and k represents weight coefficient. It can be seen that the satellite positioning weight and the positioning accuracy value have a negative correlation, and the satellite positioning weight and the weight coefficient have a positive correlation.

Step 406, determining a fusion positioning result of the positioning device based on the satellite positioning weight and the satellite positioning result.

As shown in fig. 6, a schematic diagram of a process of fusion positioning according to another exemplary embodiment of the present application is shown. Based on satellite positioning information 601 such as satellite number, signal-to-noise ratio, altitude angle, azimuth angle and DOP factor, satellite distribution characteristics 602 such as satellite number, average signal-to-noise ratio, average satellite altitude angle, satellite azimuth standard deviation and Wei Xingzhan ratio with signal-to-noise ratio larger than 60 are extracted, and the satellite distribution characteristics 602 are input into a positioning precision estimation model 603 to perform positioning precision value estimation, so that a positioning precision value 604 output by the model is obtained; further, a weight coefficient 605 is determined based on the positioning accuracy value 604, so that satellite positioning weights 606 of satellite positioning results are calculated according to the positioning accuracy value 604 and the weight coefficient 605; the satellite positioning results 607, satellite positioning weights 606, and other positioning results (inertial navigation positioning results and/or visual camera positioning results 608) are then input into a fused positioning universe 609 to obtain a fused positioning result 610.

The implementation of step 406 may refer to the above embodiments, which are not described herein.

In this embodiment, a plurality of grid positions are obtained by dividing a satellite view, and satellites are projected into unique grid positions based on satellite altitude angles and satellite azimuth angles, so that first sub-distribution features of each grid position are calculated respectively to obtain satellite distribution features, the features of the satellite distribution positions can be extracted better through division of the grid positions, the feature quantity contained in the satellite distribution features is enriched, and analysis of positioning accuracy values is facilitated. In addition, the positioning accuracy value is estimated through the positioning accuracy estimation model, so that the estimation accuracy of the positioning accuracy value can be improved; in addition, the precision range is divided according to different positioning application scenes, so that the fusion positioning method can be applied to the different positioning application scenes, and the positioning precision requirements of the positioning application scenes are adapted.

In order to enable the positioning accuracy estimation model to have the function of estimating the positioning accuracy value, the positioning accuracy estimation model needs to be trained in advance, so that the positioning accuracy estimation model can learn the relation between the satellite distribution characteristics and the positioning accuracy value from the input satellite distribution characteristics.

Referring to fig. 7, a training method of a positioning accuracy estimation model according to an exemplary embodiment of the present application is shown, where the method includes:

and 701, acquiring sample satellite distribution characteristics and sample labeling positioning accuracy values.

Similar to the model application process, in the model training process, sample satellite distribution characteristics are required to be obtained, and an actual positioning precision value settled by satellite positioning results is used as a target result value of a positioning precision estimation model, namely, a sample labeling positioning precision value is obtained. Illustratively, 483 eigenvalues or 123 eigenvalues may be included in each sample satellite distribution feature, where the number of eigenvalues included in the sample satellite distribution feature is determined by the grid number, the number of eigenvalue dimensions, or the grid number, the number of eigenvalue dimensions, and the number of system categories of the satellite system.

Step 702, inputting the distribution characteristics of the sample satellite into a positioning accuracy estimation model to obtain a sample prediction positioning accuracy value output by the positioning accuracy estimation model.

For example, if the positioning accuracy model is the XGBoost model, model parameters of the XGBoost model need to be set before model training, for example, a boost (weak learner type) is defined as gbtree, an objective (problem type and corresponding loss function) is defined as reg, a square-decoder, a gamma (loss reduction threshold caused by XGBoost decision tree splitting) is defined as 0.01, a max_depth (depth of tree) is defined as 6, a subsample (subsample parameter) is defined as 0.7, a color_byte (minimum sub node weight threshold) is defined as 0.5, and a num_rounds (iteration number) is defined as 500.

After the model parameters are set, the sample satellite distribution characteristics can be input into a positioning precision estimation model, and precision estimation is carried out by the positioning precision estimation model to obtain a sample prediction positioning precision value output by the positioning precision estimation model.

In step 703, a positioning accuracy estimation model is trained based on the loss between the sample labeling positioning accuracy value and the sample prediction positioning accuracy value.

Alternatively, the positioning accuracy estimation model may employ MSE mean square error as the loss function. The model loss calculation function may be as shown in formula (2).

Wherein dist _predict Sample prediction positioning precision value, dist, representing positioning precision estimation model output _truth And (5) representing the sample labeling positioning precision value.

In the model training process, the positioning accuracy estimation model can be trained iteratively based on the loss (error function) between the sample labeling positioning accuracy value and the sample prediction positioning accuracy value, and when the preset iteration times are reached and/or the loss of the positioning accuracy estimation model is smaller than a preset threshold value, the positioning accuracy estimation model training is determined to be completed, and the model training method can be used for estimating the positioning accuracy value of the satellite positioning result based on the input satellite distribution characteristics in the fusion positioning process.

It should be noted that steps 701 to 703 may be performed before the step of determining satellite distribution characteristics of each satellite observed under the location of the positioning device.

Optionally, after the positioning accuracy estimation model is deployed on each positioning device, the positions of the positioning devices may be different, so that in order to enable each positioning accuracy estimation model to be adapted to a personalized positioning device, in the application process of the positioning accuracy estimation model, the positioning accuracy estimation model can be optimized and trained based on user feedback. The process of corresponding optimization training may include the following steps one and two.

Step one, under the condition that a negative feedback signal for the fusion positioning result is received, satellite distribution characteristics and positioning accuracy values corresponding to the fusion positioning result are obtained, wherein the negative feedback signal is used for indicating that the positioning error of the fusion positioning result is larger than a positioning error threshold value.

And secondly, optimizing and training the positioning precision estimation model based on satellite distribution characteristics and positioning precision values.

In order to improve accuracy prediction accuracy of the positioning accuracy estimation model, the positioning accuracy estimation model can be optimized and trained regularly in the use process of the model, and the aim of optimization and training is mainly to samples with incorrect positioning accuracy value estimation in the use process of the positioning accuracy estimation model, and the fusion positioning result is deviated due to the incorrect positioning accuracy value estimation. Therefore, in one possible implementation manner, when the positioning device receives the negative feedback signal to the fusion positioning result, it indicates that the positioning error of the fusion positioning result is greater than the positioning error threshold, the positioning precision value and the satellite distribution feature used in the process of determining the fusion positioning result can be obtained, the satellite distribution feature and the positioning precision value are determined as negative samples, and the positioning precision estimation model is optimally trained, so as to improve the accuracy of the positioning precision estimation model in estimating the positioning precision value.

Optionally, after a certain number of negative samples are accumulated, the positioning accuracy estimation model can be optimally trained, so that generalization of the model is improved.

In the embodiment, the positioning precision estimation model is trained by using the sample satellite distribution characteristics and the sample labeling positioning precision values, so that the positioning precision estimation model can have the positioning precision value estimation capability, and the positioning precision values are estimated in the fusion positioning process; in addition, in the using process of the positioning precision estimation model, the positioning precision estimation model can be optimized and trained by collecting negative samples of the positioning precision estimation error in the using process, so that the precision estimation accuracy of the positioning precision estimation model can be further improved, and the determination accuracy of the subsequent fusion positioning result is improved.

In a satellite positioning scene, the positioning equipment can observe more satellites at an open position, and the more the number of satellites is, the more the available satellites are for determining satellite positioning results, so that compared with the fewer satellites, the satellite positioning results with higher precision can be provided; in one possible embodiment, the reference factor of the number of satellites may also be introduced when determining the satellite positioning weights of the satellite positioning results.

Referring to fig. 8, a flowchart of a fused positioning method according to another exemplary embodiment of the present application is shown, where the embodiment of the present application uses the positioning device 120 in the foregoing embodiment as an example, and the method includes:

in step 801, satellite positioning information of each satellite observed by the positioning device is acquired.

Step 802, determining satellite distribution characteristics of each satellite observed under the position of the positioning device based on the satellite positioning information.

Step 803, determining a positioning accuracy value of the satellite positioning result based on the satellite distribution characteristics.

The implementation manners of steps 801 to 803 may refer to the above embodiments, and this embodiment is not described herein.

Step 804, determining the total number of satellites observed under the position of the positioning device from the satellite positioning information.

In step 805, in the case where the total number of satellites is less than the number threshold, determining satellite positioning weights of the satellite positioning results in the fusion positioning process based on the positioning accuracy values.

Since satellite positioning results require at least 4 satellites to be determinable, the number threshold is an integer greater than 4. For example, the number threshold may be 10.

If the total number of satellites which can be observed by the positioning equipment is larger, the current position of the positioning equipment is wider, satellite signals are not blocked by other buildings or obstacles, and the satellite positioning result is relatively accurate. Otherwise, if the total number of satellites is less, the current position of the positioning equipment is possibly shielded more, and the satellite positioning result is relatively low in accuracy; when the total number of satellites is smaller than the number threshold, determining satellite positioning weight of the satellite positioning result in the fusion positioning process according to the positioning precision value; if the total number of satellites is greater than the number threshold, determining satellite positioning weights of the satellite positioning results in the fusion positioning process together based on the positioning precision value and the total number of satellites, wherein the satellite positioning weights and the total number of satellites are in positive correlation. Namely, on the basis of the positioning accuracy value, corresponding satellite weights are added for satellite positioning results determined under the scene of more total satellites.

Alternatively, a relationship between the total number of satellites and the increased satellite weight may be provided in the positioning device. The satellite positioning weight which is the satellite positioning result can be determined according to the sum of the satellite weights determined by the satellite weight and the positioning accuracy value.

Step 806, determining a fusion positioning result of the positioning device based on the satellite positioning weight and the satellite positioning result.

The implementation of step 806 may refer to the above embodiments, which are not described herein.

In this embodiment, considering the relationship between the total number of satellites observed by the positioning device and the positioning accuracy corresponding to the satellite positioning result, the total number of satellites is introduced in the process of determining the satellite positioning weight, so that the consistency between the satellite positioning weight and the actual positioning error can be further improved, thereby improving the accuracy of the fusion positioning result.

Referring to fig. 9, a block diagram of a fusion positioning device according to an exemplary embodiment of the present application is shown, where the device includes:

a determining module 901, configured to determine satellite distribution characteristics of each satellite observed at a location where the positioning device is located;

The determining module 901 is further configured to determine a positioning accuracy value of a satellite positioning result based on the satellite distribution feature, where the satellite positioning result is determined based on the observed satellite signals of the satellites;

the determining module 901 is further configured to determine a satellite positioning weight of the satellite positioning result in the fusion positioning process based on the positioning precision value, where the satellite positioning weight and the positioning precision value have a negative correlation;

and a fusion positioning module 902, configured to determine a fusion positioning result of the positioning device based on the satellite positioning weight and the satellite positioning result.

Optionally, the determining module 901 is further configured to:

acquiring satellite positioning information of each satellite observed by the positioning equipment, wherein the satellite positioning information comprises at least one of satellite number, satellite altitude angle, satellite azimuth angle, satellite signal-to-noise ratio and satellite precision attenuation factor;

and determining the satellite distribution characteristics of each satellite observed under the position of the positioning equipment based on the satellite positioning information.

Optionally, the determining module 901 is further configured to:

determining grid positions of the satellites in a satellite view based on the satellite altitude and the satellite azimuth, wherein the number of grids containing the grid positions in the satellite view is determined by a satellite altitude range and a satellite azimuth range;

Determining a first sub-distribution feature of satellites corresponding to the grid positions based on the satellite positioning information of satellites contained in the grid positions;

and determining the set of the first sub-distribution features corresponding to each grid position as the satellite distribution features, wherein the number of the feature values of the satellite distribution features is determined by the number of grids.

Optionally, the determining module 901 is further configured to:

dividing satellites contained in the grid location into different satellite systems based on the satellite positioning information of the satellites contained in the grid location;

determining a second sub-distribution characteristic of the satellite system in the grid position based on satellite positioning information of satellites of the same satellite system in the grid position;

and determining a set of second sub-distribution features corresponding to each satellite system in the grid position as the first sub-distribution features of the satellites corresponding to the grid position, wherein the number of feature values of the satellite distribution features is determined by the number of grids and the number of system categories of the satellite systems.

Optionally, the determining module 901 is further configured to:

at least one of a number of satellites of the same satellite system in the grid position, an average satellite altitude, an average signal-to-noise ratio, a target Wei Xingzhan ratio, and a satellite azimuth standard deviation is determined based on the satellite positioning information of satellites of the same satellite system in the grid position, the target Wei Xingzhan ratio referring to a duty cycle of satellites having a signal-to-noise ratio greater than a signal-to-noise ratio threshold.

Optionally, the determining module 901 is further configured to:

determining the total number of satellites observed under the position of the positioning equipment from the satellite positioning information;

determining the satellite positioning weight of the satellite positioning result in the fusion positioning process based on the positioning precision value under the condition that the total number of satellites is smaller than a quantity threshold;

the apparatus further comprises:

and the determining module is used for determining the satellite positioning weight of the satellite positioning result in the fusion positioning process based on the positioning precision value and the total number of satellites under the condition that the total number of satellites is larger than the number threshold value, and the satellite positioning weight and the total number of satellites are in positive correlation.

Optionally, the determining module 901 is further configured to:

and inputting the satellite distribution characteristics into a positioning precision estimation model to obtain the positioning precision value output by the positioning precision estimation model, wherein the positioning precision estimation model is obtained by training based on sample satellite distribution characteristics and sample labeling positioning precision values.

Optionally, the apparatus further includes:

the acquisition module is used for acquiring the sample satellite distribution characteristics and the sample labeling positioning accuracy values;

The precision prediction module is used for inputting the sample satellite distribution characteristics into the positioning precision estimation model to obtain a sample prediction positioning precision value output by the positioning precision estimation model;

and the training module is used for training the positioning precision estimation model based on the loss between the sample labeling positioning precision value and the sample prediction positioning precision value.

Optionally, the apparatus further includes:

the acquisition module is further configured to acquire the satellite distribution feature and the positioning accuracy value corresponding to the fused positioning result under the condition that a negative feedback signal to the fused positioning result is received, where the negative feedback signal is used to indicate that a positioning error of the fused positioning result is greater than a positioning error threshold;

the training module is further used for carrying out optimization training on the positioning precision estimation model based on the satellite distribution characteristics and the positioning precision value.

Optionally, the determining module 901 is further configured to:

determining a weight coefficient of the satellite positioning result under the positioning precision value, wherein the weight coefficient and the positioning precision value are in a negative correlation;

and determining the satellite positioning weight of the satellite positioning result in the fusion positioning process based on the weight coefficient and the positioning precision value.

Optionally, the determining module 901 is further configured to:

determining a positioning precision range in which the positioning precision value is positioned, wherein different positioning precision ranges correspond to different weight coefficients;

and determining the weight coefficient corresponding to the positioning precision range as the weight coefficient of the satellite positioning result under the positioning precision value.

Optionally, the apparatus further includes:

the acquisition module is used for acquiring the positioning application scene of the fusion positioning result;

the dividing module is used for dividing the positioning precision range based on the positioning precision requirement of the positioning application scene on the fusion positioning result, and different positioning application scenes correspond to different positioning precision range dividing modes.

It should be noted that: the apparatus provided in the above embodiment is only exemplified by the division of the above functional modules, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the apparatus is divided into different functional modules, so as to perform all or part of the functions described above. In addition, the apparatus and the method embodiments provided in the foregoing embodiments belong to the same concept, and detailed implementation processes of the method embodiments are described in the method embodiments, which are not repeated herein.

Referring to fig. 10, a schematic structural diagram of a computer device according to an exemplary embodiment of the present application is shown. The computer device may be applied to the positioning device in the above embodiments. Specifically, the present invention relates to a method for manufacturing a semiconductor device. The computer apparatus 1000 includes a central processing unit (Central Processing Unit, CPU) 1001, a system memory 1004 including a random access memory 1002 and a read only memory 1003, and a system bus 1005 connecting the system memory 1004 and the central processing unit 1001. The computer device 1000 also includes a basic Input/Output system (I/O) 1006, which helps to transfer information between various devices within the computer, and a mass storage device 1007 for storing an operating system 1013, application programs 1014, and other program modules 1015.

In some embodiments, the basic input/output system 1006 includes a display 1008 for displaying information and an input device 1009, such as a mouse, keyboard, or the like, for a user to input information. Wherein the display 1008 and the input device 1009 are connected to the central processing unit 1001 via an input output controller 1010 connected to a system bus 1005. The basic input/output system 1006 may also include an input/output controller 1010 for receiving and processing input from a number of other devices, such as a keyboard, mouse, or electronic stylus. Similarly, the input output controller 1010 also provides output to a display screen, a printer, or other type of output device.

The mass storage device 1007 is connected to the central processing unit 1001 through a mass storage controller (not shown) connected to the system bus 1005. The mass storage device 1007 and its associated computer-readable media provide non-volatile storage for the computer device 1000. That is, the mass storage device 1007 may include a computer readable medium (not shown) such as a hard disk or drive.

The computer readable medium may include computer storage media and communication media without loss of generality. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes random access Memory (Random Access Memory, RAM), read Only Memory (ROM), flash Memory or other solid state Memory technology, compact disk (Compact Disc Read-Only Memory, CD-ROM), digital versatile disk (Digital Versatile Disc, DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices. Of course, those skilled in the art will recognize that the computer storage medium is not limited to the one described above. The system memory 1004 and mass storage devices 1007 described above may be collectively referred to as memory.

The memory stores one or more programs configured to be executed by the one or more central processing units 1001, the one or more programs containing instructions for implementing the above-described methods, the central processing unit 1001 executing the one or more programs to implement the fusion positioning method provided by the various method embodiments described above.

According to various embodiments of the present application, the computer device 1000 may also operate by being connected to a remote computer on a network, such as the Internet. I.e., the computer device 1000 may be connected to the network 1011 via a network interface unit 1012 coupled to the system bus 1005, or alternatively, the network interface unit 1012 may be used to connect to other types of networks or remote computer systems (not shown).

The memory also includes one or more programs stored in the memory, the one or more programs including a fusion positioning method for performing the method provided by the embodiments of the present application, performed by the positioning device.

The embodiment of the application further provides a computer readable storage medium, where at least one instruction, at least one section of program, a code set, or an instruction set is stored, where at least one instruction, at least one section of program, a code set, or an instruction set is loaded and executed by a processor to implement the fusion positioning method described in any of the foregoing embodiments.

Embodiments of the present application provide a computer program product comprising computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the fusion positioning method provided in the above aspect.

Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program for instructing related hardware, and the program may be stored in a computer readable storage medium, which may be a computer readable storage medium included in the memory of the above embodiments; or may be a computer-readable storage medium, alone, that is not assembled into a computer device. The computer readable storage medium stores at least one instruction, at least one section of program, a code set or an instruction set, where the at least one instruction, the at least one section of program, the code set or the instruction set is loaded and executed by a processor to implement the method for generating a virtual-real fusion picture according to any one of the method embodiments.

Alternatively, the computer-readable storage medium may include: ROM, RAM, solid state disk (Solid State Drives, SSD), or optical disk, etc. The RAM may include resistive random access memory (Resistance Random Access Memory, reRAM) and dynamic random access memory (Dynamic Random Access Memory, DRAM), among others. The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

It should be understood that references herein to "a plurality" are to two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. And references herein to "first," "second," etc. are used to distinguish similar objects and are not intended to limit a particular order or sequence. In addition, the step numbers described herein are merely exemplary of one possible execution sequence among steps, and in some other embodiments, the steps may be executed out of the order of numbers, such as two differently numbered steps being executed simultaneously, or two differently numbered steps being executed in an order opposite to that shown, which is not limited by the embodiments of the present application.

The foregoing description of the preferred embodiments is merely exemplary in nature and is in no way intended to limit the invention, since it is intended that all modifications, equivalents, improvements, etc. that fall within the spirit and scope of the invention.

Claims

1. A fusion positioning method, the method comprising:

2. The method of claim 1, wherein determining satellite distribution characteristics for each satellite observed at the location of the positioning device comprises:

3. The method of claim 2, wherein said determining the satellite distribution characteristics of the respective satellites observed under the location of the positioning device based on the satellite positioning information comprises:

4. The method of claim 3, wherein the determining a first sub-distribution characteristic of the grid location corresponding to a satellite based on the satellite positioning information of satellites included in the grid location comprises:

5. The method of claim 4, wherein said determining a second sub-distribution characteristic of the satellite system in the grid location based on satellite positioning information of satellites of the same satellite system in the grid location comprises:

6. The method of claim 2, wherein determining satellite positioning weights for the satellite positioning results in a fused positioning process based on the positioning accuracy values comprises:

the method further comprises the steps of:

and under the condition that the total number of satellites is larger than the number threshold, determining the satellite positioning weight of the satellite positioning result in the fusion positioning process based on the positioning precision value and the total number of satellites, wherein the satellite positioning weight and the total number of satellites are in positive correlation.

7. The method according to any one of claims 1 to 6, wherein determining a positioning accuracy value of a satellite positioning result based on the satellite distribution characteristics comprises:

8. The method of claim 7, wherein the method further comprises:

acquiring the distribution characteristics of the sample satellite and the sample labeling positioning accuracy value;

inputting the sample satellite distribution characteristics into the positioning precision estimation model to obtain a sample prediction positioning precision value output by the positioning precision estimation model;

and training the positioning precision estimation model based on the loss between the sample labeling positioning precision value and the sample predicting positioning precision value.

9. The method of claim 7, wherein the method further comprises:

under the condition that a negative feedback signal for the fusion positioning result is received, acquiring the satellite distribution characteristics and the positioning accuracy value corresponding to the fusion positioning result, wherein the negative feedback signal is used for indicating that the positioning error of the fusion positioning result is larger than a positioning error threshold;

and carrying out optimization training on the positioning precision estimation model based on the satellite distribution characteristics and the positioning precision value.

10. The method according to any one of claims 1 to 6, wherein determining satellite positioning weights of the satellite positioning results in a fusion positioning process based on the positioning accuracy values comprises:

11. The method of claim 10, wherein said determining the weight coefficient of the satellite positioning result at the positioning accuracy value comprises:

12. The method of claim 11, wherein the method further comprises:

acquiring a positioning application scene of the fusion positioning result;

dividing the positioning precision range based on the positioning precision requirement of the positioning application scene on the fusion positioning result, wherein different positioning application scenes correspond to different positioning precision range dividing modes.

13. A fusion positioning device, the device comprising:

14. A computer device comprising a processor and a memory, wherein the memory has stored therein at least one program that is loaded and executed by the processor to implement the fusion positioning method of any of claims 1-12.

15. A computer readable storage medium having stored therein at least one program loaded and executed by a processor to implement the fusion positioning method of any of claims 1 to 12.

16. A computer program product, characterized in that it comprises computer instructions stored in a computer-readable storage medium, from which computer instructions a processor of a computer device reads, which processor executes the computer instructions to implement the fusion positioning method according to any of claims 1 to 12.