Performance evaluation method and device for satellite-based enhanced navigation

Abstract

The invention provides a performance evaluation method and device for satellite-based enhanced navigation, and relates to the technical field of high-precision positioning. The method comprises the steps that the area range of a to-be-evaluated area is acquired, grid point division operation is carried out on the to-be-evaluated area according to the area range, and the grid point division operation is used for dividing the to-be-evaluated area into a plurality of sampling grid points; acquiring enhanced information data and broadcast ephemeris data of the target satellite, and calculating an enhanced orbit error and an enhanced clock error of the target satellite according to the enhanced information data and the broadcast ephemeris data; the enhanced orbit error and the enhanced clock error of the target satellite and the positions of the sampling grid points serve as input, multiple sets of positioning errors of the target satellite on the multiple sampling grid points are calculated through a precise positioning model, and one sampling grid point corresponds to one set of positioning errors; constructing a positioning error sequence through the multiple groups of positioning errors, and calculating convergence time and positioning precision when convergence conditions are met according to the positioning error sequence; and sending the convergence time and the positioning precision as performance evaluation results to the terminal equipment. According to the method, the problem that the positioning performance evaluation result cannot comprehensively and objectively reflect the actual capability of the enhanced service at the service area boundary or even under the condition that no actual measurement station is available due to the fact that the existing satellite-based enhanced service positioning performance evaluation method cannot uniformly select the tracking stations in the specified service area to perform positioning performance evaluation is solved.

Description

Technical Field

[0001] The present application relates to the field of high-precision positioning technology, and in particular to a performance evaluation method and device for satellite-based enhanced navigation. Background Art

[0002] Today, major global navigation satellite systems (GNSS) have been vigorously developing their own satellite-based augmentation services. The satellite-based augmentation services that have been provided include Beidou's precise point positioning service PPP-B2b, Galileo's high-precision service HAS, and QZSS's wide-area augmentation service MADOCA-PPP. Evaluating the positioning performance of satellite-based augmentation services is a prerequisite for users to better use positioning services, and is also the key to improving the performance of positioning systems.

[0003] The current global satellite navigation system's satellite-based augmentation service positioning performance evaluation refers to the traditional basic navigation service performance evaluation method, which selects the measured data of satellite tracking stations in the service area, uses enhanced orbit and clock products for real-time precise positioning, and statistically evaluates the positioning error. However, this method faces the following difficulties in the performance evaluation of satellite-based augmentation positioning services: PPP-B2b, HAS and MADOCA-PPP augmentation services only cover some areas of the world, and it is impossible to evenly select tracking stations in the designated service area for positioning performance evaluation. There are even cases where there are no measured stations available at the border of the service area. Therefore, the positioning performance evaluation results cannot fully and objectively reflect the actual capabilities of the augmented services.

[0004] Therefore, there is an urgent need for a performance evaluation method and device for satellite-based enhanced navigation. Summary of the invention

[0005] The present application provides a performance evaluation method and device for satellite-based augmented navigation, which solves the problem that the current satellite-based augmented service positioning performance evaluation method cannot evenly select tracking stations in a specified service area for positioning performance evaluation. Therefore, in the case where there are no actual measurement stations available at the boundary of the service area, the positioning performance evaluation results cannot fully and objectively reflect the actual capabilities of the augmented service.

[0006] In a first aspect of the present application, a performance evaluation method for satellite-based augmented navigation is provided, the method comprising: obtaining the area scope of an area to be evaluated, and performing a grid point division operation on the area to be evaluated according to the area scope, the grid point division operation being used to divide the area to be evaluated into a plurality of sampling grid points; obtaining enhanced information data and broadcast ephemeris data of a target satellite, and calculating an enhanced orbit error and an enhanced clock error of the target satellite according to the enhanced information data and the broadcast ephemeris data; taking the enhanced orbit error, enhanced clock error and sampling grid point position of the target satellite as input, calculating a plurality of groups of positioning errors of the target satellite at a plurality of sampling grid points respectively through a precise positioning model, one sampling grid point corresponding to a group of positioning errors; constructing a positioning error sequence through a plurality of groups of positioning errors, and calculating a convergence time and a positioning accuracy when a convergence condition is met according to the positioning error sequence; and sending the convergence time and the positioning accuracy as a performance evaluation result to a terminal device.

[0007] Optionally, the area scope of the area to be evaluated is obtained, and a grid point division operation is performed on the area to be evaluated according to the area scope, specifically including: obtaining an initial longitude interval and an initial latitude interval; and performing a grid point division operation according to the initial longitude interval and the initial latitude interval and the area scope.

[0008] Optionally, after the initial longitude interval and the initial latitude interval are used and the grid point division operation is performed according to the regional range, the method further includes: dynamically adjusting the division of the multiple sampling grid points according to the following formula:

[0009]

[0010] Among them, B0 is the initial longitude interval, L 0,0 is the initial latitude interval, α is the latitude and longitude resolution ratio coefficient, and α=dB 0 / dL0, i is the order of grid point division from low latitude to high latitude, B i is the initial longitude interval after the i-th grid point division operation, L i,0 is the initial latitude interval after the i-th grid point division operation, dB i-1 is the longitude resolution after the i-1th grid point division operation, dL i-1 It is the latitude resolution after the i-1th grid point division operation.

[0011] Optionally, the enhanced orbit error and enhanced clock error of the target satellite are calculated, specifically including: obtaining enhanced orbit data and reference orbit data, and obtaining the enhanced orbit error by calculating the mutual difference between the enhanced orbit data and the reference orbit data; obtaining enhanced clock error data and reference clock error data, and obtaining the enhanced clock error by calculating the mutual difference between the enhanced clock error data and the reference clock error data.

[0012] Optionally, before taking the enhanced orbit error, enhanced clock error and sampling grid point position of the target satellite as input and respectively calculating multiple groups of positioning errors of the target satellite at multiple sampling grid points through the precise positioning model, it is necessary to construct a precise positioning model, specifically including: constructing a simulated observation equation of an ionosphere-free combination through the following formula, and constructing the precise positioning model through the simulated observation equation of the ionosphere-free combination:

[0013]

[0014] Wherein, r is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the satellite-to-earth direction cosine, dX r is the position error simulation parameter, c is the speed of light in vacuum, is the projection of the enhanced orbit error and the enhanced clock error in the satellite-to-ground direction, that is, Among them, ΔO s is the enhanced orbit error, ΔC s is the enhanced clock error, dt r is the clock difference of the terminal device, is the slant path tropospheric delay, is the pseudorange hardware delay simulation parameter of the target satellite, λ IF is the wavelength of the ionosphere-free combination, are the ambiguity simulation parameters of the ionospheric-free combination.

[0015] Optionally, multiple groups of positioning errors of the target satellite at multiple sampling grid points are calculated separately through the precise positioning model, specifically including: calculating the sampling grid point state estimation values ​​of the target satellite at multiple sampling grid points separately through the precise positioning model, the sampling grid point state estimation values ​​including position error estimation values, tropospheric error estimation values, ambiguity estimation values ​​and receiver clock error estimation values; obtaining the actual value of the sampling grid point state, and taking the error between the actual value of the sampling grid point state and the sampling grid point state estimation value as the positioning error.

[0016] Optionally, the convergence time when the convergence condition is met is obtained, specifically including: the convergence time when the convergence condition is met is calculated according to the positioning error sequence, specifically including: obtaining the first time point corresponding to the calculation of the initial positioning error, the initial positioning error being the first positioning error in the positioning error sequence that is calculated by the precise positioning model; obtaining the second time point corresponding to the calculation of the target positioning error, the target positioning error being the first positioning error in the positioning error sequence that meets the preset positioning accuracy requirement; and taking the time period between the second time point and the first time point as the convergence time.

[0017] In a second aspect of the present application, a performance evaluation device for satellite-based enhanced navigation is provided, the device comprising an acquisition module and a processing module, wherein:

[0018] The acquisition module is used to obtain the area range of the area to be evaluated, and perform a grid point division operation on the area to be evaluated according to the area range, and the grid point division operation is used to divide the area to be evaluated into multiple sampling grid points; obtain the enhanced information data and broadcast ephemeris data of the target satellite, and calculate the enhanced orbit error and enhanced clock error of the target satellite based on the enhanced information data and the broadcast ephemeris data.

[0019] The processing module is used to take the enhanced orbit error, enhanced clock error and sampling grid point position of the target satellite as input, and calculate multiple groups of positioning errors of the target satellite on multiple sampling grid points through the precise positioning model, and one sampling grid point corresponds to one group of positioning errors; construct a positioning error sequence through multiple groups of positioning errors, and calculate the convergence time and positioning accuracy when the convergence conditions are met according to the positioning error sequence; send the convergence time and positioning accuracy to the terminal device as the performance evaluation result.

[0020] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any one of the methods described above.

[0021] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to perform any of the above methods.

[0022] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0023] 1. By obtaining the area range of the area to be evaluated and performing grid point division operations, the area to be evaluated is divided into multiple sampling grid points. The enhanced information data and broadcast ephemeris data of the target satellite are obtained to calculate the enhanced orbit error and enhanced clock error. Taking the enhanced orbit error, enhanced clock error and sampling grid point position of the target satellite as input, multiple groups of positioning errors on multiple sampling grid points are calculated through the precise positioning model, and a positioning error sequence is constructed through multiple groups of positioning errors. The convergence time and positioning accuracy when the convergence conditions are met are calculated based on the positioning error sequence; the convergence time and positioning accuracy are sent to the terminal device as the performance evaluation result, so as to ensure that each sampling point can perform independent positioning error calculation by dividing the entire area to be evaluated into grid points, thereby achieving a comprehensive and objective satellite-based enhanced navigation performance evaluation.

[0024] 2. By obtaining the initial longitude and latitude intervals and dynamically adjusting the division of sampling grid points, adaptive grid point division that takes into account both high resolution and computational efficiency can be achieved.

[0025] 3. The precise positioning model is used to calculate the estimated state values ​​of the target satellite at multiple sampling grid points, obtain the actual state values ​​of the sampling grid points, and use the error between the actual state value of the sampling grid point and the estimated state value of the sampling grid point as the positioning error, thereby effectively identifying and quantifying the orbit and clock deviations in the enhanced service, providing a data basis for the subsequent performance evaluation of the precise positioning model, and improving the evaluation accuracy and reliability of the precise positioning model. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flowchart of a performance evaluation method for satellite-based enhanced navigation provided in an embodiment of the present application;

[0027] Figure 2 It is a module schematic diagram of a performance evaluation device for satellite-based enhanced navigation provided in an embodiment of the present application;

[0028] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0029] Explanation of the reference numerals: 21, acquisition module; 22, processing module; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0030] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0031] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0032] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more.

[0033] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0034] Today, major GNSSs have been vigorously developing their own satellite-based augmentation services. The satellite-based augmentation services that have been provided include Beidou's precise point positioning service PPP-B2b, Galileo's high-precision service HAS, and QZSS's wide-area augmentation service MADOCA-PPP. Evaluating the positioning performance of satellite-based augmentation services is a prerequisite for users to better use positioning services and is also the key to improving the performance of positioning systems.

[0035] The current global satellite navigation system's satellite-based augmentation service positioning performance evaluation refers to the traditional basic navigation service performance evaluation method, which selects the measured data of satellite tracking stations in the service area, uses enhanced orbit and clock products for real-time precise positioning, and statistically evaluates the positioning error. However, this method faces the following difficulties in the performance evaluation of satellite-based augmentation positioning services: PPP-B2b, HAS and MADOCA-PPP augmentation services only cover some areas of the world, and it is impossible to evenly select tracking stations in the designated service area for positioning performance evaluation. There are even cases where there are no measured stations available at the border of the service area. Therefore, the positioning performance evaluation results cannot fully and objectively reflect the actual capabilities of the augmented services.

[0036] Therefore, there is an urgent need for a performance evaluation method and device for satellite-based enhanced navigation.

[0037] Please refer to Figure 1 , which shows a flow chart of a performance evaluation method for satellite-based enhanced navigation provided in an embodiment of the present application, and the flow chart mainly includes the following steps: S101 to S104.

[0038] Step S101, obtaining the area range of the area to be evaluated, and performing a grid point division operation on the area to be evaluated according to the area range, wherein the grid point division operation is used to divide the area to be evaluated into a plurality of sampling grid points.

[0039] Specifically, when conducting a high-precision positioning performance test on GNSS, the area to be evaluated is first divided into grid points using variable resolution. At this time, the area range corresponding to the area to be evaluated is obtained, and the area to be evaluated is divided into grid points according to the size of the area range, thereby dividing the area to be evaluated into multiple sampling grid points.

[0040] In a possible implementation, step S101 further includes: obtaining an initial longitude interval, an initial latitude interval, and a latitude and longitude resolution ratio coefficient; performing a grid point division operation according to the initial longitude interval, the initial latitude interval, and the latitude and longitude resolution ratio coefficient and based on the regional range.

[0041] Specifically, the earth is assumed to be a sphere, and the initial longitude interval and the initial latitude interval of the sampling grid points are set according to the size of the regional scope, so as to perform a grid point division operation on the regional scope. For example, assuming that the evaluation scope is a global area, the initial longitude interval and the initial latitude interval can be set to 5 degrees and 2.5 degrees respectively. Assuming that the evaluation scope is a regional scope, the initial longitude interval and the initial latitude interval can be set to 2 degrees and 1 degree respectively according to the size of the regional scope. After that, the starting longitude and latitude point is determined, and according to the initial longitude interval and the starting latitude interval, starting from the starting longitude and latitude point, each longitude and latitude point in the regional scope is gradually calculated, and then each longitude and latitude point is used as the coordinates corresponding to multiple sampling grid points, so as to complete the grid point division operation.

[0042] In a possible implementation, step S101 further includes: dynamically adjusting the division of the plurality of sampling grid points according to the following formula:

[0043]

[0044] Among them, B0 is the initial longitude interval, L 0,0 is the initial latitude interval, α is the latitude and longitude resolution ratio coefficient, and α=dB 0 / dL0, i is the order of grid point division from low latitude to high latitude, B i is the initial longitude interval after the i-th grid point division operation, L i,0 is the initial latitude interval after the i-th grid point division operation, dB i-1 is the longitude resolution after the i-1th grid point division operation, dL i-1 It is the latitude resolution after the i-1th grid point division operation.

[0045] Specifically, considering that equally spaced sampling grid points cover a larger area in low-latitude areas and a smaller area in high-latitude areas, in order to ensure that the area represented by the sampling grid points is relatively consistent in different latitude bands, that is, to more reliably reflect the satellite-based augmented positioning performance of the area to be evaluated, the division of multiple sampling grid points needs to be dynamically adjusted according to the above formula.

[0046] Step S102: Acquire the enhanced information data and broadcast ephemeris data of the target satellite, and calculate the enhanced orbit error and enhanced clock error of the target satellite according to the enhanced information data and the broadcast ephemeris data.

[0047] Specifically, the enhanced information data and broadcast ephemeris data of the target satellite are obtained, and the enhanced information data and broadcast ephemeris data can be obtained through a satellite signal receiver terminal device or through the Internet. This embodiment assumes that the enhanced information data and the third-party precise orbit and clock error products can be obtained. Only in this way can the errors of the enhanced orbit and clock error be calculated to achieve the simulation of real-time precise positioning, and the third-party precise orbit and clock error products can be obtained from the public network addresses of iGMAS, IGS official website, data center and analysis center.

[0048] In a possible implementation, step S102 also includes: acquiring enhanced orbit data and reference orbit data, and acquiring an enhanced orbit error by calculating the mutual difference between the enhanced orbit data and the reference orbit data; acquiring enhanced clock difference data and reference clock difference data, and acquiring an enhanced clock difference error by calculating the mutual difference between the enhanced clock difference data and the reference clock difference data.

[0049] Specifically, the enhanced orbit data and reference orbit data are obtained, wherein the reference orbit data is orbit information provided based on a high-precision orbit model or historical data, which is usually data that has been accurately calculated or provided by a ground base station. These data can be set according to the satellite's designed orbit, predicted orbit or real-time monitoring information; the enhanced clock error data and reference clock error data are obtained, wherein the reference clock error data is clock error information based on a high-precision time standard or provided by a ground base station, which is usually a time deviation that has been accurately calculated and can be set according to the satellite's clock calibration records, historical data or real-time monitoring information. Afterwards, the enhanced orbit error and enhanced clock error are calculated using the following formula:

[0050]

[0051] Among them, ΔO s To enhance the orbit error, that is, to enhance the orbit data and reference orbit data The difference between the two, ΔC s To enhance the clock error, that is, to enhance the clock error data and reference clock error data The difference between them.

[0052] Step S103, taking the enhanced orbit error and enhanced clock error of the target satellite as input, a plurality of groups of positioning errors of the target satellite at a plurality of sampling grid points are calculated respectively through a precise positioning model, and one sampling grid point corresponds to one group of positioning errors.

[0053] Specifically, the enhanced orbit error and enhanced clock error are used as inputs of the precise positioning model, and parameter allocation operations are performed. The specific steps of the parameter allocation operation are as follows: During the positioning process, the changes of the enhanced orbit error and enhanced clock error are continuously monitored, and the error estimates are dynamically adjusted according to the latest enhanced information data and broadcast ephemeris data. A suitable adaptive algorithm is used to update the enhanced orbit error and enhanced clock error. Different weights are set according to the degree of influence of the enhanced orbit error and enhanced clock error on the positioning results. The weight values ​​of the enhanced orbit error and enhanced clock error can be determined by historical data analysis or experience-based methods. According to the results of the weighted error calculation, the corrected positioning parameters are output. These parameters will be used in subsequent positioning calculations to improve positioning accuracy. The simulated observation equation of the ionosphere-free combination can be constructed by the following formula, and the precise positioning model can be constructed by the simulated observation equation of the ionosphere-free combination:

[0054]

[0055] Among them, r is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the satellite-to-earth direction cosine, dX r is the position error simulation parameter, c is the speed of light in vacuum, To enhance the projection of orbit error and clock error in the satellite-to-ground direction, Among them, ΔO s To enhance the orbit error, ΔC s To enhance the clock error, dt r is the clock error of the terminal device, is the slant path tropospheric delay, is the pseudorange hardware delay simulation parameter of the target satellite, λ IF is the wavelength of the ionosphere-free combination, are the ambiguity simulation parameters for the ionosphere-free combination.

[0056] Specifically, a single group of positioning errors is used as an example to illustrate, and a simulated observation equation of the ionosphere-free combination corresponding to the visible target satellite is constructed, and each group of positioning errors is calculated by the simulated observation equation of the ionosphere-free combination. In the simulated observation equation of the ionosphere-free combination, the weight ratio of the pseudorange and phase equations should be consistent with the empirical value. For example, a weight ratio of 1:1000 is used, and the normal equation is obtained by superimposing all simulated observation equations, and then a floating point solution can be solved to obtain the state estimate of the sampling grid point, and then the above calculation process is repeated to obtain multiple groups of positioning errors. Among them, the state estimate of the sampling grid point includes but is not limited to: position error estimate, tropospheric error estimate, ambiguity estimate, and receiver clock error estimate, etc. At the same time, the actual state value of the sampling grid point is obtained, and the actual state value of the sampling grid point can be obtained by, and the error between the actual state value of the sampling grid point and the estimated state value of the sampling grid point is used as the positioning error.

[0057] Step S104, constructing a positioning error sequence through multiple groups of positioning errors, and calculating the convergence time and positioning accuracy when the convergence condition is met according to the positioning error sequence.

[0058] Specifically, a positioning error sequence is constructed by using the multiple groups of positioning errors calculated in step S103, and the convergence time and positioning accuracy when the convergence condition is met are calculated according to the positioning error sequence.

[0059] In a possible implementation, step S104 also includes: obtaining a first time point corresponding to when calculating the initial positioning error, the initial positioning error being the first positioning error in the positioning error sequence that is calculated by the precise positioning model; obtaining a second time point corresponding to when calculating the target positioning error, the target positioning error being the first positioning error in the positioning error sequence that meets the preset positioning accuracy requirement; and using the time period between the second time point and the first time point as the convergence time.

[0060] Specifically, when obtaining the convergence time, first record the first time point corresponding to when the first group of positioning errors starts to be calculated. Then, when calculating each group of positioning errors, determine whether the positioning errors meet the preset positioning accuracy requirements after the calculation is completed. The preset positioning requirements can be set according to the actual needs of the positioning performance evaluation. For example, obtain multiple groups of positioning errors to form an error sequence within a period of time, calculate the 95% quantile of the error sequence, and determine whether the quantile is less than or equal to the positioning accuracy requirement. Obtain the positioning error when the preset positioning accuracy requirement is met for the first time, and the second time point corresponding to when the positioning error calculation is completed. At this time, the time interval between the second time point and the first time point is the convergence time. According to actual needs, the conditions for obtaining the convergence time can be restricted more strictly. For example, after obtaining the positioning error that meets the preset positioning accuracy requirement for the first time, it is determined whether the calculation of the positioning error continues to meet the positioning accuracy requirement within the preset time period. If the positioning accuracy requirement is continuously met, the time interval between the second time point and the first time point and the sum of the preset time period are used as the convergence time; if the positioning accuracy requirement is not continuously met, the first group of positioning errors is redefined and the convergence time is re-obtained until a convergence time that meets the conditions is obtained. Among them, the preset time period can be set to 1 minute, 3 minutes, 5 minutes, etc., and the embodiments in this application do not limit the setting of the preset time period.

[0061] Step S105: sending the convergence time and positioning accuracy as performance evaluation results to the terminal device.

[0062] The convergence time and positioning accuracy are sent to the terminal device as performance evaluation results to complete the performance evaluation operation of the target satellite's satellite-based enhanced navigation.

[0063] This application adopts the above method to obtain the area scope of the area to be evaluated, and performs grid point division operations to divide the area to be evaluated into multiple sampling grid points. Obtain the enhanced information data and broadcast ephemeris data of the target satellite, and calculate the enhanced orbit error and enhanced clock error. Taking the enhanced orbit error, enhanced clock error and sampling grid point position of the target satellite as input, multiple groups of positioning errors on multiple sampling grid points are calculated through a precise positioning model, and a positioning error sequence is constructed through multiple groups of positioning errors. The convergence time and positioning accuracy when the convergence conditions are met are calculated according to the positioning error sequence; the convergence time and positioning accuracy are sent to the terminal device as the performance evaluation result, thereby ensuring that each sampling point can perform independent positioning error calculation by dividing the entire area to be evaluated into grid points, thereby achieving a comprehensive and objective satellite-based enhanced navigation performance evaluation.

[0064] Please refer to Figure 2, which shows a module schematic diagram of a performance evaluation device for satellite-based enhanced navigation provided in an embodiment of the present application, the device includes an acquisition module 21 and a processing module 22, wherein:

[0065] The acquisition module 21 is used to obtain the area range of the area to be evaluated, and perform a grid point division operation on the area to be evaluated according to the area range, and the grid point division operation is used to divide the area to be evaluated into multiple sampling grid points; obtain the enhanced information data and broadcast ephemeris data of the target satellite, and calculate the enhanced orbit error and enhanced clock error of the target satellite based on the enhanced information data and the broadcast ephemeris data.

[0066] The processing module 22 is used to take the enhanced orbit error, enhanced clock error and sampling grid point position of the target satellite as input, and calculate multiple groups of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model, and one sampling grid point corresponds to one group of positioning errors; construct a positioning error sequence through multiple groups of positioning errors, and calculate the convergence time and positioning accuracy when the convergence conditions are met according to the positioning error sequence; and send the convergence time and positioning accuracy to the terminal device as a performance evaluation result.

[0067] In a possible implementation, the acquisition module 21 is used to obtain the area scope of the area to be evaluated, and perform a grid point division operation on the area to be evaluated according to the area scope, specifically including: obtaining an initial longitude interval and an initial latitude interval; using the initial longitude interval and the initial latitude interval, and performing a grid point division operation according to the area scope.

[0068] In a possible implementation, the acquisition module 21 is used to, after performing a grid point division operation according to the initial longitude interval and the initial latitude interval and the regional range, the method further includes: dynamically adjusting the division of the multiple sampling grid points according to the following formula:

[0069]

[0070] Among them, B0 is the initial longitude interval, L 0,0 is the initial latitude interval, α is the latitude and longitude resolution ratio coefficient, and α=dB 0 / dL0, i is the order of grid point division from low latitude to high latitude, B i is the initial longitude interval after the i-th grid point division operation, L i,0 is the initial latitude interval after the i-th grid point division operation, dB i-1 is the longitude resolution after the i-1th grid point division operation, dL i-1 It is the latitude resolution after the i-1th grid point division operation.

[0071] In one possible implementation, the acquisition module 21 is used to calculate the enhanced orbit error and enhanced clock error of the target satellite, specifically including: acquiring enhanced orbit data and reference orbit data, and obtaining the enhanced orbit error by calculating the mutual difference between the enhanced orbit data and the reference orbit data; acquiring enhanced clock difference data and reference clock difference data, and obtaining the enhanced clock difference error by calculating the mutual difference between the enhanced clock difference data and the reference clock difference data.

[0072] In a possible implementation, the processing module 22 is used to construct a precise positioning model before respectively calculating multiple groups of positioning errors of the target satellite at multiple sampling grid points using the precise positioning model, taking the enhanced orbit error, enhanced clock error and sampling grid point position of the target satellite as inputs. Specifically, the precise positioning model is constructed by constructing a simulated observation equation of an ionosphere-free combination using the following formula, and constructing a precise positioning model using the simulated observation equation of an ionosphere-free combination:

[0073]

[0074] Among them, r is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the satellite-to-earth direction cosine, dX r is the position error simulation parameter, c is the speed of light in vacuum, To enhance the projection of orbit error and clock error in the satellite-to-ground direction, Among them, ΔO s To enhance the orbit error, ΔC s To enhance the clock error, dt r is the clock error of the terminal device, is the slant path tropospheric delay, is the pseudorange hardware delay simulation parameter of the target satellite, λ IF is the wavelength of the ionosphere-free combination, are the ambiguity simulation parameters for the ionosphere-free combination.

[0075] In a possible implementation, the processing module 22 is used to calculate multiple groups of positioning errors of the target satellite at multiple sampling grid points respectively through a precise positioning model, specifically including: calculating the sampling grid point state estimation values ​​of the target satellite at multiple sampling grid points respectively through a precise positioning model, the sampling grid point state estimation values ​​including position error estimation values, tropospheric error estimation values, ambiguity estimation values ​​and receiver clock error estimation values; obtaining the actual value of the sampling grid point state, and taking the error between the actual value of the sampling grid point state and the sampling grid point state estimation value as the positioning error.

[0076] In a possible implementation, the processing module 22 is used to calculate the convergence time when the convergence conditions are met based on the positioning error sequence, specifically including: obtaining the first time point corresponding to the calculation of the initial positioning error, the initial positioning error being the first positioning error in the positioning error sequence that is calculated by the precise positioning model; obtaining the second time point corresponding to the calculation of the target positioning error, the target positioning error being the first positioning error in the positioning error sequence that meets the preset positioning accuracy requirement; and using the time period between the second time point and the first time point as the convergence time.

[0077] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0078] The present application also provides an electronic device. Figure 3 , Figure 3 30 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include: at least one processor 301, at least one communication bus 302, a user interface 303, at least one network interface 304, and a memory 305.

[0079] The communication bus 302 is used to realize the connection and communication between these components.

[0080] The user interface 303 may include a display screen (Display) and a camera (Camera), and the optional user interface 303 may also include a standard wired interface and a wireless interface.

[0081] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0082] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0083] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a performance evaluation application for satellite-based enhanced navigation.

[0084] exist Figure 3In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the performance evaluation application of satellite-based enhanced navigation stored in the memory 305. When executed by one or more processors 301, the electronic device executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited to the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0085] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0086] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0087] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0088] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0090] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0091] The above are only exemplary embodiments disclosed in this application, and the scope of the disclosure of this application cannot be limited by this. That is, any equivalent changes and modifications made according to the teachings disclosed in this application are still within the scope of the disclosure of this application. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other implementation schemes disclosed in this application.

[0092] This application is intended to cover any modifications, uses or adaptive changes disclosed in this application, which follow the general principles disclosed in this application and include common knowledge or customary technical means in the technical field not recorded in this application.

Claims

1. A performance evaluation method for satellite-based augmented navigation, characterized in that: The method comprises: Acquire the area range of the area to be evaluated, and perform a grid point division operation on the area to be evaluated according to the area range, wherein the grid point division operation is used to divide the area to be evaluated into a plurality of sampling grid points; Acquire enhanced information data and broadcast ephemeris data of a target satellite, and calculate an enhanced orbit error and an enhanced clock error of the target satellite according to the enhanced information data and the broadcast ephemeris data; Taking the enhanced orbit error, the enhanced clock error and the position of the sampling grid point of the target satellite as input, a plurality of groups of positioning errors of the target satellite at the plurality of the sampling grid points are respectively calculated by a precise positioning model, wherein one sampling grid point corresponds to one group of the positioning errors; Constructing a positioning error sequence through multiple groups of positioning errors, and calculating the convergence time and positioning accuracy when the convergence condition is met according to the positioning error sequence; The convergence time and the positioning accuracy are sent to the terminal device as performance evaluation results.

2. The method according to claim 1, characterized in that The obtaining of the area range of the area to be evaluated and performing a grid point division operation on the area to be evaluated according to the area range specifically includes: Get the initial longitude interval and initial latitude interval; The grid point division operation is performed through the initial longitude interval and the initial latitude interval and according to the area range.

3. The method according to claim 2, characterized in that After the initial longitude interval and the initial latitude interval are used and the grid point division operation is performed according to the area range, the method further includes: The division of multiple sampling grid points is dynamically adjusted according to the following formula: Wherein, B0 is the initial longitude interval, L 0,0 is the initial latitude interval, α is the latitude and longitude resolution ratio coefficient, and α = dB 0 / dL0, i is the order of performing the grid point division operation from low latitude to high latitude, B i is the initial longitude interval after the i-th grid point division operation, L i,0 is the initial latitude interval after the i-th grid point division operation, dB i-1 is the longitude resolution after the i-1th grid point division operation, dL i-1 It is the latitude resolution after the i-1th grid point division operation.

4. The method according to claim 1, characterized in that The calculating the enhanced orbit error and enhanced clock error of the target satellite specifically includes: Acquire enhanced orbit data and reference orbit data, and acquire the enhanced orbit error by calculating the mutual difference between the enhanced orbit data and the reference orbit data; Enhanced clock difference data and reference clock difference data are obtained, and the enhanced clock difference error is obtained by calculating the mutual difference between the enhanced clock difference data and the reference clock difference data.

5. The method according to claim 4, characterized in that Before respectively calculating multiple groups of positioning errors of the target satellite at multiple sampling grid points using a precise positioning model with the enhanced orbit error and the enhanced clock error of the target satellite as input, the precise positioning model needs to be constructed, specifically including: The simulated observation equation of the ionosphere-free combination is constructed by the following formula, and the precise positioning model is constructed by the simulated observation equation of the ionosphere-free combination: Wherein, r is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the satellite-to-earth direction cosine, dX r is the position error simulation parameter, c is the speed of light in vacuum, is the projection of the enhanced orbit error and the enhanced clock error in the satellite-to-ground direction, that is, Among them, ΔO s is the enhanced orbit error, ΔC s is the enhanced clock error, dt r is the clock difference of the terminal device, is the slant path tropospheric delay, is the pseudorange hardware delay simulation parameter of the target satellite, λ IF is the wavelength of the ionosphere-free combination, are the ambiguity simulation parameters of the ionospheric-free combination.

6. The method according to claim 1, characterized in that The calculating, by the precise positioning model, a plurality of groups of positioning errors of the target satellite at a plurality of the sampling grid points respectively comprises: Calculating sampling grid point state estimation values ​​of the target satellite at the plurality of sampling grid points respectively by using the precise positioning model, the sampling grid point state estimation values ​​comprising a position error estimation value, a tropospheric error estimation value, an ambiguity estimation value, and a receiver clock error estimation value; The actual value of the sampling grid point state is obtained, and the error between the actual value of the sampling grid point state and the estimated value of the sampling grid point state is used as the positioning error.

7. The method according to claim 1, characterized in that The calculating, according to the positioning error sequence, the convergence time when the convergence condition is satisfied specifically includes: Obtaining a first time point corresponding to the calculation of an initial positioning error, wherein the initial positioning error is the first positioning error in the positioning error sequence calculated by the precise positioning model; Obtaining a second time point corresponding to when calculating a target positioning error, wherein the target positioning error is the first positioning error in the positioning error sequence that meets a preset positioning accuracy requirement; The time period between the second time point and the first time point is used as the convergence time.

8. A performance evaluation device for satellite-based augmented navigation, characterized in that: The device comprises an acquisition module and a processing module, wherein: The acquisition module is used to acquire the area range of the area to be evaluated, and perform a grid point division operation on the area to be evaluated according to the area range, wherein the grid point division operation is used to divide the area to be evaluated into a plurality of sampling grid points; acquire enhanced information data and broadcast ephemeris data of the target satellite, and calculate the enhanced orbit error and enhanced clock error of the target satellite according to the enhanced information data and the broadcast ephemeris data; The processing module is used to take the enhanced orbit error, the enhanced clock error and the sampling grid point position of the target satellite as input, and calculate multiple groups of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model, and one sampling grid point corresponds to one group of positioning errors; construct a positioning error sequence through multiple groups of positioning errors, and calculate the convergence time and positioning accuracy when the convergence condition is met according to the positioning error sequence; and send the convergence time and the positioning accuracy as a performance evaluation result to the terminal device.

9. An electronic device, characterized in that: It includes a processor, a communication bus, a user interface, a network interface and a memory, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

Images