A performance evaluation method and device for satellite-based augmentation navigation

Abstract

The present application provides a method and device for evaluating the performance of satellite-based augmentation navigation, which relates to the field of high-precision positioning technology. The method includes: obtaining the regional scope of the area to be evaluated, and performing a grid point division operation on the area to be evaluated according to the regional scope, where the grid point division operation is used to divide the area to be evaluated into multiple sampling grid points; obtaining the augmentation information data and broadcast ephemeris data of the target satellite, and calculating the augmentation orbit error and augmentation clock error of the target satellite according to the augmentation information data and broadcast ephemeris data; using the augmentation orbit error, augmentation clock error of the target satellite and the sampling grid point positions as inputs, and respectively calculating multiple groups of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model, where one sampling grid point corresponds to one group of 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; sending the convergence time and positioning accuracy as the performance evaluation results to the terminal device. The present application solves the problem that the current method for evaluating the positioning performance of satellite-based augmentation services cannot uniformly select tracking stations in a specified service area for positioning performance evaluation. Therefore, in the case where there are no actual measurement stations available even at the boundary of the service area, the positioning performance evaluation results cannot comprehensively and objectively reflect the actual capabilities of the augmentation service.

Description

Technical Field

[0001] This application relates to the field of high-precision positioning technology, and particularly relates to a performance evaluation method and device for satellite-based augmentation navigation. Background Art

[0002] Nowadays, major global navigation satellite systems (GNSS) have been vigorously developing their respective satellite-based augmentation services. Those that already provide satellite-based augmentation services include the Beidou Precise Point Positioning Service PPP-B2b, the High Accuracy Service HAS of Galileo, and the Wide Area Augmentation Service MADOCA-PPP of QZSS. 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] Currently, the positioning performance evaluation of satellite-based augmentation services of global navigation satellite systems refers to the traditional basic navigation service performance evaluation method, that is, selecting the measured data of satellite tracking stations in the service area, using enhanced orbit and clock offset products for real-time precise positioning, and statistically evaluating the positioning error. However, this method faces the following problems for the positioning performance evaluation of satellite-based augmentation positioning services: The PPP-B2b, HAS, and MADOCA-PPP augmentation services only cover some regions of the world, and it is impossible to evenly select tracking stations in the specified service area for positioning performance evaluation. There are even no measured stations available at the service area boundary. Therefore, the positioning performance evaluation results cannot comprehensively and objectively reflect the actual capabilities of the augmentation services.

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

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

[0006] In the first aspect of the present application, a method for performance evaluation of satellite-based augmentation navigation is provided. The method includes: obtaining the regional scope of the area to be evaluated, and performing a grid point division operation on the area to be evaluated according to the regional scope. The grid point division operation is used to divide the area to be evaluated into multiple sampling grid points; obtaining the augmentation information data and broadcast ephemeris data of the target satellite, and calculating the augmentation orbit error and augmentation clock error of the target satellite according to the augmentation information data and broadcast ephemeris data; using the augmentation orbit error, augmentation clock error of the target satellite, and the sampling grid point positions as inputs, and respectively calculating multiple groups of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model. One sampling grid point corresponds to one group of 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; sending the convergence time and positioning accuracy as performance evaluation results to the terminal device.

[0007] Optionally, obtaining the regional scope of the area to be evaluated, and performing a grid point division operation on the area to be evaluated according to the regional scope specifically includes: obtaining the initial longitude interval and the initial latitude interval; performing a grid point division operation through the initial longitude interval and the initial latitude interval, and according to the regional scope.

[0008] Optionally, after performing a grid point division operation through the initial longitude interval and the initial latitude interval, and according to the regional scope, the method further includes: dynamically adjusting the division of multiple sampling grid points according to the following formula:

[0009]

[0010] wherein, B0 is the initial longitude interval, L 0,0 is the initial latitude interval, α is the longitude and latitude 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 performing the i-th grid point division operation, L i,0 is the initial latitude interval after performing the i-th grid point division operation, dB i-1 is the longitude resolution after performing the (i - 1)-th grid point division operation, dL i-1 is the latitude resolution after performing the (i - 1)-th grid point division operation.

[0011] Optionally, calculating the augmentation orbit error and augmentation clock error of the target satellite specifically includes: obtaining the augmentation orbit data and the reference orbit data, and obtaining the augmentation orbit error by calculating the difference between the augmentation orbit data and the reference orbit data; obtaining the augmentation clock data and the reference clock data, and obtaining the augmentation clock error by calculating the difference between the augmentation clock data and the reference clock data.

[0012] Optionally, before calculating multiple sets of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model with the enhanced orbit error, enhanced clock error, and sampling grid point position of the target satellite as inputs, a precise positioning model needs to be constructed, specifically including: constructing a simulated observation equation for the ionosphere-free combination through the following formula, and constructing the precise positioning model through the simulated observation equation for the ionosphere-free combination:

[0013]

[0014] where r is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the cosine of the satellite-to-ground direction, 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, i.e., where ΔO s is the enhanced orbit error, ΔC s is the enhanced 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, is the ambiguity simulation parameter of the ionosphere-free combination.

[0015] Optionally, calculating multiple sets of positioning errors of the target satellite at multiple sampling grid points through the precise positioning model specifically includes: calculating the state estimation values of the sampling grid points of the target satellite at multiple sampling grid points through the precise positioning model, where the state estimation values of the sampling grid points include position error estimation values, tropospheric error estimation values, ambiguity estimation values, and receiver clock error estimation values; obtaining the actual values of the sampling grid point states, and taking the error between the actual values of the sampling grid point states and the state estimation values of the sampling grid points as the positioning error.

[0016] Optionally, obtaining the convergence time when the convergence condition is met specifically includes: calculating the convergence time when the convergence condition is met according to the positioning error sequence, specifically including: obtaining the first time point corresponding to the calculation of the initial positioning error, where the initial positioning error is the first positioning error calculated by the precise positioning model in the positioning error sequence; obtaining the second time point corresponding to the calculation of the target positioning error, where the target positioning error is the first positioning error that meets the preset positioning accuracy requirement in the positioning error sequence; 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 augmentation navigation is provided. The device includes an acquisition module and a processing module. Among them,

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

[0019] The processing module is configured to use the augmentation orbit error, augmentation clock error of the target satellite, and the sampling grid point position as inputs, and respectively calculate multiple groups of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model. 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; send the convergence time and positioning accuracy as performance evaluation results to the terminal device.

[0020] In a 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 the method as described in any one of the above.

[0021] In a fourth aspect of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to perform the method as described in any one of the above.

[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 regional scope of the area to be evaluated and performing a grid point division operation, the area to be evaluated is divided into multiple sampling grid points. Obtain the augmentation information data and broadcast ephemeris data of the target satellite, and calculate the augmentation orbit error and augmentation clock error. Use the augmentation orbit error, augmentation clock error of the target satellite, and the sampling grid point position as inputs, and through a precise positioning model, calculate multiple groups of positioning errors at multiple sampling grid points, 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; send the convergence time and positioning accuracy as performance evaluation results to the terminal device, thereby ensuring that independent positioning error calculations can be performed for each sampling point by dividing the entire area to be evaluated into grid points, and further realizing a comprehensive and objective performance evaluation of satellite-based augmentation navigation.

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

[0025] 3. The sampling grid point state estimated values of the target satellite at multiple sampling grid points are calculated respectively through a precise positioning model, the actual values of the sampling grid point states are obtained, and the error between the actual values of the sampling grid point states and the estimated values of the sampling grid point states is used as the positioning error, so as to effectively identify and quantify the orbit and clock biases in the augmentation service, provide a data basis for the performance evaluation of the subsequent precise positioning model, and improve the evaluation accuracy and reliability of the precise positioning model. Description of the Drawings

[0026] Figure 1 is a schematic flowchart of a method for evaluating the performance of satellite-based augmentation navigation provided by an embodiment of the present application;

[0027] Figure 2 is a schematic block diagram of a device for evaluating the performance of satellite-based augmentation navigation provided by an embodiment of the present application;

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

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

[0030] In order to enable those skilled in the art 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 accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than 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 limit the present application. As used in the specification of the present application, the singular forms "a", "one kind", "the", "above-mentioned", "this" and "this one" are also intended to include the plural forms, unless there is a clear indication to the contrary in the context. It should also be understood that the term " / and / " used in the present application refers to and includes any or all possible combinations of one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and should not be construed as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

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

[0034] Nowadays, major GNSSs have been vigorously developing their respective space-based augmentation services. The space-based augmentation services that have been provided include the Beidou Precise Point Positioning Service PPP-B2b, the High Accuracy Service HAS of Galileo, and the Wide Area Augmentation Service MADOCA-PPP of QZSS. Evaluating the positioning performance of space-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 positioning performance evaluation of the space-based augmentation services of current global satellite navigation systems refers to the traditional basic navigation service performance evaluation method, that is, selecting the measured data of satellite tracking stations in the service area, using the enhanced orbit and clock offset products for real-time precise positioning, and statistically evaluating the positioning error. However, this method faces the following problems for the positioning performance evaluation of space-based augmentation positioning services: The PPP-B2b, HAS, and MADOCA-PPP augmentation services only cover some regions of the world, and it is impossible to evenly select tracking stations in the specified service area for positioning performance evaluation. In the case where there are even no measured stations available at the service area boundary, the positioning performance evaluation results cannot comprehensively and objectively reflect the actual capabilities of the augmentation services.

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

[0037] Please refer to Figure 1 , which shows a schematic flowchart of a performance evaluation method for space-based augmentation navigation provided by an embodiment of the present application. The flowchart mainly includes the following steps: S101 to S104.

[0038] Step S101, obtain the regional scope of the area to be evaluated, and perform a grid point division operation on the area to be evaluated according to the regional scope. The grid point division operation is used to divide the area to be evaluated into multiple sampling grid points.

[0039] Specifically, when conducting high-precision positioning performance tests for GNSS, first, the operation of dividing grid points is performed on the area to be evaluated using variable resolution. At this time, the area range corresponding to the area to be evaluated is obtained, and the operation of dividing grid points is performed on the area to be evaluated 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 manner, step S101 further includes: obtaining an initial longitude interval, an initial latitude interval, and a longitude-latitude resolution ratio coefficient; performing the operation of dividing grid points through the initial longitude interval, the initial latitude interval, and the longitude-latitude resolution ratio coefficient, and according to the area range.

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

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

[0043]

[0044] where B0 is the initial longitude interval, L 0,0 is the initial latitude interval, α is the longitude-latitude resolution ratio coefficient, and α = dB 0 / dL0, i is the order of performing the operation of dividing grid points from low latitude to high latitude, B i is the initial longitude interval after the i-th operation of dividing grid points, L i,0 is the initial latitude interval after the i-th operation of dividing grid points, dB i-1 is the longitude resolution after the (i - 1)-th operation of dividing grid points, dL i-1 is the latitude resolution after the (i - 1)-th operation of dividing grid points.

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

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

[0047] Specifically, obtain the augmentation information data and broadcast ephemeris data of the target satellite. The augmentation information data and broadcast ephemeris data can be obtained through the satellite signal receiver terminal device or through the Internet network. In this embodiment, it is assumed that the augmentation information data and the precise orbit and clock products of a third party can be obtained. Only in this way can the errors of the augmentation orbit and clock be calculated to realize the simulation of real-time precise positioning, and the precise orbit and clock products of a third party can be obtained from the public network addresses of iGMAS, IGS official websites, data centers, and analysis centers.

[0048] In a possible implementation manner, step S102 further includes: obtaining the augmentation orbit data and reference orbit data, and obtaining the augmentation orbit error by calculating the difference between the augmentation orbit data and the reference orbit data; obtaining the augmentation clock data and reference clock data, and obtaining the augmentation clock error by calculating the difference between the augmentation clock data and the reference clock data.

[0049] Specifically, obtain the augmentation orbit data and reference orbit data, where the reference orbit data is the orbit information provided based on a high-precision orbit model or historical data, usually the data calculated precisely or provided by a ground base station. These data can be set according to the designed orbit, predicted orbit, or real-time monitoring information of the satellite; obtain the augmentation clock data and reference clock data, where the reference clock data is the clock difference information provided based on a high-precision time standard or a ground base station, usually the precisely calculated time deviation, which can be set according to the clock calibration record, historical data, or real-time monitoring information of the satellite. Then, calculate the augmentation orbit error and augmentation clock error through the following formula:

[0050]

[0051] where, ΔO s is the augmentation orbit error, that is, the difference between the augmentation orbit data and the reference orbit data ΔC s is the augmentation clock error, that is, the difference between the augmentation clock data and the reference clock data the mutual difference between

[0052] Step S103: Using the enhanced orbit error and enhanced clock error of the target satellite as inputs, calculate multiple groups of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model, with one sampling grid point corresponding to one group of positioning errors.

[0053] Specifically, use the enhanced orbit error and enhanced clock error as inputs to the precise positioning model and perform parameter allocation operations. The specific steps of the parameter allocation operation are as follows: During the positioning process, continuously monitor the changes in the enhanced orbit error and enhanced clock error, dynamically adjust the error estimation value according to the latest enhanced information data and broadcast ephemeris data, and use a suitable adaptive algorithm to update the enhanced orbit error and enhanced clock error. Set different weights according to the influence degrees of the enhanced orbit error and enhanced clock error on the positioning result respectively. The weight values of the enhanced orbit error and enhanced clock error can be determined through historical data analysis or experience-based methods. Output the corrected positioning parameters according to the results calculated from the weighted errors. These parameters will be used for subsequent positioning calculations to improve the positioning accuracy. The simulated observation equation of the ionosphere-free combination can be constructed through the following formula, and the precise positioning model can be constructed through the simulated observation equation of the ionosphere-free combination:

[0054]

[0055] where r is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the geocentric 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 enhanced clock error in the geocentric direction, that is where ΔO s is the enhanced orbit error, ΔC s is the enhanced 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, is the ambiguity simulation parameter of the ionosphere-free combination.

[0056] Specifically, taking the single-group positioning error as an example, 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 through 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 adopted, and the normal equation is obtained by superimposing all the simulated observation equations, and then the floating-point solution can be solved to obtain the state estimation value of the sampling grid points. After that, the above calculation process is repeated to obtain multiple groups of positioning errors. Among them, the state estimation value of the sampling grid points includes, but is not limited to, the position error estimation value, the tropospheric error estimation value, the ambiguity estimation value, and the receiver clock error estimation value, etc. At the same time, the actual value of the sampling grid point state is obtained, and the actual value of the sampling grid point state can be obtained through, and the error between the actual value of the sampling grid point state and the state estimation value of the sampling grid point is used as the positioning error.

[0057] Step S104: Construct a positioning error sequence from 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.

[0058] Specifically, a positioning error sequence is constructed from 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 manner, step S104 further includes: obtaining the first time point corresponding to the calculation of the initial positioning error, where the initial positioning error is the first positioning error calculated by the precise positioning model in the positioning error sequence; obtaining the second time point corresponding to the calculation of the target positioning error, where the target positioning error is the first positioning error that meets the preset positioning accuracy requirement in the positioning error sequence; and taking 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 the start of the calculation of the first set of positioning errors. Then, when calculating each set of positioning errors, after the calculation is completed, determine whether the positioning error meets the preset positioning accuracy requirement. The preset positioning requirement can be set according to the actual needs of positioning performance evaluation. For example, obtain multiple sets of positioning errors to form an error sequence within a period of time, calculate the 95% quantile of the error sequence, and determine whether this quantile is less than or equal to the positioning accuracy requirement. Obtain the positioning error when the preset positioning accuracy requirement is first met, and the second time point corresponding to the completion of the calculation of this positioning error. 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 acquisition conditions of the convergence time can be restricted more strictly. For example, after obtaining the positioning error when the preset positioning accuracy requirement is first met, determine whether the calculation of the positioning error continuously meets the positioning accuracy requirement within the preset time period. If it continuously meets the positioning accuracy requirement, then take the sum of the time interval between the second time point and the first time point and the preset time period as the convergence time; if it does not continuously meet the positioning accuracy requirement, re-define the first set of positioning errors and re-obtain the convergence time until the 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, send the convergence time and the positioning accuracy as the performance evaluation result to the terminal device.

[0062] Send the convergence time and the positioning accuracy as the performance evaluation result to the terminal device to complete the performance evaluation operation of the target satellite-based augmentation navigation.

[0063] By adopting the above method, this application obtains the regional range of the area to be evaluated, performs grid point division operation, and divides the area to be evaluated into multiple sampling grid points. Obtain the augmentation information data and broadcast ephemeris data of the target satellite, and calculate the augmentation orbit error and augmentation clock error. Using the augmentation orbit error, augmentation clock error of the target satellite, and the sampling grid point positions as inputs, through the precise positioning model, calculate multiple sets of positioning errors at multiple sampling grid points, construct a positioning error sequence through multiple sets of positioning errors, and calculate the convergence time and positioning accuracy when meeting the convergence conditions according to the positioning error sequence; send the convergence time and the positioning accuracy as the performance evaluation result to the terminal device, thereby ensuring that independent positioning error calculations can be performed for each sampling point by dividing the entire area to be evaluated into grid points, and further realizing a comprehensive and objective performance evaluation of satellite-based augmentation navigation.

[0064] Please refer to Figure 2, which shows a schematic diagram of modules of a performance evaluation device for satellite-based augmentation navigation provided by an embodiment of the present application. The device includes an acquisition module 21 and a processing module 22, where,

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

[0066] The processing module 22 is configured to use the augmentation orbit error, augmentation clock error of the target satellite, and the sampling grid point positions as inputs, and respectively calculate multiple groups of positioning errors of the target satellite at multiple sampling grid points through a precise positioning model. 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; send the convergence time and positioning accuracy as performance evaluation results to the terminal device.

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

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

[0069]

[0070] where, B0 is the initial longitude interval, L 0,0 is the initial latitude interval, α is the longitude and latitude 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 - 1)-th grid point division operation, dL i-1 is the latitude resolution after the (i - 1)-th grid point division operation.

[0071] In a 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 difference between the enhanced orbit data and the reference orbit data; acquiring enhanced clock error data and reference clock error data, and obtaining the enhanced clock error by calculating the difference between the enhanced clock error data and the reference clock error data.

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

[0073]

[0074] where r is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the cosine of the satellite-to-ground direction, 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 enhanced clock error in the satellite-to-ground direction, that is where ΔO s is the enhanced orbit error, ΔC s is the enhanced 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, is the ambiguity simulation parameter of 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 through the precise positioning model, specifically including: calculating the sampling grid point state estimation values of the target satellite at multiple sampling grid points through the precise positioning model, and the sampling grid point state estimation values include position error estimation values, tropospheric error estimation values, ambiguity estimation values, and receiver clock error estimation values; obtaining the actual values of the sampling grid point state, and taking the error between the actual values of the sampling grid point state and the sampling grid point state estimation values as the positioning error.

[0076] In a possible implementation, the processing module 22 is configured to calculate the convergence time when the convergence condition is met according to the positioning error sequence, specifically including: obtaining a first time point corresponding to the calculation start positioning error, where the start positioning error is the first positioning error in the positioning error sequence that is calculated by the precise positioning model; obtaining a second time point corresponding to the calculation target positioning error, where the target positioning error is 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.

[0077] It should be noted that: when the device provided in the above embodiment realizes its functions, only the division of the above function modules is used for illustration. In actual applications, the above functions can be allocated to different function modules according to needs, that is, the internal structure of the device is divided into different function 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 can be seen in the method embodiment, which will not be elaborated here.

[0078] This application also provides an electronic device. Refer to Figure 3 , Figure 3 which is a schematic structural diagram of an electronic device provided in an embodiment of this 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] Among them, the communication bus 302 is used to realize the connection and communication between these components.

[0080] Among them, the user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0081] Among them, the network interface 304 may optionally include a standard wired interface and 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 connects various parts within the entire server using various interfaces and lines. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by invoking the data stored in the memory 305, it performs various functions of the server and processes data. Optionally, the processor 301 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 301 may integrate a combination of one or more of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately by a single chip.

[0083] Among them, the memory 305 may include random access memory (RAM) and may also include 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, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store the data involved in the above-mentioned various method embodiments. Optionally, the memory 305 may also be at least one storage device located far from the aforementioned processor 301. Refer to Figure 3 , as a computer storage medium, the memory 305 may include an operating system, a network communication module, a user interface module, and a performance evaluation application for satellite-based augmentation navigation.

[0084] In Figure 3In the electronic device shown, the user interface 303 is mainly used to provide an interface for the user to input data and obtain the data input by the user. The processor 301 can be used to call the performance evaluation application program for satellite-based augmentation navigation stored in the memory 305. When executed by one or more processors 301, the electronic device is caused to execute one or more of the methods as described in the above embodiments. It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences 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 essential to this application.

[0085] This application also provides a computer-readable storage medium storing instructions. When executed by one or more processors, the electronic device is caused to execute one or more of the methods as described in the above embodiments.

[0086] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0087] In several implementation manners provided by this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there can be other division methods. For example, 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 displayed or discussed mutual coupling or direct coupling or communication connection can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

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

[0089] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0090] When 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 this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned memory includes various media that can store program codes, such as USB flash drives, mobile hard disks, magnetic disks, or optical discs.

[0091] The above are only exemplary embodiments disclosed in this application and should not be used to limit the scope of the disclosure of this application. That is, any equivalent changes and modifications made in accordance with the teachings of this application disclosure still fall within the scope covered by this application disclosure. Those skilled in the art will readily think of other implementation schemes of this application disclosure after considering the specification and the disclosure of the practical truth.

[0092] This application aims to cover any variations, uses, or adaptive changes of this application disclosure that follow the general principles of this application disclosure and include common general knowledge or conventional technical means in the technical field not recorded in this application disclosure.

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, specifically comprising: 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 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; 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; wherein building the precise positioning model specifically includes: 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: ； in, is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the star-to-earth direction cosine, is the position error simulation parameter, 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, ,in, is the enhanced orbit error, is the enhanced clock error, is the clock difference of the terminal device, is the tropospheric delay of the slant path, is the pseudorange hardware delay simulation parameter of the target satellite, is the wavelength of the ionosphere-free combination, are the ambiguity simulation parameters of the ionospheric-free combination.

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: ； in, is the initial longitude interval, is the initial latitude interval, is the latitude and longitude resolution scale factor, and , is the order of performing the grid point division operation from low latitude to high latitude, To conduct the The initial longitude interval after the grid point division operation, To conduct the The initial latitude interval after the grid point division operation, To conduct the The longitude resolution after the grid point division operation is as follows: To conduct the The latitude resolution after the above grid point division operation.

4. 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.

5. The method according to claim 1, characterized in that The calculating, according to the positioning error sequence, a 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.

6. 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, specifically including: acquiring enhanced orbit data and reference orbit data, and acquiring the enhanced orbit error by calculating the mutual difference between the enhanced orbit data and the reference orbit data; acquiring enhanced clock error data and reference clock error data, and acquiring the enhanced clock error by calculating the mutual difference between the enhanced clock error data and the reference clock error 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 respectively 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 a 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; send the convergence time and positioning accuracy as a performance evaluation result to the terminal device; wherein, constructing the precise positioning model specifically includes: 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: ； in, is the sampling grid point, is the pseudorange of the target satellite, is the residual of the ionosphere-free combination, is the star-to-earth direction cosine, is the position error simulation parameter, 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, ,in, is the enhanced orbit error, is the enhanced clock error, is the clock difference of the terminal equipment, is the tropospheric delay of the oblique path, is the pseudorange hardware delay simulation parameter of the target satellite, is the wavelength of the ionosphere-free combination, are the ambiguity simulation parameters of the ionospheric-free combination.

7. 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 as described in any one of claims 1 to 5.

8. 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 5 is performed.

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