A method and system for acquiring real-time GNSS ionospheric information based on forecast variance

Abstract

This invention proposes a method and system for acquiring real-time ionospheric information using GNSS based on forecast variance, relating to the field of GNSS positioning technology. The method includes: acquiring real-time ionospheric data from multiple different analysis centers and preprocessing it to obtain corresponding spherical harmonic coefficients; converting the spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point using a spherical harmonic function, correcting the total electron content at different puncture points using solar position information to obtain corrected electron content data, and converting the corrected electron content data into global VTEC grid data; using the electron content forecast information released by the European Orbit Determination Centre as the true value and the global VTEC grid data as the observed value, calculating the data weight value for each analysis center; and weighting and fusing the global VTEC grid data corresponding to each analysis center using the data weight value to obtain the target ionospheric electron total quantity information.

Description

Technical Field

[0001] This invention relates to the field of GNSS positioning technology, and in particular to a method and system for acquiring real-time GNSS ionospheric information based on prediction variance. Background Technology

[0002] Currently, Global Navigation Satellite System (GNSS) is increasingly widely used, and high-precision positioning services have become an indispensable support for many fields, such as transportation, geological exploration, weather forecasting, and aerospace. However, GNSS positioning accuracy is constrained by a variety of factors, among which the irregular variations of free electrons in the ionosphere (60-1000 km above the Earth's surface) are a key influencing factor. As a special region in the Earth's atmosphere, the ionosphere's free electrons cause refraction and scattering effects on GNSS signals, altering the signal propagation path and generating ionospheric delay errors. The magnitude of these delay errors is closely related to the total electron content (TEC) of the ionosphere; changes in TEC directly affect the propagation time of GNSS signals, thus significantly impacting positioning results. Therefore, accurately acquiring ionospheric information, especially real-time ionospheric products, is crucial for improving GNSS positioning accuracy.

[0003] However, current data broadcasting primarily relies on single-organization data transmission. If a single organization experiences a data transmission failure, such as equipment damage, network outage, or data processing errors, the entire service will be interrupted, making it impossible to guarantee continuous product supply. Furthermore, calculating satellite penetration points and projection coefficients involves complex mathematical operations and extensive data processing, placing high demands on computer computing power. This not only increases hardware costs but also limits the large-scale deployment and application of the system, failing to meet the growing user demand. Summary of the Invention

[0004] In view of this, the present invention proposes a method and system for acquiring real-time GNSS ionospheric information based on forecast variance.

[0005] The technical solution of this invention is implemented as follows: The first aspect of this invention provides a method for acquiring real-time GNSS ionospheric information based on prediction variance, comprising:

[0006] Real-time ionospheric data from multiple different analysis centers were acquired and preprocessed to obtain the corresponding spherical harmonic coefficients; the spherical harmonic coefficients include band harmonic coefficients, sector harmonic coefficients, and field harmonic coefficients.

[0007] The spherical harmonic coefficients are converted into the total electron content at the corresponding ionospheric puncture point using spherical harmonic functions. The total electron content at different puncture points is then corrected using solar position information to obtain corrected electron content data. This corrected electron content data is then converted into global VTEC grid data. The global VTEC grid data includes a uniform grid matrix that records the vertical total electron content values ​​for global regions.

[0008] Using the electron content forecast information released by the European Orbit Determination Centre as the true value and the global VTEC grid data as the observed value, the root mean square error of the electron content data of each of the analysis centers at the current time is calculated, and the data weight value of each analysis center is determined based on the reciprocal of the root mean square error.

[0009] The global VTEC grid data corresponding to each of the analysis centers is weighted and fused using the data weight values ​​to obtain the total amount of electrons in the target ionosphere.

[0010] Based on the above technical solutions, preferably, the step of acquiring real-time ionospheric data from multiple different analysis centers and performing preprocessing to obtain the corresponding spherical harmonic coefficients includes:

[0011] When converting the system time of each of the analysis centers to GPS time, time alignment and uniform time resolution are performed.

[0012] The real-time ionospheric data of the analysis center currently in operation is acquired, formatted, and decoded to obtain the corresponding spherical harmonic coefficients.

[0013] Based on the above technical solutions, preferably, the step of converting the spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point using a spherical harmonic function, correcting the total electron content at different puncture points by combining solar position information, obtaining corrected electron content data, and converting the corrected electron content data into global VTEC grid data includes:

[0014] The spherical harmonic coefficients of different analysis centers are converted into the total electron content at the corresponding ionospheric puncture point using spherical harmonic functions. The total electron content at different puncture points is then corrected by combining solar position information to obtain corrected electron content data.

[0015] The corrected electron content data is converted into global VTEC grid data, and the global VTEC grid data corresponding to each analysis center is determined.

[0016] Based on the above technical solutions, preferably, the step of using the electron content forecast information released by the European Orbit Determination Centre as the true value and the global VTEC grid data as the observed value to calculate the root mean square error of the electron content data of each of the analysis centers at the current time includes:

[0017] The root mean square error of each analysis center at the preset grid point is determined based on the first total electron content of each analysis center at the preset grid point and the second total electron content of the corresponding grid point in the electron content prediction information; the preset grid point is any grid point in the global VTEC grid.

[0018] The root mean square errors of each grid point are processed together to determine the total root mean square error of the electron content data at the current moment for each analysis center.

[0019] Based on the above technical solutions, preferably, the analysis center includes at least a first analysis center and a second analysis center; the step of weighting and fusing the global VTEC grid data corresponding to each analysis center using the data weight values ​​to obtain the target ionospheric electron total information includes:

[0020] The total electron content at the preset grid points is weighted based on the first data weight value corresponding to the first analysis center to obtain the first total electron component.

[0021] The total electron content at the preset grid points is weighted based on the second data weight value corresponding to the second analysis center to obtain the second total electron component; the sum of the first data weight value and the second data weight value is 1.

[0022] The sum of the first total electron component and the second total electron component is determined as the total electron quantity at the preset grid point.

[0023] Based on the above technical solutions, preferably, the step of weighting and fusing the global VTEC grid data corresponding to each of the analysis centers using the data weight values ​​to obtain the target ionospheric electron total information further includes:

[0024] Identify currently active and valid analysis centers;

[0025] The global VTEC grid data corresponding to each of the effective analysis centers are fused with equal weights to obtain the total amount of electrons in the target ionosphere.

[0026] Based on the above technical solutions, preferably, after obtaining the total amount of electrons in the target ionosphere, the method further includes:

[0027] The total electron quantity information of the target ionosphere is mapped to the latitude and longitude grid corresponding to each of the analysis centers, and the format is standardized to generate a standard IONEX file.

[0028] More preferably, a second aspect of the present invention provides a GNSS real-time ionospheric information acquisition system based on forecast variance, comprising: a coefficient acquisition module, a data conversion module, a weight determination module, and a weighted fusion module; wherein,

[0029] The coefficient acquisition module is configured to acquire real-time ionospheric data from multiple different analysis centers and preprocess the data to obtain the corresponding spherical harmonic coefficients; the spherical harmonic coefficients include band harmonic coefficients, sector harmonic coefficients, and field harmonic coefficients.

[0030] The data conversion module is configured to use a spherical harmonic function to convert the spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point, and to correct the total electron content at different puncture points by combining solar position information to obtain corrected electron content data. The corrected electron content data is then converted into global VTEC grid data. The global VTEC grid data includes a uniform grid matrix that records the vertical total electron content values ​​of global regions.

[0031] The weight determination module is configured to use the electron content forecast information released by the European Orbit Determination Centre as the true value, the global VTEC grid data as the observed value, calculate the root mean square error of the electron content data of each analysis center at the current time, and determine the data weight value of each analysis center based on the reciprocal of the root mean square error.

[0032] The weighted fusion module is configured to perform weighted fusion of the global VTEC grid data corresponding to each of the analysis centers using the data weight values ​​to obtain the total amount of electrons in the target ionosphere.

[0033] More preferably, a third aspect of the present invention provides an electronic device, including a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the GNSS real-time ionospheric information acquisition method based on prediction variance described in the first aspect.

[0034] More preferably, a fourth aspect of the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the GNSS real-time ionospheric information acquisition method based on prediction variance described in the first aspect.

[0035] The GNSS real-time ionospheric information acquisition method and system based on prediction variance of the present invention have the following advantages over the prior art:

[0036] 1. By integrating real-time ionospheric data from multiple analysis centers, ionospheric electron totality information is generated. Even if one analysis center experiences data transmission failure, equipment problems, or network interruptions, data from other analysis centers can continue to participate in the integrated processing. This effectively avoids service interruptions caused by problems in a single institution, greatly improving the continuity and stability of ionospheric product supply. After converting the spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point using spherical harmonic functions, the total electron content at different puncture points is corrected by combining solar position information to obtain corrected electron content data. This more accurately reflects the actual electron content of the ionosphere at different locations, reducing errors caused by not considering the influence of solar activity and improving data accuracy. Weights are calculated based on true values ​​and actual observation data to objectively reflect the quality and accuracy of data from each analysis center, effectively integrating the advantageous data from each center and further improving the accuracy of the target ionospheric electron totality information.

[0037] 2. By converting the data into spherical harmonic coefficients and using spherical harmonic functions for related calculations, the process avoids large amounts of complex data storage and computation. Furthermore, the calculation method based on spherical harmonic functions is relatively mature and stable, and the calculation process is relatively simple, reducing the requirements for computer computing power. This facilitates large-scale deployment and application of the system and can meet the growing user demands.

[0038] 3. The corrected electron content data, enhanced with solar position information, is converted into global VTEC grid data, presenting the global ionospheric electron content distribution in an intuitive and unified manner for easy user access and use. Ionospheric information from different regions and times can be quickly queried and analyzed through the grid matrix, providing standardized data support for applications such as GNSS positioning, ionospheric research, and space weather monitoring worldwide. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A flowchart illustrating a method for acquiring real-time GNSS ionospheric information based on prediction variance, provided in an embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram of the weight calculation results provided in an embodiment of the present invention;

[0042] Figure 3A schematic diagram of the root mean square error of different ionospheric information acquisition methods on a certain day provided in an embodiment of the present invention;

[0043] Figure 4 A schematic diagram of the structure of a GNSS real-time ionospheric information acquisition system based on prediction variance provided in an embodiment of the present invention;

[0044] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0045] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0046] In some embodiments, such as Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for acquiring real-time GNSS ionospheric information based on prediction variance, provided by an embodiment of the present invention. The method includes:

[0047] S110: Acquire real-time ionospheric data from multiple different analysis centers and preprocess them to obtain the corresponding spherical harmonic coefficients; the spherical harmonic coefficients include band harmonic coefficients, sector harmonic coefficients and field harmonic coefficients.

[0048] The basis functions of the spherical harmonic function are orthogonalized Legendre polynomials, which construct a basic element from the power terms of the ionospheric TEC (Total Electron Content) according to a certain proportion. Unlike other basic fitting models, the basis functions of the spherical harmonic function can represent specific physical meanings. The specific formula for calculating the spherical harmonic function is as follows:

[0049] ;

[0050] In the formula, The geomagnetic latitude representing the ionospheric penetration point (IPP). The diurnal longitude representing the ionospheric puncture point. The geomagnetic longitude representing the puncture point. The geomagnetic longitude representing the sun. Universal time, representing the time of observation Describes the classical Legendre function of order m to the nth degree. The orthogonalization factor, This represents the maximum order of the spherical harmonic function. and Represents the spherical harmonic coefficients. Orthogonalization factor. The definition is as follows:

[0051] ;

[0052] ;

[0053] In the formula, The zeroth term of the spherical harmonic coefficients is represented by the Kronecker notation. The global average ionospheric TEC is generally expressed as MGEC (Mean Global Total Electron Content).

[0054] When the coefficients of the spherical harmonic function When the ionosphere's total electron content varies with latitude, this is called the band harmonic coefficient; when... When, it is called the sector harmonic coefficient, representing the difference in global ionospheric TEC by longitude; when When the spherical harmonic coefficient is denoted by the spherical harmonic coefficient, it represents the difference in global ionospheric TEC across different spherical grids. All terms in the spherical harmonic function coefficients (band harmonic coefficients, sector harmonic coefficients, and spherical harmonic coefficients) collectively describe the variation of the total global electron content at each grid point.

[0055] In some embodiments, real-time ionospheric data from multiple different analysis centers are acquired and preprocessed to obtain the corresponding spherical harmonic coefficients, including:

[0056] The system time of each analysis center is converted to GPS time, and time alignment and uniform time resolution are performed.

[0057] The system acquires real-time ionospheric data from the currently operational analysis center, performs format unification and decoding, and obtains the corresponding spherical harmonic coefficients.

[0058] In this embodiment, considering that the real-time ionospheric data is broadcast as GPS, it is necessary to convert all system times to GPS time. Furthermore, since the time resolutions of different institutions are not uniform, it is necessary to unify them. For example, by searching for the real-time ionospheric data stream information at the current moment, determining whether the search was successful, and setting a counter for the number of analysis centers, the time of each analysis center is converted to a five-minute interval. After unification, the number of institutions participating in the comprehensive analysis at the current moment is output.

[0059] In one example, BNC software is used to receive, decode, and store real-time ionospheric data from different ionospheric analysis centers. These centers may include CAS (Chinese Academy of Sciences), WHU (Wuhan University), CNES (Centre National d'Études Spatiales), and UPC (Universitat Politècnica de Catalunya). CNES uses 12th-order spherical harmonic coefficients for ionospheric modeling, while CAS and WHU use 15th-order spherical harmonic coefficients. UPC uses a simplified three-dimensional tomographic model for ionospheric modeling. The first line of information for real-time ionospheric data may include data type, time (year, month, day, hour, minute, second), mount point, and an information update interval indicator (time resolution of the data stream). The second line of data records provides four parameters: the number of compressed layers in the ionospheric thin layer (1 layer), the maximum spherical harmonic waviness and the maximum order of the spherical harmonics (12*12 order), and the assumed height of the ionospheric thin layer (450km). The remaining data blocks contain the specific spherical harmonic coefficients.

[0060] S120 uses spherical harmonic functions to convert spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point. Combined with solar position information, the total electron content at different puncture points is corrected to obtain corrected electron content data. The corrected electron content data is then converted into global VTEC grid data. Global VTEC grid data includes a uniform grid matrix that records the vertical total electron content values ​​for global regions.

[0061] In some embodiments, the spherical harmonic coefficients are converted into the total electron content at the corresponding ionospheric puncture point using a spherical harmonic function. The total electron content at different puncture points is then corrected using solar position information to obtain corrected electron content data. This corrected electron content data is then converted into global VTEC grid data, including:

[0062] By using spherical harmonic functions, the spherical harmonic coefficients of different analysis centers are converted into the total electron content at the corresponding ionospheric puncture point. Combined with solar position information, the total electron content at different puncture points is corrected to obtain corrected electron content data.

[0063] The corrected electron content data were converted into global VTEC grid data, and the global VTEC grid data corresponding to each analysis center was determined.

[0064] The maximum TEC value typically occurs around 14:00 local time, at which time t=50400s. Furthermore, the longitude of the IPP rotates around the Earth's polar axis. Therefore, it's necessary to compensate for the strong correlation between VTEC (Vertical Total Electron Content) and the sun's position. The correspondence between the sun's position and the puncture point is considered as follows:

[0065] ;

[0066] In the formula, The longitude of the puncture point in the ionosphere. To take into account the solar fixed longitude of the ionospheric puncture point behind the sun's position, The calculated GPS time (in seconds).

[0067] S130 uses the electron content forecast information released by the European Orbit Determination Centre as the true value and the global VTEC grid data as the observed value to calculate the root mean square error of the electron content data at the current time of each analysis center, and determines the data weight value of each analysis center based on the reciprocal of the root mean square error.

[0068] The one-day forecast products released by CODE (Center for Orbit Determination in Europe) are in the standard IONEX format and directly provide the global VTEC grid.

[0069] In some embodiments, electron content forecasts published by the European Orbit Determination Centre are used as true values, and global VTEC grid data are used as observed values. The root mean square error of the electron content data at the current time for each analysis centre is calculated, including:

[0070] The root mean square error of each analysis center at the current time at the preset grid point is determined based on the first total electron content and the second total electron content of the corresponding grid point in the electron content forecast information of each analysis center at the preset grid point; the preset grid point is any grid point in the global VTEC grid.

[0071] The root mean square error of each grid point is processed to determine the total root mean square error of the electron content data at the current moment for each analysis center.

[0072] For example, using the one-day ionospheric forecast product broadcast in advance by CODE, the root mean square error (RMS) of the RT-GIM (Real-Time Global Ionospheric Map) for CAS, WHU, UPC, and CNES is calculated hourly, and its reciprocal is used to assign weights for real-time calculation. Each analysis center... With real-time weights The calculation method is shown in the following formula:

[0073] ;

[0074] In the formula, This represents the total number of grid points in the GIM at the corresponding time. This represents the number of analysis centers participating in the calculation at that moment. Representing different analysis centers, For GIM VTEC value at each grid point

[0075] and The real-time ionospheric products from each analysis center and the ionospheric forecast products from CODE are respectively... The TEC value at each grid point represents the first total electron content and the second total electron content.

[0076] S140 uses data weight values ​​to weight and fuse the global VTEC grid data corresponding to each analysis center to obtain information on the total amount of electrons in the target ionosphere.

[0077] In some embodiments, the analysis center includes at least a first analysis center and a second analysis center; the global VTEC grid data corresponding to each analysis center are weighted and fused using data weight values ​​to obtain information on the total amount of electrons in the target ionosphere, including:

[0078] The total electron content at preset grid points is weighted based on the first data weight value corresponding to the first analysis center to obtain the first total electron component.

[0079] The total electron content at the preset grid points is weighted based on the second data weight value corresponding to the second analysis center to obtain the second total electron component; the sum of the first data weight value and the second data weight value is 1.

[0080] The sum of the first total electron component and the second total electron component is determined as the total electron quantity at the preset grid point.

[0081] In some embodiments, the global VTEC grid data corresponding to each analysis center is weighted and fused using data weight values ​​to obtain information on the total amount of electrons in the target ionosphere, and the method further includes:

[0082] Identify currently active and valid analysis centers;

[0083] By equally weighting and fusing the global VTEC grid data corresponding to each effective analysis center, information on the total amount of electrons in the target ionosphere can be obtained.

[0084] In one example, see Figure 2 , Figure 2 This is a schematic diagram of the weight calculation results provided in an embodiment of the present invention; the data collection time is from 01:00 to 23:00 on February 13, 2024. The vertical axis represents the weight, and the horizontal axis represents the GPS time, in hours. Due to data interruption issues at some analysis centers, only the data that can be received is used for aggregation. If an analysis center has no data at the aggregation time, its weight is 0. The calculation formula is shown below:

[0085] ;

[0086] In the formula, This represents the number of analysis centers participating in the calculation at that moment. and The two methods are equal-weighted synthesis and real-time weighted synthesis, respectively. The TEC value at each grid point These are the real-time weights calculated using different methods.

[0087] In some embodiments, after obtaining the total number of electrons in the target ionosphere, the method further includes:

[0088] The total electron quantity information of the target ionosphere is mapped to the latitude and longitude grid corresponding to each analysis center, and the format is standardized to generate a standard IONEX file.

[0089] In this embodiment, a 2.5°*5° geographic grid is created according to the file format, and the calculated global VTEC information is mapped to its respective latitude and longitude grid. The VTEC is then written into the file according to the IONEX standard format.

[0090] In one optional embodiment, the feasibility of this method is analyzed using different accuracy indicators, primarily selecting three: root mean square error, mean deviation, and standard deviation. The calculation methods for these three accuracy indicators are as follows:

[0091] ;

[0092] In the formula, This represents the total number of grid points in the GIM at the corresponding time. For real-time ionospheric products synthesized using three different methods ( , and ), The post-production products released for CODE in the first TEC value at each grid point.

[0093] Taking root mean square error as an example, the RMS result calculated from root mean square error is as follows: Figure 3As shown, the data includes RMS data from 01:00 to 23:00 on November 26, 2024. The vertical axis represents RMS and the horizontal axis represents time, with the unit being hours. It can be seen that the GNSS real-time ionospheric information acquisition method based on forecast variance proposed in this application has a significant improvement in accuracy compared to the integrated products of various institutions, and the data integrity rate has been increased to 100%.

[0094] In one example, the accuracy of RT-GIMs from different institutions and the RT-GIM synthesized in this application was statistically analyzed in the E, N, and U directions under three levels of geomagnetic activity. The results are shown in Table 1.

[0095] Table 1. SF-SPP accuracy statistics of RT-GIM in the E, N, and U directions for various institutions.

[0096]

[0097] It can be seen that the RT-GIM integrated in this application has a better effect on single-frequency SPP positioning. The reason why CNES is slightly better than this application is that the data integrity rate is low and the data is often interrupted when there is geomagnetic interference.

[0098] The results of single-frequency PPP calculation are shown in Table 2.

[0099] Table 2. Statistical analysis of SF-PPP accuracy of RT-GIM in the E, N, and U directions for various institutions.

[0100]

[0101] As can be seen from Table 2, the GNSS real-time ionospheric information acquisition method based on forecast variance provided in this application greatly improves the solution accuracy of single-frequency PPP.

[0102] In some embodiments, please refer to Figure 4 , Figure 4 This is a schematic diagram of a GNSS real-time ionospheric information acquisition system based on prediction variance, provided in an embodiment of the present invention. The present invention provides a GNSS real-time ionospheric information acquisition system 500 based on prediction variance, comprising: a coefficient acquisition module 510, a data conversion module 520, a weight determination module 530, and a weighted fusion module 540; wherein,

[0103] The coefficient acquisition module 510 is configured to acquire real-time ionospheric data from multiple different analysis centers and preprocess the data to obtain the corresponding spherical harmonic coefficients; the spherical harmonic coefficients include band harmonic coefficients, sector harmonic coefficients and field harmonic coefficients.

[0104] The data conversion module 520 is configured to use spherical harmonic functions to convert spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point, and to correct the total electron content at different puncture points by combining solar position information to obtain corrected electron content data. The corrected electron content data is then converted into global VTEC grid data. The global VTEC grid data includes a uniform grid matrix that records the vertical total electron content values ​​of global regions.

[0105] The weight determination module 530 is configured to use the electron content forecast information released by the European Orbit Determination Centre as the true value and the global VTEC grid data as the observed value to calculate the root mean square error of the electron content data of each analysis center at the current time, and determine the data weight value of each analysis center based on the reciprocal of the root mean square error.

[0106] The weighted fusion module 540 is configured to perform weighted fusion of global VTEC grid data corresponding to each analysis center through data weight values ​​to obtain the total amount of electrons in the target ionosphere.

[0107] In some embodiments, the coefficient acquisition module 510 is specifically configured as follows:

[0108] The system time of each analysis center is converted to GPS time, and time alignment and uniform time resolution are performed.

[0109] The system acquires real-time ionospheric data from the currently operational analysis center, performs format unification and decoding, and obtains the corresponding spherical harmonic coefficients.

[0110] In some embodiments, the data conversion module 520 is specifically configured as follows:

[0111] By using spherical harmonic functions, the spherical harmonic coefficients of different analysis centers are converted into the total electron content at the corresponding ionospheric puncture point. Combined with solar position information, the total electron content at different puncture points is corrected to obtain corrected electron content data.

[0112] The corrected electron content data were converted into global VTEC grid data, and the global VTEC grid data corresponding to each analysis center was determined.

[0113] In some embodiments, the weight determination module 530 is specifically configured as follows:

[0114] The root mean square error of each analysis center at the current time at the preset grid point is determined based on the first total electron content and the second total electron content of the corresponding grid point in the electron content forecast information of each analysis center at the preset grid point; the preset grid point is any grid point in the global VTEC grid.

[0115] The root mean square error of each grid point is processed to determine the total root mean square error of the electron content data at the current moment for each analysis center.

[0116] In some embodiments, the analysis center includes at least a first analysis center and a second analysis center; the weighted fusion module 540 is specifically configured as follows:

[0117] The total electron content at preset grid points is weighted based on the first data weight value corresponding to the first analysis center to obtain the first total electron component.

[0118] The total electron content at the preset grid points is weighted based on the second data weight value corresponding to the second analysis center to obtain the second total electron component; the sum of the first data weight value and the second data weight value is 1.

[0119] The sum of the first total electron component and the second total electron component is determined as the total electron quantity at the preset grid point.

[0120] In some embodiments, the weighted fusion module 540 is further configured as follows:

[0121] Identify currently active and valid analysis centers;

[0122] By equally weighting and fusing the global VTEC grid data corresponding to each effective analysis center, information on the total amount of electrons in the target ionosphere can be obtained.

[0123] In some embodiments, the GNSS real-time ionospheric information acquisition system based on prediction variance further includes a mapping generation module; the mapping generation module is specifically configured as follows:

[0124] The total electron quantity information of the target ionosphere is mapped to the latitude and longitude grid corresponding to each analysis center, and the format is standardized to generate a standard IONEX file.

[0125] It should be noted that the GNSS real-time ionospheric information acquisition system based on prediction variance provided in this application embodiment and the GNSS real-time ionospheric information acquisition method based on prediction variance provided in this application embodiment are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned GNSS real-time ionospheric information acquisition method based on prediction variance, and the repeated parts will not be described again.

[0126] In some embodiments, please refer to Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 600 provided in this application includes a processor 610 and a memory 620; the memory 620 stores a computer program, wherein the computer program, when executed by the processor, implements the aforementioned method for acquiring real-time GNSS ionospheric information based on prediction variance.

[0127] Specifically, processor 610 may include, for example, a general-purpose microprocessor, an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. Processor 610 may also include onboard memory for caching purposes. Processor 610 may be a single processing unit or multiple processing units for performing different actions of the method flow according to embodiments of this application.

[0128] Memory 620 may be any medium capable of containing, storing, transmitting, propagating, or transmitting instructions. For example, memory 620 may include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, instruments, or propagation media. Specific examples of memory 620 include: magnetic storage devices such as magnetic tape or hard disk drives (HDDs); optical storage devices such as optical discs (CD-ROMs); and may also be random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0129] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, this program implements the aforementioned method for acquiring real-time GNSS ionospheric information based on prediction variance. This computer-readable medium may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into that device / apparatus / system. The aforementioned computer-readable medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0130] According to embodiments of this application, a computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wired, optical fiber, radio frequency signals, etc., or any suitable combination thereof.

[0131] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application. Therefore, the scope of this application should not be limited to the above embodiments, but should be defined not only by the appended claims, but also by their equivalents. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the protection scope of this invention.

Claims

1. A method for acquiring real-time GNSS ionospheric information based on forecast variance, characterized in that, include: Real-time ionospheric data from multiple different analysis centers were acquired and preprocessed to obtain the corresponding spherical harmonic coefficients; The spherical harmonic coefficients include band harmonic coefficients, sector harmonic coefficients, and field harmonic coefficients; The spherical harmonic coefficients are converted into the total electron content at the corresponding ionospheric puncture point using spherical harmonic functions. The total electron content at different puncture points is then corrected using solar position information to obtain corrected electron content data. This corrected electron content data is then converted into global VTEC grid data. The global VTEC grid data includes a uniform grid matrix that records the vertical total electron content values ​​for global regions. Using the electron content forecast information released by the European Orbit Determination Centre as the true value and the global VTEC grid data as the observed value, the root mean square error of the electron content data of each of the analysis centers at the current time is calculated, and the data weight value of each analysis center is determined based on the reciprocal of the root mean square error. The global VTEC grid data corresponding to each of the analysis centers is weighted and fused using the data weight values ​​to obtain the total amount of electrons in the target ionosphere.

2. The method for acquiring real-time GNSS ionospheric information based on forecast variance as described in claim 1, characterized in that, The process of acquiring and preprocessing real-time ionospheric data from multiple different analysis centers to obtain the corresponding spherical harmonic coefficients includes: When converting the system time of each of the analysis centers to GPS time, time alignment and uniform time resolution are performed. The real-time ionospheric data of the analysis center currently in operation is acquired, formatted, and decoded to obtain the corresponding spherical harmonic coefficients.

3. The method for acquiring real-time GNSS ionospheric information based on forecast variance as described in claim 1, characterized in that, The process involves using spherical harmonic functions to convert the spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point, then correcting the total electron content at different puncture points using solar position information to obtain corrected electron content data. This corrected electron content data is then converted into global VTEC grid data, including: The spherical harmonic coefficients of different analysis centers are converted into the total electron content at the corresponding ionospheric puncture point using spherical harmonic functions. The total electron content at different puncture points is then corrected by combining solar position information to obtain corrected electron content data. The corrected electron content data is converted into global VTEC grid data, and the global VTEC grid data corresponding to each analysis center is determined.

4. The method for acquiring real-time GNSS ionospheric information based on forecast variance as described in claim 1, characterized in that, The step of using the electron content forecast information released by the European Centre for Orbit Determination as the true value and the global VTEC grid data as the observed value to calculate the root mean square error of the electron content data at the current time for each of the analysis centers includes: The root mean square error of each analysis center at the preset grid point is determined based on the first total electron content of each analysis center at the preset grid point and the second total electron content of the corresponding grid point in the electron content prediction information; the preset grid point is any grid point in the global VTEC grid. The root mean square errors of each grid point are processed together to determine the total root mean square error of the electron content data at the current moment for each analysis center.

5. The method for acquiring real-time GNSS ionospheric information based on prediction variance as described in claim 4, characterized in that, The analysis centers include at least a first analysis center and a second analysis center; the step of weighting and fusing the global VTEC grid data corresponding to each analysis center using the data weight values ​​to obtain the target ionospheric electron total information includes: The total electron content at the preset grid points is weighted based on the first data weight value corresponding to the first analysis center to obtain the first total electron component. The total electron content at the preset grid points is weighted based on the second data weight value corresponding to the second analysis center to obtain the second total electron component; the sum of the first data weight value and the second data weight value is 1. The sum of the first total electron component and the second total electron component is determined as the total electron quantity at the preset grid point.

6. The method for acquiring real-time GNSS ionospheric information based on forecast variance as described in claim 1, characterized in that, The step of weighting and fusing the global VTEC grid data corresponding to each of the analysis centers using the data weight values ​​to obtain the target ionospheric electron total information also includes: Identify currently active and valid analysis centers; The global VTEC grid data corresponding to each of the effective analysis centers are fused with equal weights to obtain the total amount of electrons in the target ionosphere.

7. The method for acquiring real-time GNSS ionospheric information based on forecast variance as described in claim 1, characterized in that, After obtaining the total number of electrons in the target ionosphere, the method further includes: The total electron quantity information of the target ionosphere is mapped to the latitude and longitude grid corresponding to each of the analysis centers, and the format is standardized to generate a standard IONEX file.

8. A GNSS real-time ionospheric information acquisition system based on forecast variance, characterized in that, include: The module comprises a coefficient acquisition module, a data transformation module, a weight determination module, and a weighted fusion module; among which, The coefficient acquisition module is configured to acquire real-time ionospheric data from multiple different analysis centers and preprocess the data to obtain the corresponding spherical harmonic coefficients; the spherical harmonic coefficients include band harmonic coefficients, sector harmonic coefficients, and field harmonic coefficients. The data conversion module is configured to use a spherical harmonic function to convert the spherical harmonic coefficients into the total electron content at the corresponding ionospheric puncture point, and to correct the total electron content at different puncture points by combining solar position information to obtain corrected electron content data. The corrected electron content data is then converted into global VTEC grid data. The global VTEC grid data includes a uniform grid matrix that records the vertical total electron content values ​​of global regions. The weight determination module is configured to use the electron content forecast information released by the European Orbit Determination Centre as the true value, the global VTEC grid data as the observed value, calculate the root mean square error of the electron content data of each analysis center at the current time, and determine the data weight value of each analysis center based on the reciprocal of the root mean square error. The weighted fusion module is configured to perform weighted fusion of the global VTEC grid data corresponding to each of the analysis centers using the data weight values ​​to obtain the total amount of electrons in the target ionosphere.

9. An electronic device comprising a processor and a memory; said memory storing a computer program, wherein, When the computer program is executed by the processor, it implements the method for acquiring real-time GNSS ionospheric information based on forecast variance as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, It stores a computer program, wherein when the computer program is executed by a processor, it implements the method for acquiring real-time GNSS ionospheric information based on prediction variance as described in any one of claims 1 to 7.

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