A method, system, device, medium, and product for ionospheric modeling based on detection data.

Abstract

The application discloses a method, system, device, medium and product for ionospheric modeling based on detection data, relates to the field of electromagnetic wave transmission and ionospheric modeling, and comprises the following steps: acquiring GNOS-II detection data of different dates according to a space environment, and screening effective rays based on the correction degree of electron density of the detection data; acquiring grid points through by the effective rays based on a space-based ionospheric inversion method according to corresponding data of the effective rays; determining total electron content of the space-based ionospheric inversion by using a dual-frequency calculation method according to the corresponding data of the effective rays; performing horizontal constraint and vertical constraint on global ionospheric electron density distribution by using a ground-based ionospheric inversion method according to the grid points through by the effective rays and the total electron content of the space-based ionospheric inversion; outputting the constrained global ionospheric electron density distribution to obtain a global ionospheric model. The application realizes real-time high-precision ionospheric construction in a global range.

Description

Technical Field

[0001] This application relates to the fields of electromagnetic wave transmission and ionospheric modeling, and in particular to a method, system, device, medium and product for ionospheric modeling based on detection data. Background Technology

[0002] During skywave transmission, the composition of the ionosphere affects the refraction, reflection, and attenuation of shortwave waves, significantly influencing their transmission trajectory. When natural disasters occur (earthquakes, volcanoes, tsunamis, etc.), the ionosphere's state undergoes abnormal changes. Therefore, real-time ionospheric imaging and state monitoring can quantify and correct the ionosphere's impact on communication systems in real time.

[0003] On September 6, 2017, a solar flare and subsequent ionospheric disturbance reportedly severely disrupted aircraft communications along Arctic routes. These space weather events caused HF (High Frequency) communication outages, forcing aircraft to avoid polar regions and take lower-latitude routes, resulting in increased flight time and fuel consumption. During several events between 2013 and 2016, as solar activity peaked, the ionosphere in polar regions was frequently disturbed, affecting communication on transpolar routes. During these disturbances, aircraft had to detour and use alternative communication methods, such as satellite communication. However, satellite communication is ineffective at high latitudes (above 82 degrees), increasing flight risks and delays. Similar phenomena were observed during the ionospheric storm of August 25-26, 2018, where HF radio communication was severely restricted in polar regions, forcing flights to replan their routes. Therefore, in-depth research into the structure and characteristics of the ionosphere, and combining ionospheric phenomena with communication phenomena, has significant scientific and practical implications for the development of near-Earth space communication, monitoring, and navigation systems.

[0004] Existing ionospheric detection methods are mainly divided into ground-based and space-based methods. Currently, ground-based GNSS (Global Navigation Satellite System) data remains the primary source of data for ionospheric inversion. However, since GNSS stations are mostly distributed in the Northern Hemisphere, with fewer stations in the Southern Hemisphere, oceans, and high-latitude regions, the accuracy of ionospheric modeling in these areas is relatively low. Applying space-based detection data to ionospheric modeling is currently the main development direction. In 2021, China launched the FY-3E satellite, filling a gap in global space-based meteorological detection systems. Subsequently, in 2023, the FY-3G satellite was launched. The GNSS Radio Occultation Sounder-II (GNOS-II) instrument on both satellites can provide detection data for ionospheric inversion modeling under different weather conditions. Traditional occultation detection data cannot obtain information on the spatial distribution of the ionosphere over a large area. Combining occultation detection data with ground-based GNSS detection data inversion methods can make up for the narrow coverage of traditional space-based ionospheric detection and realize real-time high-precision ionospheric construction on a global scale. Summary of the Invention

[0005] The purpose of this application is to provide an ionospheric modeling method, system, device, medium, and product based on probe data, so as to achieve real-time high-precision ionospheric construction on a global scale.

[0006] To achieve the above objectives, this application provides the following solution:

[0007] Firstly, this application provides an ionospheric modeling method based on probe data, including:

[0008] GNOS-II detection data for different dates are acquired based on the space environment. Based on the correction degree of electron density in the GNOS-II detection data, effective rays are selected and their corresponding data are saved. The space environment includes whether the sun is in a flare period, whether the target date is in a solar disturbance period, the geomagnetic index Dst value, and the solar activity index F10.7 value. The GNOS-II detection data includes ionospheric additional phase. The corresponding data includes the ionospheric additional phase of the two channels on GNOS-II, the position information of LEO satellites, and the position information of GNSS satellites.

[0009] Based on the first response data of the effective rays, the grid points through which the effective rays pass are obtained using the space-based ionospheric inversion method; wherein, the first response data includes the position information of LEO satellites and the position information of GNSS satellites;

[0010] Based on the second response data of the effective rays, the total electron content along the corresponding ray path of the space-based ionosphere inversion is determined using the dual-frequency calculation method; where the second response data is the additional ionospheric phase of the two channels on GNOS-II;

[0011] Based on the grid points through which the effective rays pass and the total electron content retrieved from the space-based ionosphere, the global ionospheric electron density distribution is subjected to horizontal and vertical constraints using the ground-based ionospheric inversion method, resulting in the constrained global ionospheric electron density distribution. The horizontal constraint is non-equal weight smoothing, and the vertical constraint is a Chapman function constraint.

[0012] The constrained global ionospheric electron density distribution is output to obtain the global ionospheric model.

[0013] Optionally, GNOS-II detection data from different dates are acquired based on the space environment, and effective radiation is screened based on the degree of correction to the electron density using the GNOS-II detection data, and the corresponding data of the effective radiation is saved. Specifically, this includes:

[0014] GNOS-II probe data were acquired on different dates based on the space environment;

[0015] The global ionosphere is divided and numbered according to three dimensions: latitude, longitude, and altitude, to obtain a global ionospheric grid model. The electron density at any point in each grid of the global ionospheric grid model is the electron density at the corresponding location in the international reference ionospheric model.

[0016] Calculate the ray collision height at the time of the occultation event based on the location information in the detection data, and calculate the corresponding ray equation;

[0017] Based on the initial electron density value, a multiplicative algebraic reconstruction iteration is performed to obtain the electron density after a single iteration. The difference between the electron density after a single iteration and the initial electron density value is calculated to determine the degree of correction of the electron density by each ray. The initial electron density value is the electron density at the corresponding position in the international reference ionospheric model.

[0018] Based on the detection data, the total electron content along the ray path is calculated using a dual-frequency calculation method;

[0019] Valid rays are selected based on whether the correction of electron density by the ray falls within a first set range and whether the total electron content along the ray path falls within a second set range, and the corresponding data of the valid rays are saved.

[0020] Optionally, based on the initial value of the electron density, a multiplicative algebraic reconstruction iteration is performed to obtain the electron density after a single iteration, specifically including:

[0021] Using formula Determine the electron density after a single iteration; where, Let be the electron density of the j-th pixel after the first iteration; Let y be the initial value of the electron density of the j-th pixel; i a is the total electron content along the i-th ray path; i Let be the i-th row vector of the intercept matrix A; γ is the relaxation factor for iteration; a ij Let be the j-th pixel value in the i-th row vector of the intercept matrix A.

[0022] Optionally, the difference between the electron density after a single iteration and the initial electron density value is calculated to determine the degree of correction of the electron density by each ray, specifically including:

[0023] The difference between the electron density after a single iteration and the initial electron density is calculated to obtain the correction value of each ray for each grid.

[0024] Determine the root mean square error of all non-zero correction values ​​to obtain the degree of correction for the electron density for each ray.

[0025] Optionally, based on the detection data, the total electron content along the ray path is calculated using a dual-frequency calculation method, specifically including:

[0026] Using formula Determine the total electron content along the ray path; where TEC is the total electron content along the ray path; C is the ionospheric constant; f1 is the detection frequency of the first channel; f2 is the detection frequency of the second channel; L1 is the ionospheric additional phase observation value of the first channel; L2 is the ionospheric additional phase observation value of the second channel.

[0027] Optionally, based on the grid points through which the effective rays pass and the total electron content retrieved from the space-based ionosphere, the global ionospheric electron density distribution is horizontally and vertically constrained using a ground-based ionospheric inversion method to obtain the constrained global ionospheric electron density distribution, specifically including:

[0028] Obtain the longitude, latitude, and altitude of the grid points through which the effective rays pass, and use the electron density at the corresponding location in the international reference ionospheric model as the average electron density of the grid corresponding to the grid points through which the effective rays pass;

[0029] The average electron density at the same height is smoothed by mean distribution to construct a trend surface;

[0030] Using the electron density at the corresponding position of the International Reference Ionospheric Model as the initial value of the electron density, and combining the intercept of the effective ray in the grid, a multiplicative algebraic reconstruction iteration is performed to obtain the iterated electron density;

[0031] The iterative electron density obtained from each ray is constrained by the height using the Chapman function;

[0032] Subtract the trend surface from the iterated electron density obtained from each ray, and perform non-weighted smoothing on the iterated electron density obtained from each ray based on whether there are effective rays passing through the grid.

[0033] Calculate the root mean square error between the total electron density obtained after iteration for each ray and the total electron content obtained from the inversion of the space-based ionosphere;

[0034] If the mean squared error is greater than the set mean squared error, continue iterating;

[0035] If the root mean square error is less than the set root mean square error, then the constrained global ionospheric electron density distribution is obtained.

[0036] Secondly, this application discloses an ionospheric modeling system based on probe data, comprising:

[0037] The data acquisition module is used to acquire GNOS-II detection data for different dates based on the space environment, and to filter effective rays and save the corresponding data of the effective rays based on the degree of correction of electron density in the GNOS-II detection data. The space environment includes whether the sun is in a solar flare period, whether the target date is in a solar disturbance period, the geomagnetic index Dst value, and the solar activity index F10.7 value. The GNOS-II detection data includes the ionospheric additional phase. The corresponding data includes the ionospheric additional phase of the two channels on GNOS-II, the position information of LEO satellites, and the position information of GNSS satellites.

[0038] The space-based inversion module is used to obtain the grid points through which the effective rays pass, based on the first response data of the effective rays and the space-based ionospheric inversion method; wherein, the first response data includes the position information of LEO satellites and the position information of GNSS satellites;

[0039] The total electron content calculation module is used to determine the total electron content on the corresponding ray path of the space-based ionosphere inversion based on the second corresponding data of the effective rays using a dual-frequency calculation method; wherein, the second corresponding data is the additional ionospheric phase of the two channels on GNOS-II;

[0040] The constraint module is used to apply horizontal and vertical constraints to the global ionospheric electron density distribution based on the grid points through which the effective rays pass and the total electron content retrieved from the space-based ionosphere, using the ground-based ionosphere inversion method, to obtain the constrained global ionospheric electron density distribution; the horizontal constraint is non-equal weight smoothing; the vertical constraint is a Chapman function constraint.

[0041] The modeling module is used to output the constrained global ionospheric electron density distribution to obtain a global ionospheric model.

[0042] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the ionospheric modeling method based on probe data as described above.

[0043] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the ionospheric modeling method based on probe data described above.

[0044] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the ionospheric modeling method based on probe data described above.

[0045] According to the specific embodiments provided in this application, this application has the following technical effects:

[0046] This application provides a method, system, device, medium, and product for ionospheric modeling based on probe data. It acquires GNOS-II probe data from different dates based on the space environment and filters effective rays based on the correction degree of electron density in the probe data. Based on the corresponding data of the effective rays, it obtains the grid points traversed by the effective rays using a space-based ionospheric inversion method. Based on the corresponding data of the effective rays, it determines the total electron content along the corresponding ray path in the space-based ionospheric inversion using a dual-frequency calculation method. Based on the grid points traversed by the effective rays and the total electron content in the space-based ionospheric inversion, it applies horizontal and vertical constraints to the global ionospheric electron density distribution using a ground-based ionospheric inversion method, outputting the constrained global ionospheric electron density distribution to obtain a global ionospheric model. This application obtains the additional phase of the GNOS-II ionosphere and, based on ground-based ionospheric inversion methods and space-based occultation inversion methods, obtains global ionospheric models under different space conditions and at different altitudes, realizing real-time, high-precision ionospheric construction on a global scale. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1A flowchart illustrating an ionospheric modeling method based on probe data, provided as an embodiment of this application;

[0049] Figure 2 A framework diagram of the ionospheric modeling method based on probe data provided in this application;

[0050] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0052] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] In one exemplary embodiment, such as Figure 1 and Figure 2 As shown, an ionospheric modeling method based on probe data is provided, including the following steps:

[0054] S1: Obtain GNOS-II detection data for different dates based on the space environment, and filter effective rays based on the correction degree of electron density in the GNOS-II detection data, and save the corresponding data of the effective rays; the space environment includes whether the sun is in a solar flare period, whether the target date is in a solar disturbance period, the geomagnetic index Dst value, and the solar activity index F10.7 value; the GNOS-II detection data includes the ionospheric additional phase; the corresponding data includes the ionospheric additional phase of the two channels on GNOS-II, the position information of LEO satellites, and the position information of GNSS satellites.

[0055] As an optional implementation, S1 specifically includes:

[0056] S11: Acquire GNOS-II detection data for different dates based on the space environment. In practical applications, additional ionospheric phase data measured by the GNOS-II instrument aboard the Fengyun satellite on different dates are selected according to different space environments.

[0057] S12: The global ionosphere is divided and numbered according to three dimensions: latitude, longitude, and altitude, to obtain a global ionospheric grid model. The electron density at any point in each grid of the global ionospheric grid model is the electron density at the corresponding location in the international reference ionospheric model.

[0058] In practical applications, the global ionosphere is divided and numbered according to three dimensions: latitude, longitude, and altitude. The number of grids in each of the three dimensions is set to a small number, and the electron density of the international reference ionospheric model at a point in each grid is read.

[0059] S13: Calculate the ray collision height at the time of the occultation event based on the location information in the detection data, and calculate the corresponding ray equation.

[0060] S14: Based on the initial value of electron density, perform a multiplicative algebraic reconstruction iteration to obtain the electron density after a single iteration, and perform a difference operation between the electron density after a single iteration and the initial value of electron density to calculate the degree of correction of electron density by each ray; the initial value of electron density is the electron density at the corresponding position of the international reference ionosphere model.

[0061] As an optional implementation, based on the initial value of the electron density, a multiplicative algebraic reconstruction iteration is performed to obtain the electron density after a single iteration, specifically including:

[0062] Using formula Determine the electron density after a single iteration; where, Let be the electron density of the j-th pixel after the first iteration; Let y be the initial value of the electron density of the j-th pixel; i a is the total electron content along the i-th ray path; i Let be the i-th row vector of the intercept matrix A; γ is the relaxation factor for iteration; a ij Let be the j-th pixel value in the i-th row vector of the intercept matrix A.

[0063] As an optional implementation, the difference between the electron density after a single iteration and the initial electron density value is calculated to determine the degree of correction of the electron density by each ray, specifically including:

[0064] The difference between the electron density after a single iteration and the initial electron density is calculated to obtain the correction value of each ray for each grid.

[0065] Determine the root mean square error of all non-zero correction values ​​to obtain the degree of correction for the electron density for each ray.

[0066] In practical applications, this step first requires simultaneously solving the equations of the corresponding two latitude surfaces, two longitude surfaces, and two altitude surfaces for each grid with the ray equation. By determining whether the intersection points are within the grid, the number of intersection points within the grid is obtained. If the number of intersection points within the same grid is 2, the intra-grid intercept is calculated; otherwise, the intra-grid intercept is 0. All intra-grid intercepts are arranged according to grid number to form an intercept matrix A.

[0067] Using the electron density of the international reference ionospheric model obtained in step S12 as the initial value, a multiplicative algebraic reconstruction iterative operation is performed. The multiplicative algebraic reconstruction iterative algorithm is based on the initial value of the electron density, and the correction formula in the k-th iteration is as follows:

[0068]

[0069] In the formula, It is the value of the j-th pixel at the k-th iteration, a i Let be the i-th row vector of the intercept matrix A, and γ be the relaxation factor for the iteration, 0 < γ < 1. Each iteration corresponds to one STEC measurement, and the STEC of the initial measurement is the value obtained from the observation data.

[0070] This step performs only one multiplication iteration to calculate the correction value of each ray for each grid. The mean square error is calculated for all non-zero Δ values. The mean square error represents the degree of correction that each ray makes to the electron density.

[0071] S15: Based on the detection data, the total electron content along the ray path is calculated using a dual-frequency calculation method.

[0072] As an optional implementation, S15 specifically includes:

[0073] Using formula Determine the total electron content along the ray path; where TEC is the total electron content along the ray path; C is the ionospheric constant, C = 40.3082 (m 3 s -2 f1 is the detection frequency of the first channel; f2 is the detection frequency of the second channel; f1 and f2 are 1575.42MHz and 1227.60MHz, respectively. L1 is the additional phase observation value of the ionosphere in the first channel; L2 is the additional phase observation value of the ionosphere in the second channel.

[0074] S16: Select effective rays based on whether the correction degree of the radiation to the electron density is within the first set range and whether the total electron content on the radiation path is within the second set range, and save the corresponding data of the effective rays.

[0075] S2: Based on the first response data of the effective rays, obtain the grid points through which the effective rays pass using the space-based ionospheric inversion method; wherein, the first response data includes the position information of LEO satellites and the position information of GNSS satellites.

[0076] In this embodiment, the ionospheric grid is divided as follows: the inverted ionospheric height ranges from 100km to 1000km, the latitude distribution is from -90° to 90°, and the longitude distribution is from -180° to 180°.

[0077] In this embodiment, the grid boundary is as follows: each grid has six faces, namely the upper and lower latitude faces, the front and back altitude faces, and the left and right longitude faces, and the coordinate system is the geocentric coordinate system.

[0078] S3: Based on the second corresponding data of the effective rays, the total electron content on the corresponding ray path of the space-based ionosphere inversion is determined using the dual-frequency calculation method; where the second corresponding data is the additional ionospheric phase of the two channels on GNOS-II.

[0079] S4: Based on the grid points through which the effective rays pass and the total electron content retrieved from the space-based ionosphere, the global ionospheric electron density distribution is subjected to horizontal and vertical constraints using the ground-based ionospheric inversion method, resulting in the constrained global ionospheric electron density distribution; the horizontal constraint is non-equal weight smoothing; the vertical constraint is a chapman function constraint.

[0080] As an optional implementation, S4 specifically includes:

[0081] S41: Obtain the longitude, latitude, and altitude of the grid points through which the effective rays pass, and use the electron density at the corresponding location in the international reference ionospheric model as the average electron density of the grid corresponding to the grid points through which the effective rays pass; smooth the average electron density at the same altitude to construct a trend surface.

[0082] In practical applications, the latitude and longitude of a point within the grid are obtained using the grid scheme defined in step S2, and the electron density of that point is obtained through the international reference ionosphere as the average electron density within the grid.

[0083] S42: Using the electron density at the corresponding position of the International Reference Ionospheric Model as the initial value of the electron density, and combining it with the intercept of the effective ray in the grid, perform multiplicative algebraic reconstruction iteration to obtain the iterated electron density.

[0084] Using the international reference ionospheric electron density as the initial value, and combining the ray intercepts within the grid, a multiplicative algebraic reconstruction iterative calculation is performed.

[0085] S43: The iterative electron density obtained from each ray is constrained by the Chapman function according to the height. The vertical profile of the electron density at any position under the Chapman function model is as follows:

[0086]

[0087] Where: x(h) is the electron density at height h; N m F2 is the peak density of the F2 layer; h m F2 is the peak height of the F2 layer; H1 is the scale height at the bottom of the ionosphere; H2 is the scale height at the top of the ionosphere.

[0088] S44: Subtract the trend surface from the iterated electron density obtained from each ray, and perform non-weighted smoothing on the iterated electron density obtained from each ray based on whether there are effective rays passing through the grid.

[0089] S45: Calculate the root mean square error between the total electron density obtained after iteration for each ray and the total electron content obtained from the space-based ionosphere inversion; if the root mean square error is greater than the set root mean square error, continue iterating; if the root mean square error is less than the set root mean square error, the constrained global ionospheric electron density distribution is obtained.

[0090] Calculate the root mean square error between the total electron content along the ray path calculated using the ground-based method and the total electron density calculated using the dual-frequency method in step S3. If the root mean square error is greater than a specified value, continue iterating; if the root mean square error is less than a specified value, output the result.

[0091] S5: Output the constrained global ionospheric electron density distribution to obtain the global ionospheric model.

[0092] This application uses ionospheric additional phase data obtained from the Global Navigation Satellite Occultation Detector-II (GNSS-3E and 3G satellites) and constructs a pixel-based ionospheric tomography model based on GNSS ground-based ionospheric inversion methods and space-based occultation inversion methods. It obtains the ionospheric variation patterns under different space environments based on detection data from different dates. It performs preliminary screening of the data from GNSS-3E and 3G satellites based on the degree of grid correction. This inversion method can obtain global ionospheric models under different space conditions and at different altitudes. The resulting accuracy model is higher than the international reference ionospheric model in high-latitude regions.

[0093] Based on the same inventive concept, this application also provides a data-based ionospheric modeling system for implementing the aforementioned data-based ionospheric modeling method. The solution provided by this system is similar to the implementation described in the above method. Therefore, the specific limitations in the data-based ionospheric modeling system embodiments provided below can be found in the limitations of the data-based ionospheric modeling method described above, and will not be repeated here.

[0094] In one exemplary embodiment, an ionospheric modeling system based on probe data is provided, comprising:

[0095] The data acquisition module is used to acquire GNOS-II detection data for different dates based on the space environment, and to filter effective rays and save the corresponding data of effective rays based on the degree of correction of electron density in the GNOS-II detection data. The space environment includes whether the sun is in a solar flare period, whether the target date is in a solar disturbance period, the geomagnetic index Dst value, and the solar activity index F10.7 value. The GNOS-II detection data includes the ionospheric additional phase. The corresponding data includes the ionospheric additional phase of the two channels on GNOS-II, the position information of LEO satellites, and the position information of GNSS satellites.

[0096] The space-based inversion module is used to obtain the grid points through which the effective rays pass, based on the first response data of the effective rays and the space-based ionospheric inversion method. The first response data includes the position information of LEO satellites and the position information of GNSS satellites.

[0097] The total electron content calculation module is used to determine the total electron content on the corresponding ray path of the space-based ionosphere inversion based on the second corresponding data of the effective rays using a dual-frequency calculation method; wherein, the second corresponding data is the additional ionospheric phase of the two channels on GNOS-II.

[0098] The constraint module is used to apply horizontal and vertical constraints to the global ionospheric electron density distribution based on the grid points through which the effective rays pass and the total electron content retrieved from the space-based ionosphere, using the ground-based ionosphere inversion method, to obtain the constrained global ionospheric electron density distribution; the horizontal constraint is non-equal weight smoothing; the vertical constraint is a Chapman function constraint.

[0099] The modeling module is used to output the constrained global ionospheric electron density distribution to obtain a global ionospheric model.

[0100] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described ionospheric modeling method based on probe data.

[0101] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the above-described ionospheric modeling method based on probe data.

[0102] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described ionospheric modeling method based on probe data.

[0103] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 3 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and databases. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media to run. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements an ionospheric modeling method based on probe data.

[0104] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0105] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0106] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0107] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0108] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0109] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method of ionospheric modeling based on sounding data, characterized in that, The method comprises the following steps: According to the space environment, GNOS-Ⅱ detection data of different dates is obtained, and effective rays are screened based on the correction degree of electron density of the GNOS-Ⅱ detection data, and the corresponding data of the effective rays is saved; the space environment comprises whether the sun belongs to a flare period, whether the target date is in a solar disturbance period, a geomagnetic index Dst value and a solar activity index F10.7 value; the GNOS-Ⅱ detection data comprises ionospheric additional phase; the corresponding data comprises ionospheric additional phase of two channels on GNOS-Ⅱ, position information of a LEO satellite and position information of a GNSS satellite; According to the first corresponding data of the effective rays, grid points through by the effective rays are obtained based on a space-based ionospheric inversion method; wherein the first corresponding data comprises position information of a LEO satellite and position information of a GNSS satellite; According to the second corresponding data of the effective rays, total electron content on a ray path corresponding to the space-based ionospheric inversion is determined by using a dual-frequency calculation method; wherein the second corresponding data is ionospheric additional phase of two channels on GNOS-Ⅱ; According to the grid points through by the effective rays and the total electron content of the space-based ionospheric inversion, global ionospheric electron density distribution is horizontally constrained and vertically constrained by using a ground-based ionospheric inversion method, to obtain constrained global ionospheric electron density distribution; the horizontal constraint is non-equivalent smoothing; the vertical constraint is chapman function constraint; The constrained global ionospheric electron density distribution is outputted to obtain a global ionospheric model.

2. The ionospheric modeling method based on sounding data according to claim 1, characterized in that, According to the space environment, GNOS-Ⅱ detection data of different dates is obtained, and effective rays are screened based on the correction degree of electron density of the GNOS-Ⅱ detection data, and the corresponding data of the effective rays is saved, specifically comprising: GNOS-Ⅱ detection data of different dates is obtained according to the space environment; Global ionosphere is divided and numbered according to latitude, longitude and height, to obtain a global ionospheric grid model, and electron density of any point in each grid of the global ionospheric grid model is electron density of a corresponding position of an international reference ionospheric model; Ray collision height when an occultation event occurs is calculated according to position information in the detection data, and a corresponding ray equation is calculated; According to an initial value of electron density, a multiplication algebraic reconstruction iteration is performed to obtain single-iteration electron density, and difference operation is performed between the single-iteration electron density and the initial value of electron density to calculate correction degree of electron density of each ray; the initial value of electron density is electron density of a corresponding position of an international reference ionospheric model; Based on the detection data, total electron content on a ray path is calculated by using a dual-frequency calculation method; Effective rays are screened according to whether the correction degree of electron density of the rays is located in a first set interval and whether the total electron content on the ray path is located in a second set interval, and the corresponding data of the effective rays is saved.

3. The ionospheric modeling method based on sounding data according to claim 2, characterized in that, According to the initial value of electron density, a multiplication algebraic reconstruction iteration is performed to obtain single-iteration electron density, specifically comprising: The electron density after a single iteration is determined using the formula wherein, is the electron density after the first iteration for the jth pixel; is the initial value of the electron density for the jth pixel; y i is the total electron content along the ith ray path; a i is the ith row vector of the intercept matrix A; γ is the relaxation factor for the iteration; a ij is the jth pixel value in the ith row vector of the intercept matrix A.

4. The ionospheric modeling method based on sounding data according to claim 2, characterized in that, The single-iteration electron density is subtracted from the initial electron density to calculate the correction degree of each ray on the electron density, specifically including: The single-iteration electron density is subtracted from the initial electron density to obtain the correction value of each ray on each grid; The mean square deviation of all non-zero correction values is determined to obtain the correction degree of each ray on the electron density.

5. The ionospheric modeling method based on sounding data according to claim 2, characterized in that, Based on the detection data, the total electron content on the ray path is calculated using a dual-frequency calculation method, specifically including: The total electron content on the ray path is determined using the formula TEC = C (f1f2) (L1L2) ; wherein TEC is the total electron content on the ray path; C is an ionospheric constant; f1 is a first channel probe frequency; f2 is a second channel probe frequency; L1 is a first channel ionospheric excess phase observation; and L2 is a second channel ionospheric excess phase observation.

6. The ionospheric modeling method based on sounding data according to claim 1, characterized in that, According to the grid points passed by the effective rays and the total electron content inverted by the space-based ionosphere, the global ionospheric electron density distribution is horizontally and vertically constrained using a ground-based ionosphere inversion method to obtain the constrained global ionospheric electron density distribution, specifically including: The longitude, latitude and altitude of the grid points passed by the effective rays are obtained, and the electron density at the corresponding position of the international reference ionosphere model is taken as the average electron density of the grid corresponding to the grid points passed by the effective rays; The average electron densities at the same altitude are mean value smoothed to construct a trend surface; The electron density at the corresponding position of the international reference ionosphere model is taken as the initial electron density, and the intercept of the effective ray in the grid is combined to perform multiplication algebraic reconstruction iteration to obtain the iteration electron density; The iteration electron density obtained by each ray is subjected to Chapman function constraint according to the height; The iteration electron density obtained by each ray is subtracted from the trend surface, and the iteration electron density obtained by each ray is subjected to non-equal weight smoothing according to whether there is an effective ray passing through the grid; The mean square deviation of the iteration electron density obtained by each ray and the total electron content inverted by the space-based ionosphere is calculated; If the mean square deviation is greater than the set mean square deviation, iteration is continued; If the mean square deviation is less than the set mean square deviation, the constrained global ionospheric electron density distribution is obtained.

7. An ionospheric modeling system based on probe data, characterized in that, It includes: A data acquisition module is configured to acquire GNOS-Ⅱ detection data of different dates according to a space environment, and filter effective rays based on the correction degree of electron density of the GNOS-Ⅱ detection data, and save corresponding data of the effective rays; the space environment includes whether the sun is in a flare period, whether the target date is in a solar disturbance period, a Dst value of a geomagnetic index, and an F10.7 value of a solar activity index; the GNOS-Ⅱ detection data includes ionospheric additional phase; the corresponding data includes ionospheric additional phase of two channels on GNOS-Ⅱ, position information of a LEO satellite, and position information of a GNSS satellite; A space-based inversion module is configured to acquire grid points passed by effective rays based on a space-based ionosphere inversion method according to first corresponding data of the effective rays; wherein the first corresponding data includes position information of a LEO satellite and position information of a GNSS satellite; A total electron content calculation module is configured to determine the total electron content on the ray path inverted by the space-based ionosphere according to second corresponding data of the effective rays using a dual-frequency calculation method; wherein the second corresponding data is ionospheric additional phase of two channels on GNOS-Ⅱ. The constraint module is configured to perform horizontal constraint and vertical constraint on the global ionospheric electron density distribution by using a ground-based ionospheric inversion method according to the grid points passed through by the effective rays and the total electron content inverted by the space-based ionospheric inversion method, to obtain the constrained global ionospheric electron density distribution; the horizontal constraint is non-equal-weight smoothing; and the vertical constraint is Chapman function constraint. The modeling module is configured to output the constrained global ionospheric electron density distribution, to obtain a global ionospheric model.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the ionospheric modeling method based on probe data according to any one of claims 1-6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the ionospheric modeling method based on probe data according to any one of claims 1-6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the ionospheric modeling method based on probe data according to any one of claims 1-6.

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