Method and system for constructing high-temporal-spatial-resolution ionosphere model for dense GNSS deformation observation station

Abstract

The invention discloses a method for constructing a high temporal-spatial resolution ionosphere model for a dense GNSS deformation observation station. The method comprises the following steps: collecting double-frequency observation data and broadcast ephemeris of a dense GNSS deformation monitoring station in a modeling area; calculating a multi-path effect, a cycle slip ratio and a data effective rate, and screening out data meeting quality requirements; respectively acquiring a satellite end DCB and a receiver end DCB; using the screened double-frequency observation data to calculate a non-geometric distance combination, and combining a satellite end DCB and a receiver end DCB to obtain an oblique path TEC; based on thin layer hypothesis, calculating a puncture point position of a satellite signal in a thin layer and a satellite elevation angle and an azimuth angle at the puncture point, and converting an oblique path TEC into a vertical TEC by using a projection function; and constructing a TEC grid model, and averaging the vertical TECs of all puncture points falling on each grid to obtain a TEC value and a system. According to the invention, calculation is carried out by using the data of the existing large-scale dense GNSS deformation network monitoring stations, and the value-added effect of the data is realized on the premise that the construction cost is not increased.

Description

Technical Field

[0001] The present invention belongs to the field of ionospheric modeling, and in particular relates to a method and system for constructing a high temporal and spatial resolution ionospheric model using densely packed GNSS deformation measuring stations. Background Art

[0002] The ionosphere is a key medium that influences satellite navigation, communication systems, and space environment monitoring. Accurate modeling of its spatiotemporal variations is crucial for high-precision applications. Traditional ionospheric modeling relies primarily on GNSS observation data provided by the Continuously Operating Reference Station (CORS) network. Based on these sparsely populated sites, traditional modeling methods (such as spherical harmonics modeling or polynomial fitting) can characterize the large-scale spatiotemporal distribution of ionospheric TEC. However, due to limitations in site density and data sampling rate, they struggle to resolve small- and medium-scale ionospheric structures, such as those at the hundred-meter to kilometer and minute to hour scales.

[0003] In recent years, with the surge in demand for geological disaster monitoring and urban safety warning, new data sources also face two major challenges: uneven data quality and the complexity of ultra-large-scale computing.

[0004] The terms involved in the description of the present invention are explained as follows: DCB: Differential Code Bias, differential code deviation; GNSS: Global Navigation Satellite System CORS: Continuous Operational Reference System, continuously operating reference station system; CMONOC: Crustal Movement Observation Network of China, China Tectonic Environment Monitoring Network; PPP: Precise Point Positioning, precise single point positioning; TEC: Total Electronic Content, total electronic content; VTEC / Vertical TEC: Vertical Total Electron Content, vertical total electron content; STEC / Slant Path TEC: Slant Total Electron Content, slant path total electron content. Summary of the Invention

[0005] In order to solve the problems that small and medium-scale ionospheric structures are difficult to analyze, and new data sources have uneven data quality and ultra-large-scale computational complexity, the present invention provides a method for constructing a high-temporal-space resolution ionospheric model using dense GNSS deformation monitoring stations. The method uses data from existing large-scale dense GNSS deformation network monitoring stations for calculation. The constructed high-temporal-space resolution ionospheric model can analyze small and medium-scale ionospheric structures while taking into account data quality and computational complexity. It achieves the value-added effect of data without increasing construction costs.

[0006] According to one aspect of the present invention, a method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations is provided, comprising: Collect dual-frequency observation data and broadcast ephemeris from dense GNSS deformation stations within the modeling area; Calculate the multipath effect, cycle slip ratio and data efficiency based on the collected data, and filter out data that meets the quality requirements; Obtain DCB on the satellite side and DCB on the receiver side respectively; The geometry-free distance combination is calculated using the selected dual-frequency observation data, and the slant path TEC is obtained by combining the DCB at the satellite end and the DCB at the receiver end. Based on the thin layer hypothesis, the penetration point of the satellite signal in the thin layer, the satellite elevation angle and azimuth at the penetration point are calculated, and the oblique path TEC is converted into vertical TEC using the projection function. A TEC grid model was constructed, and the vertical TEC values ​​of all puncture points falling on each grid were averaged to obtain the TEC value.

[0007] As a further technical solution, we calculate the multipath effect, cycle slip ratio, and data efficiency based on the collected data, and select data that meets the quality requirements, including: Delete observation arcs whose multipath effect is less than a first preset value, whose cycle slip ratio is less than a second preset value, or whose data efficiency is lower than a third preset value, and retain the undeleted data as data that meets the quality requirements.

[0008] As a further technical solution, obtaining the DCB on the satellite side and the DCB on the receiver side respectively includes: Download the Satellite DCB product and obtain Satellite DCB; The GNSS broadcast ephemeris and precise ephemeris are obtained, combined with the satellite-side DCB, and the receiver-side DCB of each GNSS deformation measuring station is estimated using the precise single point positioning method.

[0009] As a further technical solution, the strategy adopted when estimating the DCB at the receiver end of each GNSS deformation station using the precise single point positioning method is as follows: The satellite orbit, satellite clock error and satellite-side DCB are fixed, and non-differenced and non-combined observations are used. The Klobuchar model is used as the virtual ionospheric observation value, and the site coordinates, tropospheric delay and DCB are used as the parameters to be estimated.

[0010] As a further technical solution, the formula for the oblique path TEC is obtained as follows: STEC = P4 – DCBrec - DCBsat Among them, P4 represents the geometry-free distance combination, DCBrec represents the DCB at the receiver end, and DCBsat represents the satellite end receiver.

[0011] As a further technical solution, the projection function is used to convert the oblique path TEC into a vertical TEC: VTEC = STEC·cos(z') where (z') represents the zenith distance of the ionospheric single-layer model, STEC represents slant-path TEC, and VTEC represents vertical TEC.

[0012] As a further technical solution, the method further includes: For empty value grids where no puncture points fall, the values ​​of adjacent grids are used to fill them.

[0013] According to one aspect of the present invention, a system for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations is provided, comprising: The first main module is used to collect dual-frequency observation data and broadcast ephemeris of dense GNSS deformation stations within the modeling area; The second main module is used to calculate the multipath effect, cycle slip ratio and data efficiency based on the collected data, and filter out the data that meets the quality requirements; The third main module is used to obtain the DCB of the satellite end and the DCB of the receiver end respectively; The fourth main module is used to calculate the geometry-free distance combination using the filtered dual-frequency observation data, and combine the satellite-side DCB and the receiver-side DCB to obtain the slant path TEC; The fifth main module is used to calculate the penetration point position of the satellite signal in the thin layer, the satellite altitude angle and azimuth angle at the penetration point based on the thin layer hypothesis, and convert the oblique path TEC into vertical TEC using the projection function; The sixth main module is used to build a TEC grid model, taking the average of the vertical TEC of all puncture points falling on each grid to obtain the TEC value.

[0014] According to one aspect of the present invention, there is provided a device for constructing a high-temporal-space-resolution ionosphere model using dense GNSS deformation stations, comprising a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the method for constructing a high-temporal-space-resolution ionosphere model using dense GNSS deformation stations.

[0015] According to one aspect of the present invention, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the method for constructing a high-temporal-space resolution ionospheric model using densely packed GNSS deformation stations.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention overcomes the limitations of traditional modeling frameworks and provides a novel ionospheric modeling method that balances data quality control with optimized computational efficiency. It constructs an ionospheric model with high temporal and spatial resolution, avoiding the loss of small and medium-scale ionospheric structure. Furthermore, the invention utilizes data from an existing, large-scale, dense GNSS deformation network monitoring station for calculations, achieving data value-added without increasing construction costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction will be given below to the drawings used in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 A flowchart of a method for constructing a high-temporal-space resolution ionospheric model using dense GNSS deformation stations provided in an embodiment of the present invention.

[0019] Figure 2 Schematic diagram of the system structure for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] It should be noted that: The accelerated construction of dense GNSS deformation monitoring networks has provided an unprecedented data foundation for building high-temporal and spatial resolution ionospheric models. However, this new data source faces two major challenges: uneven data quality and extremely large-scale computational complexity. Therefore, there is an urgent need to overcome the limitations of traditional modeling frameworks and develop new ionospheric modeling methods that balance data quality control and computational efficiency.

[0021] Based on the above-mentioned situation, the present invention provides a method for constructing an ionospheric model with high temporal and spatial resolution. The method uses data from existing large-scale dense GNSS deformation network monitoring stations for calculation. The constructed ionospheric model with high temporal and spatial resolution can analyze the small and medium-scale ionospheric structure and achieve the value-added effect of data without increasing the construction cost.

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention are arbitrarily combined with each other to form a new technical solution. This combination is not restricted by the sequence of steps and / or structural composition mode, but must be based on the ability of ordinary technicians in this field to implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that this combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0023] The present invention provides a method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations. Figure 1 , including the following steps: Step 1. Collect dual-frequency observation data and broadcast ephemeris from densely populated GNSS stations within the modeling area. The observation data is the pseudorange and phase observation values ​​recorded by the receiver after the electromagnetic wave signal emitted by the satellite reaches the receiver.

[0024] Step 2. Perform a preliminary data quality analysis, with the main indicators being multipath effect, cycle slip ratio, and data efficiency. After the preliminary data quality analysis, delete low-quality arcs.

[0025] Specifically, preset values ​​are set for the multipath effect, cycle slip ratio, and data efficiency. If any of these indicators does not meet the preset values, the observation segment is considered to be of low quality and is deleted. The preset values ​​for the multipath effect, cycle slip ratio, and data efficiency can be set based on actual conditions or empirical values.

[0026] Step 3. Obtain GNSS broadcast ephemeris, precise ephemeris, and satellite DCB from online download products, and estimate the receiver DCB using the PPP method.

[0027] Step 4. Obtain the geometry-free range combination (P4 observation) by frequency difference calculation. Subtract the DCB of the receiver and satellite obtained in step 3 to obtain the slant path STEC.

[0028] Step 5. Based on the thin layer assumption, calculate the location (latitude and longitude) of the satellite signal's penetration point in the thin layer, as well as the satellite's altitude and azimuth at the penetration point. Use a projection function to convert STEC to vertical VTEC. Because the ionosphere is assumed to be a thin layer, the intersection of the satellite signal and the thin layer is the penetration point.

[0029] Step 6. Divide the modeling area into grids and eliminate the error by averaging the VTEC of all puncture points falling in each grid to obtain the TEC value.

[0030] Preferably, the method further comprises: Step 7. Grids without puncture points are treated as empty grids and filled with values ​​from adjacent grids.

[0031] As a preferred embodiment, the method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations provided in the embodiment of the present invention has the following specific process: (1) Collect dual-frequency observation data (L1 / L2 frequency) and broadcast ephemeris from densely populated GNSS stations across the country.

[0032] (2) Perform a preliminary quality analysis of the data and calculate the multipath effect, cycle slip ratio, and data efficiency. Based on the quality analysis results, remove observation arcs with significant multipath effect (less than 0.8), low cycle slip ratio (e.g., less than 200), or low data efficiency (less than 80%), and retain high-quality data for subsequent processing.

[0033] (3) Download satellite DCB products from the International GNSS Service (IGS) or other authoritative organizations to obtain the DCB value of the satellite. Obtain GNSS broadcast ephemeris and precise ephemeris from the products downloaded online, and use the precise point positioning (PPP) method to estimate the DCB of each GNSS station receiver (this technology is currently available). The strategy adopted is: fix the satellite orbit, satellite clock error, and satellite DCB, use non-differenced non-combined observations, use the Klobuchar model as the ionospheric virtual observation value, and use the station coordinates, tropospheric delay, and DCB as the parameters to be estimated.

[0034] (4) Calculate the geometry-free distance combination (P4 observation) using dual-frequency observation data:

[0035] in, and The phase-smoothed pseudorange observations at the L1 and L2 frequencies are obtained by deducting the DCB of the receiver and the DCB of the satellite from the geometry-free range combination to obtain the slant path total electron content (STEC): STEC = P4 – DCBrec - DCBsat (5) Based on the thin layer assumption, calculate the position (latitude and longitude) of the satellite signal's penetration point in the thin layer, the satellite altitude angle and azimuth at the penetration point. Use a projection function (such as the single-layer model projection function) to convert the oblique path STEC into the vertical direction VTEC: VTEC = STEC·cos(z') where (z') is the zenith distance of the ionosphere single-layer model.

[0036] (6) Construct a national TEC grid model: Draw a regular grid of points across the country (e.g., 0.5° × 0.5° resolution). For each grid, count the VTEC observations of all puncture points that fall within the grid, and take the average value as the TEC value of that grid point. Grids with no puncture points are considered null grids.

[0037] (7) Use the VTEC of the grids around the null grid (e.g., 100 km) to interpolate the null grid (e.g., using the inverse distance weighted method) to eliminate the null grid.

[0038] The implementation of each embodiment of the present invention is based on programmed processing performed by a device with processor functionality. Therefore, in practical engineering, the technical solutions and functions of each embodiment of the present invention are encapsulated into various modules. Based on this reality, and in addition to the aforementioned embodiments, an embodiment of the present invention provides a system for constructing a high-temporal-resolution ionospheric model using densely packed GNSS deformation stations. This system is used to implement the method for constructing a high-temporal-resolution ionospheric model using densely packed GNSS deformation stations described in the aforementioned method embodiments.

[0039] See also Figure 2 The system includes: a first main module for collecting dual-frequency observation data and broadcast ephemeris from densely populated GNSS deformation stations within the modeling area; a second main module for calculating multipath effects, cycle slip ratios, and data efficiency based on the collected data, and screening out data that meets quality requirements; a third main module for obtaining satellite-side DCB and receiver-side DCB respectively; a fourth main module for calculating a geometry-free distance combination using the screened dual-frequency observation data, and combining the satellite-side DCB and the receiver-side DCB to obtain the slant-path TEC; a fifth main module for calculating the penetration point position of the satellite signal in the thin layer, the satellite elevation angle and azimuth angle at the penetration point based on the thin layer assumption, and converting the slant-path TEC into vertical TEC using a projection function; and a sixth main module for constructing a TEC grid model, averaging the vertical TEC values ​​of all penetration points falling in each grid, and obtaining the TEC value.

[0040] The embodiment of the present invention provides a high temporal and spatial resolution ionospheric model system constructed by dense GNSS deformation stations. It is difficult to analyze small and medium-scale ionospheric structures, and new data sources have uneven data quality and ultra-large-scale computational complexity. Figure 2 Several modules in the system use data from existing large-scale and dense GNSS deformation network monitoring stations for calculations. The high-temporal and spatial resolution ionospheric model constructed can analyze the small and medium-scale ionospheric structure, while taking into account data quality and computational complexity, and achieving data value-added effects without increasing construction costs.

[0041] It should be noted that the system embodiments provided by the present invention are not only used to implement the methods in the above-mentioned method embodiments, but also used to implement the methods in other method embodiments provided by the present invention. The only difference is the setting of corresponding functional modules. The principles thereof are basically the same as those of the above-mentioned system embodiments provided by the present invention. As long as those skilled in the art refer to the specific technical solutions in other method embodiments on the basis of the above-mentioned system embodiments, obtain corresponding technical means and technical solutions composed of these technical means by combining technical features, and on the premise of ensuring the practicality of the technical solutions, improve the modules in the above-mentioned system embodiments to obtain corresponding system-type embodiments, which are used to implement the methods in other method-type embodiments. For example: Based on the content of the above system embodiment, as a preferred embodiment, the embodiment of the present invention provides a system for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations, wherein the second main module is further configured to execute the following instructions: Delete observation arcs whose multipath effect is less than a first preset value, whose cycle slip ratio is less than a second preset value, or whose data efficiency is lower than a third preset value, and retain the undeleted data as data that meets the quality requirements.

[0042] Based on the content of the above system embodiment, as a preferred embodiment, the embodiment of the present invention provides a system for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations, wherein the third main module is further configured to execute the following instructions: Download the Satellite DCB product and obtain Satellite DCB; The GNSS broadcast ephemeris and precise ephemeris are obtained, combined with the satellite-side DCB, and the receiver-side DCB of each GNSS deformation measuring station is estimated using the precise single point positioning method.

[0043] Based on the content of the above system embodiment, as a preferred embodiment, a system for constructing a high spatiotemporal resolution ionospheric model using dense GNSS deformation stations is provided in the embodiment of the present invention. When the third main module uses the precise point positioning method to estimate the DCB at the receiver end of each GNSS deformation station, the strategy adopted is: The satellite orbit, satellite clock error and satellite-side DCB are fixed, and non-differenced and non-combined observations are used. The Klobuchar model is used as the virtual ionospheric observation value, and the site coordinates, tropospheric delay and DCB are used as the parameters to be estimated.

[0044] Based on the content of the above system embodiment, as a preferred embodiment, a high temporal and spatial resolution ionospheric model system is constructed by dense GNSS deformation measurement stations provided in the embodiment of the present invention. The formula for obtaining the slant path TEC in the fourth main module is: STEC = P4 – DCBrec - DCBsat Among them, P4 represents the geometry-free distance combination, DCBrec represents the DCB at the receiver end, and DCBsat represents the satellite end receiver.

[0045] Based on the content of the above system embodiment, as a preferred embodiment, a high temporal and spatial resolution ionospheric model system is constructed by dense GNSS deformation measurement stations provided in the embodiment of the present invention. The expression for converting the oblique path TEC into vertical TEC using the projection function in the fifth main module is: VTEC = STEC·cos(z') where (z') represents the zenith distance of the ionospheric single-layer model, STEC represents slant-path TEC, and VTEC represents vertical TEC.

[0046] Based on the content of the above system embodiment, as a preferred embodiment, a system for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations provided in the embodiment of the present invention further includes: The seventh main module is used to fill in the empty value grids where no puncture points fall, using the values ​​of the adjacent grids.

[0047] Based on the same inventive concept as the aforementioned embodiment, an embodiment of the present invention further provides a device for constructing a high temporal and spatial resolution ionosphere model using dense GNSS deformation stations, comprising a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the method for constructing a high temporal and spatial resolution ionosphere model using dense GNSS deformation stations.

[0048] In an embodiment of the present invention, the memory may be a non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), or a volatile memory (volatile memory), such as a random-access memory (RAM). The memory is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory in an embodiment of the present invention may also be a circuit or any other device that can implement a storage function, for storing program instructions and / or data.

[0049] In the embodiments of the present invention, the processor may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention may be directly implemented and executed by a hardware processor, or by a combination of hardware and software modules within the processor.

[0050] According to one aspect of the present invention, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions, wherein the computer instructions enable the computer to execute the method for constructing a high spatiotemporal resolution ionospheric model using densely packed GNSS deformation stations, comprising: Collect dual-frequency observation data and broadcast ephemeris from dense GNSS deformation stations within the modeling area; Calculate the multipath effect, cycle slip ratio and data efficiency based on the collected data, and filter out data that meets the quality requirements; Obtain DCB on the satellite side and DCB on the receiver side respectively; The geometry-free distance combination is calculated using the selected dual-frequency observation data, and the slant path TEC is obtained by combining the DCB at the satellite end and the DCB at the receiver end. Based on the thin layer hypothesis, the penetration point of the satellite signal in the thin layer, the satellite elevation angle and azimuth at the penetration point are calculated, and the oblique path TEC is converted into vertical TEC using the projection function. A TEC grid model was constructed, and the vertical TEC values ​​of all puncture points falling on each grid were averaged to obtain the TEC value.

[0051] The terms "including" and "having" and any variations thereof in the description and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions, for example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to the steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0052] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices. The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily need to be executed in the order described. For example, some operations / steps may be further decomposed, while others may be combined or partially combined, so the actual execution order may vary depending on the actual situation.

[0053] In summary, the present invention proposes an ionospheric model with high temporal and spatial resolution, avoiding the loss of small and medium-scale ionospheric structures. Furthermore, the present invention utilizes data from existing large-scale, densely populated GNSS deformation network monitoring stations for calculation, thus achieving data value-added without increasing construction costs.

[0054] Unless otherwise specified, the above technologies are all known technologies.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations, characterized by: include: Collect dual-frequency observation data and broadcast ephemeris from dense GNSS deformation stations within the modeling area; Calculate the multipath effect, cycle slip ratio and data efficiency based on the collected data, and filter out data that meets the quality requirements; Obtain DCB on the satellite side and DCB on the receiver side respectively; The geometry-free distance combination is calculated using the selected dual-frequency observation data, and the slant path TEC is obtained by combining the DCB at the satellite end and the DCB at the receiver end. Based on the thin layer hypothesis, the penetration point of the satellite signal in the thin layer, the satellite elevation angle and azimuth at the penetration point are calculated, and the oblique path TEC is converted into vertical TEC using the projection function. A TEC grid model was constructed, and the vertical TEC values ​​of all puncture points falling on each grid were averaged to obtain the TEC value.

2. The method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations according to claim 1 is characterized in that: Calculate the multipath effect, cycle slip ratio, and data efficiency based on the collected data, and select data that meets quality requirements, including: Delete observation arcs whose multipath effect is less than a first preset value, whose cycle slip ratio is less than a second preset value, or whose data efficiency is lower than a third preset value, and retain the undeleted data as data that meets the quality requirements.

3. The method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations according to claim 1 is characterized in that: Obtain the satellite DCB and receiver DCB separately, including: Download the Satellite DCB product and obtain Satellite DCB; The GNSS broadcast ephemeris and precise ephemeris are obtained, combined with the satellite-side DCB, and the receiver-side DCB of each GNSS deformation measuring station is estimated using the precise single point positioning method.

4. The method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations according to claim 3 is characterized in that: When estimating the DCB at the receiver end of each GNSS deformation station using the precise point positioning method, the strategy adopted is: The satellite orbit, satellite clock error and satellite-side DCB are fixed, and non-differenced and non-combined observations are used. The Klobuchar model is used as the virtual ionospheric observation value, and the site coordinates, tropospheric delay and DCB are used as the parameters to be estimated.

5. The method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations according to claim 1 is characterized in that: The formula for the oblique path TEC is: STEC = P4 – DCBrec - DCBsat Among them, P4 represents the geometry-free distance combination, DCBrec represents the DCB at the receiver end, and DCBsat represents the satellite end receiver.

6. The method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations according to claim 1 is characterized in that: The expression for converting the oblique path TEC into a vertical TEC using the projection function is: VTEC = STEC·cos(z') where (z') represents the zenith distance of the ionospheric single-layer model, STEC represents slant-path TEC, and VTEC represents vertical TEC.

7. The method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations according to claim 1 is characterized in that: The method further comprises: For empty value grids where no puncture points fall, the values ​​of adjacent grids are used to fill them.

8. Dense GNSS deformation stations are used to construct a high temporal and spatial resolution ionospheric model system, characterized by: include: The first main module is used to collect dual-frequency observation data and broadcast ephemeris of dense GNSS deformation stations within the modeling area; The second main module is used to calculate the multipath effect, cycle slip ratio and data efficiency based on the collected data, and filter out the data that meets the quality requirements; The third main module is used to obtain the DCB of the satellite end and the DCB of the receiver end respectively; The fourth main module is used to calculate the geometry-free distance combination using the filtered dual-frequency observation data, and combine the satellite-side DCB and the receiver-side DCB to obtain the slant path TEC; The fifth main module is used to calculate the penetration point position of the satellite signal in the thin layer, the satellite altitude angle and azimuth angle at the penetration point based on the thin layer hypothesis, and convert the oblique path TEC into vertical TEC using the projection function; The sixth main module is used to build a TEC grid model, taking the average of the vertical TEC of all puncture points falling on each grid to obtain the TEC value.

9. A device for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations, characterized in that: The method comprises a memory and a processor, wherein the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the method for constructing a high temporal and spatial resolution ionospheric model using dense GNSS deformation stations as described in any one of claims 1 to 7.

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