Regional ionospheric modeling methods, devices and storage media

Abstract

This invention provides a method, apparatus, electronic device, and storage medium for regional ionospheric modeling, belonging to the field of satellite navigation and positioning technology. The method includes: acquiring the coordinates of multiple reference stations in a region; matching the coordinates with a preset threshold to obtain the coordinates of a reference point; obtaining the longitude and latitude differences between the regional reference stations and the reference point based on the coordinates of the multiple reference stations and the reference point; acquiring the coordinates of a target satellite; obtaining the difference in elevation angles observed by the multiple reference stations and the reference point of the target satellite based on the coordinates of the target satellite and the coordinates of the multiple reference stations in the region; constructing a coefficient matrix based on the elevation angle differences, the longitude and latitude differences between the regional reference stations and the reference point; and constructing a regional ionospheric model based on the coefficient matrix and the acquired regional ionospheric model coefficients. Because this invention considers the influence of both horizontal gradient and vertical delay during the modeling process, it significantly improves the model fitting accuracy.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation and positioning technology, specifically to a regional ionospheric modeling method, apparatus, electronic device, and storage medium. Background Technology

[0002] Precise Point Positioning-Real-Time Kinematic (PPP-RTK) technology, developed in recent years, has achieved high-precision and rapid positioning by providing corrections for satellite orbit, clock bias, phase deviation, and atmospheric delay. However, due to the strong spatiotemporal characteristics of the ionosphere, and the varying intensity of ionospheric activity at different latitudes and longitudes, high-precision ionospheric modeling has become a key factor affecting the high-precision positioning of PPP-RTK.

[0003] Currently, the slant ionospheric delay (SID) applied to PPP-RTK is mainly obtained through two methods: First, a spatial model of the Vertical Total ElectronContent (VTEC) is constructed, and a mapping function is used to map the VTEC in the vertical direction to the slant direction, which improves the positioning performance of PPP-RTK to some extent. Second, a single-star ionospheric delay model is constructed using a regional reference network, mainly employing interpolation and grid polynomial methods. The interpolation method interpolates the ionospheric correction of the reference station to the user to generate ionospheric enhancement information with centimeter-level accuracy. The grid polynomial model uses polynomial fitting to derive the SID and performs residual compensation based on neighboring grid points to improve the accuracy of ionospheric correction.

[0004] The first method for constructing the Vertical Total Electron Content (VTEC) spatial model has the following problems: Due to the accuracy of the VTEC model and mapping errors, the relatively low SID accuracy makes it difficult to quickly fix PPP ambiguities. The second method, using interpolation, has the following problems: It requires all reference stations to send correction data and necessitates bidirectional communication, leading to large data transmission volumes, high communication costs, and risks of privacy leaks. The second method, using grid polynomials, has the following problems: While traditional grid polynomial methods overcome the shortcomings of the above two methods, they only consider the horizontal gradient effect when modeling the ionosphere, neglecting the vertical ionospheric variations related to the elevation angle, resulting in reduced fitting accuracy. Summary of the Invention

[0005] In view of this, it is necessary to provide a regional ionospheric modeling method, apparatus, electronic device and storage medium to solve the technical problem of low fitting accuracy in ionospheric modeling in the prior art.

[0006] To address the aforementioned technical problems, in a first aspect, the present invention provides a method for regional ionosphere modeling, comprising:

[0007] The coordinates of multiple reference stations in the region are obtained, and the coordinates are matched with a preset threshold to obtain the coordinates of the reference point. Based on the coordinates of the multiple reference stations and the coordinates of the reference point in the region, the longitude difference and latitude difference between the regional reference stations and the reference point are obtained.

[0008] Obtain the coordinates of the target satellite, and based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, obtain the difference in the elevation angle of the target satellite observed by multiple reference stations and reference points;

[0009] A coefficient matrix is ​​constructed based on the difference in elevation angle, the difference in longitude and latitude between regional reference stations and reference points;

[0010] A regional ionospheric model is constructed based on the coefficient matrix and the obtained regional ionospheric model coefficients.

[0011] In one possible implementation, the regional ionosphere model is as follows:

[0012]

[0013]

[0014]

[0015] in, and The coordinate difference between reference station r and reference station o. , , , as well as These are: the first coefficient, the second coefficient, the third coefficient, the fourth coefficient, and the fifth coefficient of the polynomial expansion associated with the horizontal gradient. , , as well as These are: the first coefficient of the polynomial expansion associated with the vertical delay of the ionosphere, the second coefficient of the polynomial expansion associated with the vertical delay of the ionosphere, the third coefficient of the polynomial expansion associated with the vertical delay of the ionosphere, and the fourth coefficient of the polynomial expansion associated with the vertical delay of the ionosphere.

[0016] Let r be the elevation angle of satellite s obtained from reference station r. For: the reference star obtained from reference station r altitude angle, For: the elevation angle of satellite s obtained from reference point o and For: the reference star obtained from reference point o The altitude angle.

[0017] In one possible implementation, obtaining the longitude difference and latitude difference between regional reference stations and reference points based on the coordinates of multiple reference stations and reference points in the region includes:

[0018] The longitude and latitude differences between the reference stations and reference points in the region are obtained by subtracting the coordinates of multiple reference stations and reference points in the region.

[0019] In one possible implementation, obtaining the difference in elevation angle of the target satellite observed by multiple reference stations and reference points, based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, includes:

[0020] Based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, the elevation angles of the target satellite observed by multiple reference stations are obtained. Based on the elevation angles of the target satellite observed by multiple reference stations and the elevation angles of the target satellite observed by a reference point, the difference between the elevation angles of the target satellite observed by multiple reference stations and the elevation angles of the target satellite observed by a reference point is obtained.

[0021] In one possible implementation, obtaining the difference in elevation angle of the target satellite observed by multiple reference stations and reference points, based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, includes:

[0022] The difference between the elevation angles of the target satellite observed by multiple reference stations and the elevation angle of the target satellite observed by a reference point is obtained by subtracting the elevation angles of the target satellite observed by multiple reference stations and a reference point.

[0023] In one possible implementation, the acquired regional ionospheric model coefficients include:

[0024] The raw observation data from the regional reference station receiver is acquired. Based on the raw observation data, a high-precision ionospheric slant delay correction for the target satellite is obtained. Based on the high-precision ionospheric slant delay correction for the target satellite, the regional ionospheric model coefficients are obtained. The observation data includes pseudorange and phase observations from the regional reference station receiver.

[0025] In one possible implementation, the high-precision ionospheric slant delay correction based on the target satellite is used to obtain the regional ionospheric model coefficients, including:

[0026] The observation vector is composed of the high-precision ionospheric slant delay correction of the target satellite, and the regional ionospheric model coefficients are obtained based on the observation vector.

[0027] In one possible implementation, obtaining the regional ionospheric model coefficients based on the observation vector includes:

[0028] The observation equations are constructed based on the observation vectors, and the coefficients of the regional ionospheric model are obtained by solving the observation equations using the least squares method.

[0029] Secondly, the present invention also provides a regional ionosphere modeling apparatus, comprising:

[0030] The first data acquisition unit is used to acquire the coordinates of multiple reference stations in the region, match the coordinates with a preset threshold to obtain the coordinates of the reference point, and obtain the longitude difference and latitude difference between the regional reference stations and the reference point based on the coordinates of the multiple reference stations and the reference point.

[0031] The second data acquisition unit is used to acquire the coordinates of the target satellite and, based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, obtain the difference in the elevation angle of the target satellite observed by multiple reference stations and reference points.

[0032] Construct coefficient matrix units to build coefficient matrices based on differences in elevation angles, differences in longitude and latitude between regional reference stations and reference points;

[0033] Construct regional ionospheric model units to build regional ionospheric models based on coefficient matrices and obtained regional ionospheric model coefficients.

[0034] Thirdly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instructions, which, when executed by a processor, can implement the steps in the regional ionosphere modeling method described in any of the above implementations.

[0035] The beneficial effects of this invention are as follows: The regional ionospheric modeling method provided by this invention first calculates and obtains the difference in elevation angles of the target satellite observed by multiple reference stations and reference points by linearizing the vertical changes in the ionosphere. This difference in elevation angles is then incorporated into the traditional polynomials for longitude and latitude differences between regional reference stations, thereby reducing the impact of the vertical component of the ionospheric slant delay on the fitting accuracy and improving the fitting accuracy of regional ionospheric modeling. Furthermore, because this invention considers the effects of both horizontal gradient and vertical delay during the modeling process, it significantly improves the modeling accuracy compared to the traditional polynomial method that only considers the horizontal gradient. This improved modeling accuracy effectively alleviates the pressure on channel data transmission. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0037] Figure 1 A schematic flowchart of an embodiment of the regional ionosphere modeling method provided by the present invention;

[0038] Figure 2 This is a schematic diagram of an embodiment of the regional ionosphere modeling device provided by the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0040] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0041] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0042] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0043] This invention provides a method, apparatus, electronic device, and storage medium for regional ionosphere modeling, which will be described below.

[0044] Figure 1 A schematic flowchart of an embodiment of the regional ionosphere modeling method provided by the present invention is shown below. Figure 1 As shown, regional ionosphere modeling methods include:

[0045] S101. Obtain the coordinates of multiple reference stations in the region, match the coordinates with a preset threshold to obtain the coordinates of the reference point, and obtain the longitude difference and latitude difference between the regional reference stations and the reference point based on the coordinates of the multiple reference stations and the reference point in the region.

[0046] It should be noted that the reference station at or closest to the center of the region is selected as the reference point for ionospheric polynomial modeling.

[0047] S102. Obtain the coordinates of the target satellite, and based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, obtain the difference in the elevation angle of the target satellite observed by multiple reference stations and reference points.

[0048] It should be noted that the derivation process is as follows:

[0049]

[0050] in, and These are the stations The obtained satellite and reference satellite altitude angle, and They are the stations satellites that arrived and reference satellite The altitude angle.

[0051] Similarly, with Taking the point of expansion, we perform a Taylor expansion on the above equation, considering its approximate accuracy and computational efficiency, and retain the second-order terms:

[0052]

[0053] in, and For satellite and reference satellite Vertical ionospheric delay.

[0054]

[0055] in, The first polynomial expansion One coefficient, and They are the stations The obtained satellite and reference satellite altitude angle, and For the station satellites that arrived and reference satellite elevation angle and and Satellites and reference satellite Vertical ionospheric delay difference.

[0056] Furthermore, the expression for the slant ionospheric delay (SID) is as follows:

[0057]

[0058] in, and They are the stations and monitoring station The coordinate difference between them and It is the first polynomial expansion related to the horizontal gradient. Each coefficient.

[0059] Furthermore, reference station The SDBS SID is:

[0060]

[0061]

[0062] in, Indicates the station-star double difference SID, Indicates the station closest to the center area The obtained SDBS SID, and These are the stations and monitoring station The coordinate difference between them For the station star double difference, , , and These are the stations The obtained satellite and reference satellite altitude angle, and For the station satellites that arrived and reference satellite altitude angle, The station closest to the regional center and serving as the reference point. SID and Indicates the station closest to the center area The obtained SDBS SID is calculated using polynomial coefficients. express.

[0063] S103. Construct a coefficient matrix based on the difference in elevation angle, the difference in longitude and latitude between regional reference stations and reference points.

[0064] It should be noted that the server constructs a coefficient matrix using the difference in elevation angle, the difference in longitude and latitude between the regional reference station and the reference point as elements, constructs the observation equation using the SDBS SID on the reference station r as the observation value, estimates the polynomial coefficients using the least squares algorithm, and broadcasts it to the user.

[0065] It should be further explained that the differences between the latitude and longitude coordinates of the user station and the reference point, as well as the observed satellite elevation angle, are calculated, and the user's SDBS SID is fitted using the polynomial coefficients received by the user. The specific formula is as follows:

[0066]

[0067] in, SDBS SIDs fitted for the user end , , The polynomial coefficients broadcast by the server and and Represents the user's latitude and longitude coordinates.

[0068] It should be noted that the above formula can also be simplified to a first order depending on the actual situation.

[0069]

[0070] in, From the station closest to the central area The obtained SDBS SID, The station's star-difference SID is shown below:

[0071]

[0072] in, and For the station and monitoring station Inter-station single difference SID, and It can be decomposed into horizontal gradient and vertical delay effects.

[0073] Furthermore,

[0074]

[0075] in, ; and These are the stations The obtained satellite and reference satellite altitude angle, , They are the stations satellites that arrived and reference satellite altitude angle, and For the station The obtained satellite and reference satellite Vertical ionospheric delay, and For the station The obtained satellite and reference satellite Vertical ionospheric delay.

[0076] Based on the above formula, the station-satellite double difference SID can be deduced as:

[0077]

[0078] Furthermore,

[0079]

[0080] in, Due to the vertical delay effect, This is due to the influence of the horizontal gradient.

[0081] With the station Reference point (latitude = Longitude = Using a second-order Taylor expansion to measure distance Perform linearization representation:

[0082]

[0083] in, It is the first of the Taylor series expansions. One coefficient, and These are the stations and monitoring station The coordinate difference between them.

[0084] For some small areas, the effect of the horizontal gradient can also be approximated using a first-order latitude and longitude polynomial:

[0085]

[0086] in, and The first is associated with the horizontal gradient. Each coefficient.

[0087] In some embodiments of the present invention, obtaining the difference in elevation angle of the target satellite observed by multiple reference stations and reference points based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region includes:

[0088] Based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, the elevation angles of the target satellite observed by multiple reference stations are obtained. Based on the elevation angles of the target satellite observed by multiple reference stations and the elevation angles of the target satellite observed by a reference point, the difference between the elevation angles of the target satellite observed by multiple reference stations and the elevation angles of the target satellite observed by a reference point is obtained.

[0089] In some embodiments of the present invention, obtaining the difference in elevation angle of the target satellite observed by multiple reference stations and reference points based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region includes:

[0090] The difference between the elevation angles of the target satellite observed by multiple reference stations and the elevation angle of the target satellite observed by a reference point is obtained by subtracting the elevation angles of the target satellite observed by multiple reference stations and a reference point.

[0091] S104. Based on the coefficient matrix and the obtained regional ionospheric model coefficients, construct the regional ionospheric model.

[0092] It should be noted that precise point positioning and real-time dynamic positioning technology has become one of the main methods of GNSS precise positioning due to its high positioning accuracy and ease of operation. However, the convergence time of more than 30 minutes has become a major obstacle limiting the application of precise point positioning and real-time dynamic positioning technology. This invention mainly utilizes a regional reference network to construct a single-satellite ionospheric slant delay model and implements it through a grid polynomial method. The grid polynomial model uses polynomial fitting to obtain inter-satellite single differences and performs residual compensation on the inter-satellite single differences based on neighboring grid points to improve the accuracy of ionospheric correction. However, high-precision ionospheric correction depends on high-order polynomials and high-resolution grids, and the order of grid residual compensation depends on the magnitude of the residual ionospheric delay. Therefore, improving the accuracy of polynomial modeling and reducing the magnitude of ionospheric residuals can, to some extent, reduce the amount of ionospheric compensation residuals broadcast and alleviate the pressure on channel transmission. Currently, traditional polynomial methods only consider the influence of horizontal gradients when modeling the ionosphere, without taking into account the vertical ionospheric changes related to the elevation angle, leading to a decrease in fitting accuracy.

[0093] In some embodiments of the present invention, the obtained regional ionospheric model coefficients include:

[0094] The raw observation data from the regional reference station receiver is acquired. Based on the raw observation data, high-precision ionospheric slant delay corrections for the target satellite observed by the reference station are extracted. Based on the high-precision ionospheric slant delay corrections for the target satellite, the regional ionospheric model coefficients are obtained. The observation data includes pseudorange and phase observations from the regional reference station receiver.

[0095] It should be noted that, firstly, inter-satellite single differences are extracted using non-differential, non-combined observation equations and a strategy based on partially fixed ambiguities. Secondly, an appropriate reference satellite is selected, and an inter-satellite single difference strategy is employed to eliminate receiver segment differential code bias, generating inter-satellite single differences, which are then used for ionospheric polynomial modeling. Specifically, the equation is as follows:

[0096]

[0097] in, and These represent frequencies of 100 and 110 respectively. ( The pseudorange and phase observations, The geometric distance between the satellite and the receiver. The speed of light in a vacuum. and These are receiver clock bias and satellite clock bias, respectively. For frequency wavelength, For integer ambiguity, and These are the pseudorange code deviations for the receiver and the satellite, respectively. and The carrier phase hardware delays for the receiver and the satellite are respectively. It is frequency The ionospheric coefficient at the location (i=1). For first-order ionospheric delay, For tropospheric mapping functions, For tropospheric delay, The inter-system bias (ISB) between the satellite system and GPS. and These are the noise sum of the unmodeled errors in pseudorange and phase observations, respectively. Solid tides, ocean tides, phase center offset (PCO), phase center variation (PCV), and relativistic effects can all be accurately corrected using existing models.

[0098] It is necessary to further understand that, due to the correlation between parameters in the original observation equations, the parameters cannot be directly estimated. Therefore, parameter merging and absorption are performed before parameter estimation. The precise satellite clock bias products provided by the International GNSS Service (IGS) include pseudorange hardware delays without ionospheric integration at the satellite end. Therefore, after satellite clock bias correction, receiver clock bias, ionospheric delay, and ambiguity will all absorb some of the pseudorange hardware delay. In addition, phase hardware delay is strongly correlated with integer ambiguity and will be directly absorbed by the ambiguity. Therefore, the reparameterized dual-frequency non-difference non-combination equations can be expressed as:

[0099]

[0100] in, To absorb the ambiguity caused by pseudorange and phase hardware delay, To absorb the satellite clock bias caused by pseudorange hardware delay, To absorb the receiver clock error caused by the receiver pseudorange hardware delay.

[0101] It should be noted that the ionospheric slant delay is extracted from each reference station at fixed coordinates using a partial ambiguity fixation strategy and then used to construct the ionospheric polynomial model. The specific formula is as follows:

[0102]

[0103] in , , , and The receiver is at the frequency and frequency Pseudorange code deviation at the location, and Indicates the satellite's frequency and frequency The pseudorange code deviation at that location.

[0104] It should be further explained that, since the ionospheric slant delay extracted in the above formula introduces errors from both the satellite and the receiver, inter-satellite single-difference is used to eliminate the influence of receiver-side errors. Therefore, the inter-satellite single-difference ionospheric slant delay... It can be represented as:

[0105]

[0106] in, For mapping functions, and They are satellites and reference satellite altitude angle, and For satellite and reference satellite Vertical ionospheric delay.

[0107] Furthermore, regarding the effects of vertical delay and horizontal gradient:

[0108]

[0109] in, Due to the vertical delay effect, This is due to the influence of the horizontal gradient. Changes in the horizontal direction of the ionosphere can be represented by the horizontal gradient. and distance To approximate:

[0110]

[0111] Therefore, the effect of the horizontal gradient can be expressed as:

[0112]

[0113] in, , They are the stations satellites that arrived and reference satellite altitude angle, The horizontal gradient of the ionosphere, The distance between reference station r and reference point o

[0114] It should be further explained that the effect of vertical delay is specifically as described in the following formula:

[0115]

[0116] Understandably, the vertical delay effect can be analyzed using a function of the elevation angle:

[0117]

[0118] It should be further explained that the estimated coefficients are sent to users via satellite communication broadcast and the inter-satellite single-difference ionospheric slant delay is fitted at the user end.

[0119] Users utilize the fitted inter-satellite single-difference ionospheric slant delay as enhanced ionospheric information to achieve rapid ambiguity fixation, thereby improving the positioning performance of Precise Point Positioning and Real-Time Dynamic Kinematics (PPP-RTK) technology. Specifically, the formula is as follows:

[0120]

[0121] in, For the user's estimated SID, residual It follows a mean of zero and a prior variance of . It follows a normal distribution.

[0122] It should be noted that users use the fitted SID as an ionospheric delay parameter constraint to achieve rapid fixation of ambiguity.

[0123] It should be further noted that the method employed in this invention considers the effects of both horizontal gradient and vertical delay during the modeling process, significantly improving modeling accuracy compared to traditional polynomial methods that only consider horizontal gradient. This improved modeling accuracy not only effectively alleviates channel data transmission pressure but also further shortens the time for initial ambiguity fixation at the user end, enhancing the positioning performance of both precise single-point and real-time dynamic positioning.

[0124] To better implement the regional ionosphere modeling method in the embodiments of the present invention, based on regional ionosphere modeling, correspondingly, as follows: Figure 2 As shown, this embodiment of the invention also provides a regional ionosphere modeling apparatus, the regional ionosphere modeling apparatus 200 comprising:

[0125] The first data acquisition unit 201 is used to acquire the coordinates of multiple reference stations in the region, match the coordinates with a preset threshold to obtain the coordinates of the reference point, and obtain the longitude difference and latitude difference between the regional reference stations and the reference point based on the coordinates of the multiple reference stations and the reference point in the region.

[0126] The second data acquisition unit 202 is used to acquire the coordinates of the target satellite and, based on the coordinates of the target satellite and the coordinates of multiple reference stations in the region, obtain the difference in the elevation angle of the target satellite observed by multiple reference stations and reference points.

[0127] Construct coefficient matrix unit 203 to construct a coefficient matrix based on the difference in elevation angle, the difference in longitude and latitude between regional reference stations and reference points;

[0128] Construct regional ionospheric model unit 204 to construct a regional ionospheric model based on the coefficient matrix and the obtained regional ionospheric model coefficients.

[0129] The regional ionosphere modeling device 200 provided in the above embodiments can realize the technical solutions described in the above regional ionosphere modeling method embodiments. The specific implementation principles of each module or unit can be found in the corresponding content in the above regional ionosphere modeling method embodiments, and will not be repeated here.

[0130] Furthermore, embodiments of this application provide a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions in the regional ionosphere modeling methods provided in the above-described method embodiments.

[0131] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0132] The above provides a detailed description of the regional ionosphere modeling method, apparatus, and storage medium provided by the present invention. Specific examples have been used to illustrate the principles and embodiments of the present invention. The description of the embodiments above is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method of regional ionospheric modeling, characterized in that, The method comprises the following steps: obtaining the coordinates of the plurality of reference stations in the region, matching the coordinates with a preset threshold to obtain the coordinates of the reference point, and obtaining the longitude difference and the latitude difference between the reference stations and the reference point in the region based on the coordinates of the plurality of reference stations and the coordinates of the reference point; obtaining the coordinates of the target satellite, and obtaining the difference in the elevation angle of the target satellite observed by the plurality of reference stations and the reference point based on the coordinates of the target satellite and the coordinates of the plurality of reference stations in the region; constructing a coefficient matrix based on the difference in the elevation angle, the longitude difference and the latitude difference between the reference stations and the reference point in the region; the difference in the elevation angle is used to represent the vertical delay effect, and the longitude difference and the latitude difference are used to represent the horizontal gradient influence; constructing a regional ionospheric model based on the coefficient matrix and the obtained regional ionospheric model coefficient.

2. The regional ionospheric modeling method of claim 1, wherein, The regional ionospheric model is: wherein and are respectively: a first coefficient of a polynomial expansion associated with the horizontal gradient, , , , and are respectively: a first coefficient of a polynomial expansion associated with the ionospheric vertical delay, , , and are respectively: a first coefficient of a polynomial expansion associated with the ionospheric vertical delay, is: an elevation angle of the satellite s obtained by the reference station r, is: an elevation angle of the reference star obtained by the reference station r, is: an elevation angle of the satellite s obtained by the reference point o, and is: an elevation angle of the reference star obtained by the reference point o.

3. The regional ionospheric modeling method of claim 1, wherein, The method comprises the following steps: obtaining the coordinates of the plurality of reference stations in the region, matching the coordinates with a preset threshold to obtain the coordinates of the reference point, and obtaining the longitude difference and the latitude difference between the reference stations and the reference point in the region based on the coordinates of the plurality of reference stations and the coordinates of the reference point; 4. The regional ionospheric modeling method of claim 1, wherein, obtaining the coordinates of the plurality of reference stations in the region, matching the coordinates with a preset threshold to obtain the coordinates of the reference point, and obtaining the longitude difference and the latitude difference between the reference stations and the reference point in the region based on the coordinates of the plurality of reference stations and the coordinates of the reference point; obtaining the coordinates of the target satellite, and obtaining the difference in the elevation angle of the target satellite observed by the plurality of reference stations and the reference point based on the coordinates of the target satellite and the coordinates of the plurality of reference stations in the region; 5. The regional ionospheric modeling method of claim 4, wherein, obtaining the coordinates of the target satellite, and obtaining the difference in the elevation angle of the target satellite observed by the plurality of reference stations and the reference point based on the coordinates of the target satellite and the coordinates of the plurality of reference stations in the region; obtaining the coordinates of the target satellite, and obtaining the difference in the elevation angle of the target satellite observed by the plurality of reference stations and the reference point based on the coordinates of the target satellite and the coordinates of the plurality of reference stations in the region; 6. The regional ionospheric modeling method of claim 1, wherein, obtaining the coordinates of the target satellite, and obtaining the difference in the elevation angle of the target satellite observed by the plurality of reference stations and the reference point based on the coordinates of the target satellite and the coordinates of the plurality of reference stations in the region; The obtained regional ionospheric model coefficient comprises:

7. The regional ionospheric modeling method of claim 6, wherein, obtaining the original observation data of the regional reference station receiver, obtaining the high-precision ionospheric slant delay correction number of the target satellite based on the original observation data, and obtaining the regional ionospheric model coefficient based on the high-precision ionospheric slant delay correction number of the target satellite; the observation data comprises the pseudo-range and phase observation value of the regional reference station receiver. The obtained regional ionospheric model coefficient comprises:

8. The regional ionospheric modeling method of claim 7, wherein, obtaining the high-precision ionospheric slant delay correction number of the target satellite, and obtaining the regional ionospheric model coefficient based on the high-precision ionospheric slant delay correction number of the target satellite. The obtained regional ionospheric model coefficient comprises:

9. An apparatus for regional ionospheric modeling, the apparatus comprising: obtaining the high-precision ionospheric slant delay correction number of the target satellite, and obtaining the regional ionospheric model coefficient based on the high-precision ionospheric slant delay correction number of the target satellite. The obtained regional ionospheric model coefficient comprises: obtaining the high-precision ionospheric slant delay correction number of the target satellite, and obtaining the regional ionospheric model coefficient based on the high-precision ionospheric slant delay correction number of the target satellite. The method comprises the following steps: a first data acquisition unit is configured to obtain the coordinates of the plurality of reference stations in the region, match the coordinates with a preset threshold to obtain the coordinates of the reference point, and obtain the longitude difference and the latitude difference between the reference stations and the reference point in the region based on the coordinates of the plurality of reference stations and the coordinates of the reference point; a second data obtaining unit configured to obtain coordinates of the target satellite, and obtain difference values of the elevation angles of the target satellite observed by the plurality of reference stations and the reference point based on the coordinates of the target satellite and the coordinates of the plurality of reference stations in the region; the difference values of the elevation angles are used to represent the vertical delay effect, and the difference values of the longitude and latitude are used to represent the horizontal gradient effect; a coefficient matrix constructing unit configured to construct a coefficient matrix based on the difference values of the elevation angles, the difference values of the longitude and latitude between the reference stations and the reference point in the region; a regional ionospheric model constructing unit configured to construct a regional ionospheric model based on the coefficient matrix and the obtained regional ionospheric model coefficients.

10. A computer-readable storage medium, characterized in that, a computer readable storage medium for storing computer readable programs or instructions, which are executed by a processor to implement the steps of the regional ionospheric modeling method in any one of claims 1 to 8.

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