A method for constructing an ionospheric three-dimensional model based on low-orbit constellation Doppler observation
By constructing a three-dimensional model of the ionosphere using Doppler observations from low-orbit satellites, the problem of difficulty in analyzing ionospheric density distribution in existing technologies has been solved, enabling high-precision ionospheric monitoring and stable data acquisition, while reducing monitoring costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIHANG UNIV
- Filing Date
- 2026-03-13
- Publication Date
- 2026-06-12
Smart Images
Figure CN122194201A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of satellite navigation and positioning and space environment monitoring technology, and in particular relates to a method for constructing a three-dimensional model of the ionosphere based on Doppler observations from a low-Earth orbit constellation. Background Technology
[0002] The ionosphere, a crucial component of Earth's upper atmosphere, directly impacts radio signal propagation due to its changing state. When GNSS navigation and satellite communication signals traverse the ionosphere, they are interfered with by ionospheric irregularities, causing rapid, random fluctuations in signal amplitude and phase—a phenomenon known as ionospheric scintillation. With solar activity entering its high-period cycle, the frequency and intensity of ionospheric scintillation have significantly increased, seriously threatening the accuracy and reliability of satellite navigation services. Therefore, establishing high spatiotemporal resolution methods for ionospheric monitoring and modeling is of paramount practical significance for space weather early warning and the robust operation of communication and navigation constellations. Currently, the main technical approaches in this field rely on specialized ionospheric scintillation monitoring receivers and a widely deployed ground-based GNSS observation network. While specialized monitoring receivers offer high accuracy, their high cost leads to sparse deployment and difficulty in achieving high-density global monitoring coverage. Monitoring methods based on ordinary geodesic GNSS receivers are more widely used; however, their core reliance is on carrier phase observations. In environments with strong ionospheric scintillation, carrier phase observations are highly susceptible to cycle slips, leading to discontinuous data or estimated anomalies, ultimately causing monitoring models to fail under adverse space weather conditions. To address the issue of carrier phase cycle slips, existing technologies have proposed methods for constructing ionospheric scintillation indices based on GNSS Doppler observations. This method utilizes Doppler observations that are insensitive to cycle slips, effectively reducing monitoring costs and improving data availability in strong scintillation environments. However, this method still obtains the integral result of the electron content path across the entire space from the Earth's surface to satellite altitude, failing to reflect the fine structure of the ionosphere at a vertical scale. While further integration with three-dimensional tomography holds promise for obtaining electron density information at different altitudes, its calculation process relies on empirical vertical constraints to improve the rank deficiency of the tomographic equations. For periods of high solar activity where empirical constraints are inapplicable, the accuracy and availability of vertical electron density results obtained through tomography are limited. Therefore, existing technologies cannot adequately resolve the electron density distribution within the 50 to 1000 km range, where major ionospheric activity is concentrated, significantly limiting in-depth understanding of ionospheric physical processes and the improvement of high-precision space environment early warning capabilities. How to overcome the technical bottleneck of vertical resolution through observation while ensuring the continuous and stable monitoring data in complex electromagnetic environments has become a core problem that urgently needs to be solved in the field of high-precision ionospheric modeling. Summary of the Invention
[0003] To address the aforementioned technical problems, this invention proposes a method for constructing a three-dimensional ionospheric model based on Doppler observations from low-Earth orbit constellations, thereby resolving the issues present in the existing technologies.
[0004] Firstly, to achieve the above objectives, this invention provides a method for constructing a three-dimensional ionospheric model based on Doppler observations from a low-Earth orbit constellation, comprising the following steps: Acquire Doppler observations of dual-frequency or triple-frequency signals from various low-Earth orbit satellites at different orbital altitudes, and classify the observation data into different altitude layer sets according to the orbital altitude of each satellite; Based on the Doppler observations, the rate of change of total electron content in the ionosphere along the line of sight is calculated by constructing a geometric distance-free combination solution, and the rate of change is integrated in the time domain and corrected by a constant term to obtain the total amount of tilted ionosphere. The total tilted ionospheric content is vertically projected onto the orbital altitude of the corresponding satellite to obtain the vertical total electron content of each altitude layer. A spherical two-dimensional model is then performed on the vertical total electron content at each altitude layer to construct a cumulative two-dimensional ionospheric model for each altitude layer. Interlayer difference is performed on the cumulative two-dimensional ionospheric model of adjacent height layers to obtain the electron content of the corresponding height interval, and a three-dimensional voxel mesh is inverted based on the electron content to generate a three-dimensional model of ionospheric electron density.
[0005] Optionally, the process of acquiring and classifying observation data includes: The Doppler observations are preprocessed by removing outliers and truncating elevation angles; The average orbital altitude of the satellite is calculated based on the satellite ephemeris, and the preprocessed observation data is divided into multiple altitude layer sets corresponding to different average orbital altitudes.
[0006] Optionally, the process of calculating the rate of change of total electron content in the ionosphere includes: For dual-frequency signals, a dual-frequency geometric distance-free combination is used for solution; Alternatively, for three-frequency signals, a three-frequency linear combination that satisfies the constraints of geometric distance and receiver clock error can be used for solution.
[0007] Optionally, the process of integrating the rate of change in the time domain and correcting for the constant term includes: Numerical integration of the rate of change of total electron content in the ionosphere over consecutive epochs yields the total tilted ionosphere, including terms of undetermined constants. The constant term is determined by using the statistical mean of a geometrically inverse combination of pseudorange observations, or by using reference values provided by an empirical ionospheric model.
[0008] Optionally, the vertical projection process includes: By using a single-layer mapping function, combined with the satellite elevation angle and satellite orbital altitude, the total amount of tilted ionosphere is converted into the total vertical electron content at the corresponding orbital altitude.
[0009] Optionally, the process of performing interlayer differential includes: Calculate the difference value of the cumulative two-dimensional ionospheric model between two adjacent height layers. The difference value represents the electron content information in the height interval between these two height layers.
[0010] Optionally, the process of performing 3D voxel mesh inversion includes: The average electron density is calculated based on the electron content of the height interval obtained from the interlayer difference and the corresponding thickness of the height interval. Within the specified height range, the vertical distribution function of the ionosphere is introduced as a constraint for fitting to refine the electron density distribution inside the shell.
[0011] Secondly, the present invention also provides a computer terminal device, comprising: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the method for constructing a three-dimensional ionospheric model based on low-Earth orbit constellation Doppler observations in the first aspect described above.
[0012] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the method for constructing a three-dimensional ionospheric model based on low-Earth orbit constellation Doppler observations in the first aspect described above.
[0013] Fourthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method for constructing a three-dimensional ionospheric model based on low-Earth orbit constellation Doppler observations described in the first aspect above.
[0014] Compared with the prior art, the present invention has the following advantages and technical effects: This invention provides a method for constructing a three-dimensional ionospheric model based on Doppler observations from a low-Earth orbit (LEO) constellation. This method possesses the capability for detailed detection of the ionospheric vertical structure, overcoming the limitation of traditional methods that can only obtain vertical integral information of the ionosphere. By utilizing LEO satellites operating at different altitudes within the ionosphere for observation and employing interlayer difference and fusion techniques, this invention can resolve the detailed electron density distribution structure of the ionosphere in the vertical direction. The model is constructed based on cycle-slip-immune Doppler observations, exhibiting strong anti-interference capabilities and ensuring data continuity and model stability under strong ionospheric scintillation or complex electromagnetic environments. Furthermore, this invention eliminates the need for expensive dedicated monitoring facilities, achieving high spatiotemporal resolution three-dimensional ionospheric monitoring globally at a relatively low cost by utilizing widely distributed LEO constellation resources and commercial terminals. Attached Figure Description
[0015] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart illustrating a method for constructing a three-dimensional ionospheric model based on Doppler observations from a low-Earth orbit constellation, according to an embodiment of the present invention. Detailed Implementation
[0016] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.
[0017] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.
[0018] Example 1 like Figure 1 As shown, this embodiment provides a method for constructing a three-dimensional model of the ionosphere based on Doppler observations from a low-Earth orbit constellation, including: Acquire Doppler observations of dual-frequency or triple-frequency signals from various low-Earth orbit satellites at different orbital altitudes, and classify the observation data into different altitude layer sets according to the orbital altitude of each satellite; Based on the Doppler observations, the rate of change of total electron content in the ionosphere along the line of sight is calculated by constructing a geometric distance-free combination solution, and the rate of change is integrated in the time domain and corrected by a constant term to obtain the total amount of tilted ionosphere. The total tilted ionospheric content is vertically projected onto the orbital altitude of the corresponding satellite to obtain the vertical total electron content of each altitude layer. A spherical two-dimensional model is then performed on the vertical total electron content at each altitude layer to construct a cumulative two-dimensional ionospheric model for each altitude layer. Interlayer difference is performed on the cumulative two-dimensional ionospheric model of adjacent height layers to obtain the electron content of the corresponding height interval, and a three-dimensional voxel mesh is inverted based on the electron content to generate a three-dimensional model of ionospheric electron density.
[0019] Furthermore, the process of acquiring and classifying observation data includes: The Doppler observations are preprocessed by removing outliers and truncating elevation angles; The average orbital altitude of the satellite is calculated based on the satellite ephemeris, and the preprocessed observation data is divided into multiple altitude layer sets corresponding to different average orbital altitudes.
[0020] Specifically, the implementation process of this embodiment includes: Step 1: Acquisition and cleaning of multi-source low-Earth orbit satellite observation data: Data Acquisition: Utilizing multi-mode satellite receivers deployed globally, various types of low-Earth orbit (LEO) satellite signals are acquired. The target signal is a dual-frequency ( ) or tri-frequency ( Low-Earth orbit satellites with signal broadcasting capabilities, including but not limited to broadband communication constellations (such as Starlink) and low-Earth orbit navigation enhancement constellations.
[0021] Observation type: Acquiring Doppler observations at multiple frequencies pseudorange observations And navigation messages or precise ephemeris.
[0022] Data preprocessing: To improve the reliability and consistency of the observation data, the following preprocessing operations are performed on the acquired multi-source observation data: Gross error removal: Taking advantage of the smooth change of Doppler observations over time, the time-difference method is used to detect Doppler observations of adjacent epochs, and statistical threshold criteria (such as the three-times standard error criterion) are combined to identify and remove outlier observations.
[0023] Elevation angle cutoff: Set the cutoff elevation angle threshold (e.g.) Data with severe multipath effects and excessive atmospheric noise at low altitude angles were excluded.
[0024] Orbital Altitude Classification: Based on the ephemeris calculation of the satellite's average orbital altitude, the observed data are divided into... A set of height layers ,in Representing the The average orbital altitude of constellations (e.g., 350km, 550km, 1200km levels).
[0025] Furthermore, the process of calculating the rate of change of the total electron content in the ionosphere includes: For dual-frequency signals, a dual-frequency geometric distance-free combination is used for solution; Alternatively, for three-frequency signals, a three-frequency linear combination that satisfies the constraints of geometric distance and receiver clock error can be used for solution.
[0026] Specifically, the implementation process of this embodiment includes: Step 2: Calculation of Sluggish Total Ionospheric Equilibrium (STEC) based on Doppler: Using Doppler observations, non-ionospheric terms such as geometric distance and clock bias are eliminated, the rate of change of total ionospheric electron content along the satellite-receiver line of sight is calculated, and the total tilted ionospheric content is further recovered.
[0027] (1) Dual-frequency combined solution model: For satellites with only dual-frequency signals, a geometry-free combination of the two frequencies is established. The original Doppler observation equation is: ; Where, in the formula, Indicates the first Doppler observations of frequency (unit: Hz); For the first The carrier wavelength of the frequency; This represents the geometric distance from the satellite to the receiver; Indicates time; This represents the relative line-of-sight velocity (geometric distance rate of change) between the satellite and the receiver. The speed of light; and These represent receiver clock bias and satellite clock bias, respectively. This indicates the frequency deviation introduced by the relative drift between the receiver and the satellite clock; The tropospheric delay, expressed in units of distance along the line of sight. This represents the rate of change of tropospheric delay over time. The ionospheric delay, expressed in units of distance, is the line-of-sight delay. This represents the rate of change of ionospheric delay over time. This includes unmodeled errors such as Doppler observation noise and multipath effects.
[0028] By linearly combining Doppler observations of different frequencies, a dual-frequency, geometrically distance-free combined observation set is constructed: ; Where, in the formula, This represents the combined observations of two frequencies without geometric distance (unit: m / s). These are the wavelengths of the first and second signal frequencies, respectively; The values are Doppler observations for the corresponding frequencies (unit: Hz).
[0029] The above combination eliminates the geometric distance and receiver clock error terms while retaining the ionospheric effect term. Based on this combined observation, the rate of change of total ionospheric electron content along the line-of-sight direction can be calculated: ; Step 2, (2) Three-frequency combination enhancement solution model: For those with tri-frequency signals ( To improve solution accuracy, a three-frequency universal geometric distance-free combination of observation equations is constructed based on the observation frequency characteristics. The following three-frequency linear combination observation equations are constructed: ; in, This represents the combined observation values of the three frequencies without geometric distance (unit: m / s). These are the carrier wavelengths at three different signal frequencies; The original Doppler observation values (unit: Hz) for the corresponding frequency points; The coefficients of the three-frequency linear combination are to be determined and must satisfy the constraints of geometric distance elimination and clock error elimination.
[0030] The combination coefficients must satisfy the following constraints: In the combination, the geometric distance terms cancel each other out; The receiver clock error term is eliminated in the combination; Under the premise of meeting the above conditions, the noise amplification factor of the combination is constrained or optimized.
[0031] By selecting the optimal combination of coefficients that satisfies the constraints, the sensitivity of the combined observations to the rate of change in the ionosphere is enhanced on the one hand, and the amplification effect of observation noise is suppressed on the other hand, thus obtaining a high-precision solution for the rate of change in the total electron content of the ionosphere. .
[0032] Furthermore, the process of integrating the rate of change in the time domain and correcting for the constant term includes: Numerical integration of the rate of change of total electron content in the ionosphere over consecutive epochs yields the total tilted ionosphere, including terms of undetermined constants. The constant term is determined by using the statistical mean of a geometrically inverse combination of pseudorange observations, or by using reference values provided by an empirical ionospheric model.
[0033] Specifically, the implementation process of this embodiment includes: Step 2, (3) Integration Restoration and Constant Determination: Since Doppler observations reflect the rate of change of the total electron content in the ionosphere, the total amount of tilted ionosphere needs to be recovered through time integration.
[0034] Time-domain integration: Numerical integration of the rate of ionospheric change over consecutive epochs yields the uncalibrated total tilted ionosphere. ; in, express Total electron content of the ionosphere at any given time, depending on the line of sight (unit: TECU). This is the starting epoch time of the current continuously observed arc segment; The current epoch time; This represents the rate of change in the total electron content of the ionosphere obtained from the aforementioned steps (i.e. or (This depends on the number of satellite signal frequency points). This is an undetermined integral constant term introduced due to the lack of absolute magnitude information in Doppler observations. This constant term remains unchanged over continuous arc segments.
[0035] Constant term correction: Method A (High Precision): Construct a geometrically inverse combination of pseudorange observations and take the statistical mean within the continuous satellite observation arc to determine the integral constant term.
[0036] Method B (non-collaborative / low-cost): Using empirical ionospheric models such as the Global Ionospheric Map (GIM) or IRI as the background field, selecting epochs with higher elevation angles within the satellite arc, and using the total tilted ionospheric volume provided by the model as a reference benchmark, the integral constant term is solved.
[0037] Furthermore, the vertical projection process includes: By using a single-layer mapping function, combined with the satellite elevation angle and satellite orbital altitude, the total amount of tilted ionosphere is converted into the total vertical electron content at the corresponding orbital altitude.
[0038] Specifically, the implementation process of this embodiment includes: Step 3: Vertical Projection and Layered 2D Mesh Construction: Vertical projection: Using a single-layer mapping function, the total electron content of the tilted ionosphere calculated along the satellite-receiver line-of-sight is converted into the vertical total electron content at the corresponding satellite orbital altitude. ; in, Indicates the calculation to satellite orbital altitude Vertical total electron content at a location (unit: TECU); The total amount of tilted ionosphere obtained from the aforementioned steps; To match the satellite elevation angle and track height The relevant single-layer mapping function is used to project the total tilt along the line of sight to the vertical direction. It should be noted that the total vertical electron content obtained here represents the cumulative total electron content from the Earth's surface to the satellite's orbital altitude h, not the total vertical electron content of the entire ionosphere.
[0039] Hierarchical gridding: For each pre-defined orbital altitude layer (e.g., 350km, 550km, 1200km, etc.), the total vertical electron content data corresponding to all satellite puncture points belonging to that orbital altitude layer are collected. At each orbital altitude layer, a spherical two-dimensional model of the total vertical electron content is performed to construct a cumulative two-dimensional ionospheric model for that altitude layer. Modeling methods include, but are not limited to, spherical harmonic function fitting or Kriging interpolation algorithms.
[0040] Furthermore, the process of performing interlayer differential calculus includes: Calculate the difference value of the cumulative two-dimensional ionospheric model between two adjacent height layers. The difference value represents the electron content information in the height interval between these two height layers.
[0041] Specifically, the implementation process of this embodiment includes: Step 4: Interlayer Differentiation and 3D Voxel Reconstruction By utilizing the difference information between the cumulative two-dimensional ionospheric models corresponding to different orbital altitudes, the structural features of the ionosphere in the vertical direction are inverted.
[0042] Interlayer difference: For two adjacent orbital height layers and Calculate its difference value: ; In the formula, Indicates the altitude at which the orbit is located. and Total electron content of the vertical ionosphere within the spherical shell layer (unit: TECU). and They respectively represent the reduction to the first Layer and first The cumulative vertical total electron content at the orbital height of the layer.
[0043] The above difference results characterize the position at orbital altitude Of Information on local electron content within the height range.
[0044] Furthermore, the process of performing 3D voxel mesh inversion includes: The average electron density is calculated based on the electron content of the height interval obtained from the interlayer difference and the corresponding thickness of the height interval. Within the specified height range, the vertical distribution function of the ionosphere is introduced as a constraint for fitting to refine the electron density distribution inside the shell.
[0045] Example 2 In this embodiment, a computer terminal device is provided, including: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the above-described method for constructing a three-dimensional ionospheric model based on Doppler observations from low-Earth orbit constellations.
[0046] In this embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the above-described method for constructing a three-dimensional ionospheric model based on Doppler observations from a low-Earth orbit constellation.
[0047] In this embodiment, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the above-described method for constructing a three-dimensional ionospheric model based on Doppler observations from a low-Earth orbit constellation.
[0048] This invention provides a method for constructing a three-dimensional ionospheric model based on Doppler observations from a low-Earth orbit (LEO) constellation. This method possesses the capability for detailed detection of the ionospheric vertical structure, overcoming the limitation of traditional methods that can only obtain vertical integral information of the ionosphere. By utilizing LEO satellites operating at different altitudes within the ionosphere for observation and employing interlayer difference and fusion techniques, this invention can resolve the detailed electron density distribution structure of the ionosphere in the vertical direction. The model is constructed based on cycle-slip-immune Doppler observations, exhibiting strong anti-interference capabilities and ensuring data continuity and model stability under strong ionospheric scintillation or complex electromagnetic environments. Furthermore, this invention eliminates the need for expensive dedicated monitoring facilities, achieving high spatiotemporal resolution three-dimensional ionospheric monitoring globally at a relatively low cost by utilizing widely distributed LEO constellation resources and commercial terminals.
[0049] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A method for constructing a three-dimensional model of the ionosphere based on Doppler observations from low-Earth orbit constellations, characterized in that, Includes the following steps: Acquire Doppler observations of dual-frequency or triple-frequency signals from various low-Earth orbit satellites at different orbital altitudes, and classify the observation data into different altitude layer sets according to the orbital altitude of each satellite; Based on the Doppler observations, the rate of change of total electron content in the ionosphere along the line of sight is calculated by constructing a geometric distance-free combination solution, and the rate of change is integrated in the time domain and corrected by a constant term to obtain the total amount of tilted ionosphere. The total tilted ionospheric content is vertically projected onto the orbital altitude of the corresponding satellite to obtain the vertical total electron content of each altitude layer. A spherical two-dimensional model is then performed on the vertical total electron content at each altitude layer to construct a cumulative two-dimensional ionospheric model for each altitude layer. Interlayer difference is performed on the cumulative two-dimensional ionospheric model of adjacent height layers to obtain the electron content of the corresponding height interval, and a three-dimensional voxel mesh is inverted based on the electron content to generate a three-dimensional model of ionospheric electron density.
2. The method according to claim 1, characterized in that, The process of acquiring and classifying observation data includes: The Doppler observations are preprocessed by removing outliers and truncating elevation angles; The average orbital altitude of the satellite is calculated based on the satellite ephemeris, and the preprocessed observation data is divided into multiple altitude layer sets corresponding to different average orbital altitudes.
3. The method according to claim 1, characterized in that, The process of calculating the rate of change of total electron content in the ionosphere includes: For dual-frequency signals, a dual-frequency geometric distance-free combination is used for solution; Alternatively, for three-frequency signals, a three-frequency linear combination that satisfies the constraints of geometric distance and receiver clock error can be used for solution.
4. The method according to claim 1, characterized in that, The process of integrating the rate of change in the time domain and correcting for the constant term includes: Numerical integration of the rate of change of total electron content in the ionosphere over consecutive epochs yields the total tilted ionosphere, including terms of undetermined constants. The constant term is determined by using the statistical mean of a geometrically inverse combination of pseudorange observations, or by using reference values provided by an empirical ionospheric model.
5. The method according to claim 1, characterized in that, The process of vertical projection includes: By using a single-layer mapping function, combined with the satellite elevation angle and satellite orbital altitude, the total amount of tilted ionosphere is converted into the total vertical electron content at the corresponding orbital altitude.
6. The method according to claim 1, characterized in that, The process of performing interlayer differential includes: Calculate the difference value of the cumulative two-dimensional ionospheric model between two adjacent height layers. The difference value represents the electron content information in the height interval between these two height layers.
7. The method according to claim 1, characterized in that, The process of performing 3D voxel mesh inversion includes: The average electron density is calculated based on the electron content of the height interval obtained from the interlayer difference and the corresponding thickness of the height interval. Within the specified height range, the vertical distribution function of the ionosphere is introduced as a constraint for fitting to refine the electron density distribution inside the shell.
8. A computer terminal device, characterized in that, include: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors perform the steps of the method as described in any one of claims 1-7.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.