Lightning penetration ionosphere electromagnetic identification method based on Zhangheng No.1 satellite
By using the lightning-penetrating ionospheric electromagnetic identification method based on the Zhangheng-1 satellite, and combining ground-based data with satellite electromagnetic field data, standardized processing and layered modeling were performed to solve the problems of identification accuracy and applicability, thus achieving efficient and accurate electromagnetic signal identification.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NAT INST OF NATURAL HAZARDS MINISTRY OF EMERGENCY MANAGEMENT OF CHINA
- Filing Date
- 2026-04-08
- Publication Date
- 2026-06-12
AI Technical Summary
Existing technologies have failed to effectively utilize the payload characteristics of the Zhangheng-1 satellite, resulting in limited accuracy and applicability of identifying electromagnetic signals of lightning penetrating the ionosphere. Furthermore, the lack of standardized data processing procedures makes it prone to misjudgment.
We adopted an electromagnetic identification method for lightning penetration of the ionosphere based on the Zhangheng-1 satellite. Combining ground-based lightning location data with six-component waveform data of the electromagnetic field in the ELF/VLF band of the satellite, we established a field coordinate system through standardized event location, data matching, coordinate transformation and parameter extraction. We used the SVD algorithm to extract multi-dimensional propagation feature parameters and performed ionospheric layer-by-layer modeling analysis to construct a joint consistency determination of propagation direction and spectral structure.
It significantly improves the accuracy and reliability of identifying electromagnetic signals of lightning penetrating the ionosphere, eliminates misjudgments, fully leverages the advantages of satellite observation, and provides practical technical support for the study of atmospheric-ionospheric coupling mechanisms.
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Figure CN122193715A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the technical field of electromagnetic identification methods for lightning penetrating the ionosphere, and particularly relates to an electromagnetic identification method for lightning penetrating the ionosphere based on the Zhang Heng-1 satellite. Background Technology
[0002] The analysis of the ionospheric penetration characteristics of lightning electromagnetic signals is crucial for space weather monitoring, ionospheric physics research, and the exploration of atmospheric-ionospheric coupling mechanisms. During the penetration of the ionosphere, the ELF / VLF band electromagnetic signals generated by lightning undergo complex interactions with ionospheric plasma and the geomagnetic field. Accurate identification of these propagation characteristics is essential for understanding signal propagation patterns and revealing the coupling physical mechanisms. Traditional identification methods, primarily based on ground-based observation data, are limited by geographical location, atmospheric environment, and ionospheric irregularities. These methods suffer from limited observation coverage, insufficient signal attenuation compensation, and difficulty in capturing global-scale lightning ionospheric penetration events. Furthermore, they lack specific processing procedures for satellite observation data, thus limiting their accuracy and applicability.
[0003] While existing satellite-based methods for identifying lightning electromagnetic signals have overcome the geographical limitations of ground-based observations, a dedicated identification system adapted to the characteristics of the Zhang Heng-1 low-orbit electromagnetic satellite payload has not yet been established. The inductive coil magnetometer and electric field detector onboard the satellite can acquire six-component electromagnetic field waveform data. However, existing methods have not designed standardized coordinate transformation and parameter extraction processes that take into account the characteristics of this data. Furthermore, most methods have not established a consistency determination mechanism between ionospheric layer modeling and measured propagation parameters. Relying solely on a single parameter to judge penetration characteristics is prone to misjudgment due to factors such as changes in ionospheric background parameters and wave field interference. This fails to fully leverage the observational advantages of the Zhang Heng-1 satellite and makes it difficult to achieve accurate and efficient identification of lightning penetration electromagnetic signals. Summary of the Invention
[0004] The purpose of this invention is to address the aforementioned technical problems by providing a method for electromagnetic identification of lightning penetrating the ionosphere based on the Zhang Heng-1 satellite.
[0005] In view of this, the present invention provides a method for electromagnetic identification of lightning penetrating the ionosphere based on the Zhang Heng-1 satellite, comprising the following steps: Step 1: Read the lightning records output by the ground-based lightning location system, obtain the lightning occurrence time and geographical coordinates, and generate two types of event constraint parameters: spatial limitation parameters and time window parameters; Step 2: Based on the lightning occurrence time, geographical coordinates, and time window from Step 1, extract matching satellite observation data from the electromagnetic field observation data of Zhang Heng-1 satellite to form an electromagnetic observation dataset to be analyzed. Step 3: Based on the space reference benchmark in Step 1 and the satellite observation segment in Step 2, call the background model to obtain ionospheric and geomagnetic field parameters, and organize them into a background parameter package; Step 4: Call the electromagnetic field waveform data of Zhang Heng-1 satellite, establish the magnetic field aligned coordinate system MFAC and complete the coordinate transformation of electromagnetic field components, calculate the power spectral density and save the processed data; Step 5: Calculate the wave propagation parameters using the SVD method in the MFAC coordinate system. The propagation parameters include at least the power spectral density PSD, elliptic polarizability, wave normal angle θk, azimuth angle ϕk, planarity, and the parallel and perpendicular components of the Poynting vector. Step Six: Based on the background parameters in Step Three, perform layered modeling analysis on the propagation of electromagnetic disturbances in the ionosphere. In the lower layer, FDTD is used to calculate Joule heating and equivalent attenuation, and in the upper layer, FWM is used for spatial domain solution. The results are then compiled into a layered modeling result set. Step 7: Perform a consistency analysis on the propagation direction and spectral structure of the measured propagation parameters from Step 5 and the modeling results from Step 6, and use a joint criterion to determine whether the measured electromagnetic signal meets the penetration determination condition. Step 8: Based on the consistency analysis results of Step 7, output the identification results of whether lightning-related electromagnetic signals have the characteristic of penetrating the ionosphere.
[0006] Preferably, in step one, the ground-based lightning location system is a global lightning location network or a regional lightning detection network; The spatial limitation parameters are set with the lightning's latitude and longitude as the center, and are represented by a radius range or a latitude and longitude window; The time window is set centered on the time of lightning occurrence and is represented by the start and end times.
[0007] Preferably, in step two, satellite observation data matching includes three sub-steps: time matching, spatial matching, and forming an electromagnetic observation dataset to be analyzed. The time matching process involves extracting the corresponding observation record from the satellite electromagnetic field observation data according to the time window in step one, obtaining the satellite observation segment and recording the start and end times; The spatial matching involves reading the satellite orbit latitude and longitude or the surface projection latitude and longitude of satellite observation segments and eliminating records that do not fall within the spatial limit range of step one. The electromagnetic observation dataset to be analyzed includes at least electromagnetic field waveform data, observation time information and segment start and end times, satellite orbit latitude and longitude or Earth surface projection latitude and longitude, event identifiers, time windows and spatial limitation range parameters.
[0008] Preferably, in step three, the background parameter is taken at the latitude and longitude of the lightning center in step one, and at the midpoint of the observation period in step two. Based on the preset lower and upper limits of height and height step size, a discrete height grid is generated. Under the corresponding time, location and height range conditions, the electron density profile and collision frequency profile are obtained by calling the ionospheric empirical model, and the geomagnetic field vector parameters are obtained by calling the geomagnetic field model or equivalent geomagnetic field data source. The background parameter package includes at least the event identifier, center latitude and longitude, representative time, preset altitude range and altitude step size, discrete altitude grid, electron density profile, collision frequency profile, and geomagnetic field vector parameters.
[0009] Preferably, in step four, the waveform data of the three components of the electric field and the three components of the magnetic field of the Zhang Heng-1 satellite and their sampling information are read; The magnetic field alignment coordinate system is established as follows: the Z-axis is along the direction of the background magnetic field, the Y-axis is defined by the cross product of the Z-axis and the satellite position vector and points eastward, the Y-axis is taken as the direction of the cross product of the Z-axis and the satellite position vector, and the X-axis is supplemented as a right-handed system. Calculate the power spectral density of the waveform in the MFAC coordinate system with a fixed window length and step size, and save the waveform data and power spectral density results after coordinate transformation, along with the event identifier and observation segment identifier.
[0010] Preferably, in step five, the calculation and discrimination rules for each propagation parameter are as follows: Based on the electromagnetic field waveform under MFAC, points below a preset threshold can be eliminated. According to the SVD algorithm, positive values are right-handed, negative values are left-handed, and values close to 0 are linear polarization. The wave vector direction is calculated using the SVD algorithm. The azimuth angle ϕk is the angle between the projection direction of the wave vector onto the X–Y plane of the MFAC and the X-axis, with a value range of... Up to 180°; or 90°≤ ≤180° is inward towards the Earth. Towards the outside; 0°≤ ≤180° is eastward. To the west, combining wave properties and a priori rules eliminates the inherent ambiguity of the magnetic field SVD in the ±180° direction of the wave vector; The output of SVD serves as an auxiliary indicator of the reliability of propagation parameters. The Poynting flux is calculated and decomposed into a parallel component along the background magnetic field and a perpendicular component to the background magnetic field.
[0011] Preferably, in step six, the modeling region of the layered modeling is divided into a lower layer and an upper layer, with the top height of layer D (approximately 90 km) as the boundary. The modeling parameters include at least the electron density profile, the collision frequency profile, and the background geomagnetic field vector. The layered modeling result set includes at least the following: the Joule heating cumulative distribution and equivalent attenuation characterization quantity in the lower layer, the model power spectral density at the orbital height, the model Poynting flux at the orbital height and its parallel / vertical components, and is bound and recorded with event identifiers, background parameter versions, modeling height range, layer D boundary height, and height step information.
[0012] Preferably, in step seven, the propagation direction consistency analysis includes at least comparing the propagation direction's relative to the background magnetic field, as reflected by the wave normal angle θk, to determine whether it is partially parallel or partially perpendicular, and the azimuth angle. The propagation orientation reflected is related to the direction of the modeled energy flow in the meridional plane, and the dominance of the parallel / vertical components of the Poynting flux relative to the background magnetic field. Spectral structure consistency analysis includes at least comparing the main frequency band positions, spectral width range and band structure correspondence between the measured PSD and the model PSD. The PSD can be compared after uniform normalization, and the differences in spectral intensity can be explained by combining the D-layer attenuation and Joule heating results. The joint criterion is that when both the consistency of propagation direction and the consistency of spectral structure are satisfied, the measured electromagnetic signal is determined to meet the penetration determination condition; otherwise, it is determined that the condition is not met or the evidence is insufficient. The basis for the determination, the consistency conclusion, and the final penetration determination conclusion are recorded.
[0013] Preferably, the recognition result in step eight is represented in two forms: a binary determination result and a quantitative parameter characterizing the degree of penetration.
[0014] Preferably, the hardware platform and software environment for implementing this method include: a satellite payload data module for acquiring six-component electromagnetic field waveform data in the ELF / VLF band recorded by the inductive coil magnetometer (SCM) and electric field detector (EFD) of the Zhang Heng-1 satellite; a high-performance computing server for performing large-scale numerical simulation and matrix decomposition operations; and an external data interface for acquiring lightning parameters from the Global Lightning Location Network (WWLLN). The software environment includes an FDTD time-domain simulation program written in C language for calculating the dynamic ionospheric permeation process of lightning pulses, a Fortran language environment modeling program that integrates the IRI model, and a MATLAB core algorithm program that includes the SVD feature extraction algorithm and the FWM calculation program.
[0015] The beneficial effects of this invention are as follows: This method designs a dedicated electromagnetic identification process for the payload characteristics of the Zhangheng-1 satellite. Combining ground-based lightning location data with the six-component waveform data of the satellite's ELF / VLF band electromagnetic field, it establishes a field-oriented coordinate system through standardized event location, data matching, coordinate transformation, and parameter extraction steps to achieve data standardization. By using the SVD algorithm, it accurately extracts multi-dimensional propagation characteristic parameters, including polarization type, propagation direction, and Poynting flux. This solves the problems of poor adaptability, lack of unified standards for data processing, and incomplete parameter extraction in traditional methods, significantly improving the analytical accuracy and effective utilization rate of the satellite's measured electromagnetic data, and fully leveraging the observation advantages of the Zhangheng-1 low-orbit electromagnetic satellite.
[0016] This innovative method employs a layered ionospheric modeling and analysis strategy. The FDTD algorithm is used to quantify energy loss in the D layer, while the FWM algorithm is used in the upper layer to achieve accurate spatial domain solutions. This recreates the true propagation process of lightning electromagnetic signals in the ionosphere. Simultaneously, a joint consistency determination mechanism for propagation direction and spectral structure is constructed, replacing the traditional single-parameter judgment method. This effectively eliminates misjudgments caused by ambiguity in magnetic field SVD, changes in ionospheric background parameters, and wavefield interference. Combined with a dedicated hardware platform and a multi-language collaborative software environment, efficient linkage between data processing, numerical simulation, and result determination is achieved. This significantly improves the accuracy and reliability of identifying lightning-penetrating ionospheric electromagnetic signals, providing practical technical support for research on atmospheric-ionospheric coupling mechanisms and space weather monitoring and early warning. Attached Figure Description
[0017] Figure 1 This diagram illustrates the data sources and programming languages involved in the embodiments of the present invention.
[0018] Figure 2 This is a technical roadmap for the lightning penetration ionospheric electromagnetic identification method based on the Zhang Heng-1 satellite, provided in an embodiment of the present invention. Detailed Implementation
[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.
[0020] This invention provides a method for analyzing the ionospheric penetration of lightning energy based on the low-orbit electromagnetic satellite Zhangheng-1 and ground-based observation data. This method combines relevant data processing algorithms and numerical simulation algorithms to analyze the ionospheric penetration characteristics of lightning-related electromagnetic signals.
[0021] System hardware platform and software environment; Hardware platform components: Zhang Heng-1 satellite payload data: Acquired six-component electromagnetic field waveform data in the ELF / VLF band recorded by the inductive magnetometer (SCM) and electric field meter (EFD).
[0022] High-performance computing servers: used to perform large-scale numerical simulations and matrix factorization operations.
[0023] External data interface: Obtain lightning time, location, and current parameters provided by the Global Lightning Location Network (WWLLN).
[0024] Software environment: Time-domain simulation program (C language): The FDTD (Finite-Difference Time-Domain) program, written in C language, is used to calculate the dynamic penetration process of lightning pulses in the ionosphere.
[0025] Environmental modeling program (Fortran language): Integrates an IRI (International Reference Ionosphere) model written in Fortran for calculating background medium parameters.
[0026] Core Algorithm Program (MATLAB): Includes SVD (Singular Value Decomposition) feature extraction algorithm and Full Wave Method calculation program written in MATLAB.
[0027] Technical implementation logic: The system collects raw electromagnetic data from the Zhangheng-1 satellite and inputs it into the server. In the software workflow, an FDTD program written in C and a full-wave solution program written in MATLAB are used to jointly simulate the propagation process of lightning energy. Simultaneously, the SVD algorithm in the MATLAB environment is used to analyze the characteristics of the satellite's measured data. Finally, by combining the dispersion relation environment provided by the IRI model written in Fortran, the measured and simulated results are compared to determine the physical mechanism by which lightning penetrates the ionosphere.
[0028] This invention provides a method for identifying the characteristics of lightning propagating through the ionosphere, the method comprising the following steps: Step 1: Spatial localization of the lightning event; Read the lightning records output by the ground-based lightning location system, obtain the lightning occurrence time and geographical coordinates (longitude and latitude), and generate the event constraint parameters required for subsequent satellite data matching: spatial constraint parameters and time window.
[0029] Ground-based lightning location systems can be global lightning location networks or regional lightning detection networks. Spatial constraint parameters are set with the lightning's latitude and longitude as the center to limit the spatial matching range of subsequent satellite observation data; the spatial constraint parameters can be expressed as a radius range or a latitude and longitude window.
[0030] A time window is set with the time of the lightning occurrence as the center. The time window is represented by the start and end times and is used to extract the observation period corresponding to the lightning event from the satellite observation data.
[0031] Step 2: Satellite observation data matching; Based on the lightning occurrence time, lightning geographic coordinates, and time window output in Step 1, satellite observation data corresponding to the lightning event is extracted from low-Earth orbit electromagnetic satellite electromagnetic field observation data to form an electromagnetic observation dataset to be analyzed. Step 2 outputs: satellite observation data segments organized by event identifier and matching information.
[0032] (1) Time matching; According to the time window given in step one, extract the observation records that fall within the time window from the satellite electromagnetic field observation data to obtain the satellite observation segment corresponding to the event, and record the start and end times of the segment.
[0033] (2) Spatial matching; Read the satellite orbital latitude and longitude (or surface projection latitude and longitude) corresponding to the above satellite observation segments, and determine whether they fall within the spatial limitation range given in step one; records that fall within the range are retained, and records that do not fall within the range are discarded.
[0034] (3) Generate the electromagnetic observation dataset to be analyzed; Satellite observation records that meet the time and space matching conditions are compiled into an electromagnetic observation dataset for analysis. The dataset must contain at least: 1) Electromagnetic field observation data (time series of one or more components of electric / magnetic field); 2) Observation time information and the start and end times of the segment; 3) Satellite orbital latitude and longitude (or Earth's surface projection latitude and longitude); 4) Event identifier; 5) Time window and spatial limitation range parameters.
[0035] Step 3: Obtain background parameters; Based on the spatial reference benchmark given in step one, and combined with the satellite observation segment determined in step two, the background model is directly called to obtain ionospheric and geomagnetic field parameters under specified time and location conditions, and these parameters are compiled into a background parameter package for subsequent propagation parameter calculation and propagation modeling.
[0036] The background parameter values and times are determined as follows: Spatially, the latitude and longitude of the lightning center in step one are used as the input location for the background model; temporally, the midpoint of the observation segment in step two is used as the representative time, and this representative time and the start and end times of the observation segment are recorded. Then, preset lower and upper limits of height and height step size are set to generate a discrete height grid. Under the conditions of time, location, and height range, the ionospheric empirical model is called to obtain the electron density profile and collision frequency profile; the geomagnetic field model or equivalent geomagnetic field data source is called to obtain the geomagnetic field vector parameters corresponding to the height grid, and its coordinate system aperture is recorded to ensure consistency with subsequent MFAC establishment.
[0037] Step 3 outputs a background parameter package, which includes at least: event identifier, center latitude and longitude, representative time, preset altitude range and altitude step size, discrete altitude grid, electron density profile, collision frequency profile, and geomagnetic field vector parameters.
[0038] Step 4: Electromagnetic observation data preprocessing; Based on the observation orbit segment obtained in step two, electromagnetic field waveform data released by the Zhangheng-1 satellite is called to form input data for power spectral density calculation and SVD propagation parameter calculation.
[0039] The waveform data and sampling information of the three components of the electric field and magnetic field for this orbital segment are read. A magnetic field-aligned coordinate system is established using the background magnetic field vector provided by the satellite and the orbital position parameters: the Z-axis is along the direction of the background magnetic field; the Y-axis is the cross product of the Z-axis and the satellite position vector; the X-axis is a right-handed coordinate system. The electric and magnetic field waveform components are transformed into the magnetic field-aligned coordinate system, serving as unified data for subsequent propagation parameter calculations.
[0040] In the field coordinate system, the power spectral density of the waveform for this orbital segment is calculated using a fixed window length and step size to obtain the spectral structure result of this orbital segment. The calculation configuration, such as the window length and step size, is recorded. The waveform data after the above coordinate transformation and its power spectral density result are saved in correspondence with the event identifier and observation segment identifier for direct calculation of propagation parameters in step five.
[0041] Step 5: Extraction of propagation feature parameters; Based on the electromagnetic field waveform data obtained in step four, singular value decomposition (SVD) is used in the field-oriented coordinate system (MFAC) to calculate wave propagation parameters, which are used to determine the propagation direction and polarization type of the electromagnetic disturbance. The propagation parameters include at least: power spectral density (PSD), elliptic polarizability, wave normal angle θk, and azimuth angle. Planarity and the parallel and perpendicular components of the Poynting vector.
[0042] (1) PSD calculation; The PSD is calculated from the electromagnetic field waveform under MFAC to provide the spectral structure of the target disturbance. To highlight the target structure, points with PSD below a preset threshold can be excluded from display or plotting, and the threshold used can be recorded in the results.
[0043] (2) Elliptic polarizability and polarization type; The elliptic polarizability is calculated using the SVD algorithm, and its value is used to determine the polarization type: positive values correspond to right-handed polarization, negative values correspond to left-handed polarization, and values close to 0 correspond to linear polarization.
[0044] (3) Wave normal and azimuth; The wave vector direction is calculated using the SVD algorithm, and two angle parameters are given: Wave normal angle θk: The wave propagation direction parameter is calculated using the SVD method in the MFAC coordinate system, and two angle parameters are given; Azimuth Defined as the angle between the projection direction of the wave vector onto the X–Y plane of the MFAC and the X-axis, with a value range of... Up to 180°; Used to describe propagation "inward / outward" within the meridian plane and "eastward / westward" in the azimuth direction.
[0045] (4) The rules for determining the direction of propagation; Based on the distinction within the meridian plane: or 90°≤ ≤180°: corresponds to the direction of decreasing L value (inward towards the Earth); -90°≤ ≤90°: corresponds to the direction of increasing L value ("outward").
[0046] Determining by direction: 0°≤ ≤180°: Eastward; -180°≤ ≤0°: Westward.
[0047] It should also be noted that the magnetic field SVD has an inherent ambiguity of ±180° in the wave vector direction. When necessary, a reasonable directional branch should be selected by combining wave properties and a priori rules.
[0048] (5) Flatness; The plane wave characteristics parameters output by SVD are used to characterize whether the observed wavefield satisfies the approximate plane wave condition, serving as an auxiliary indicator of the reliability of propagation parameters.
[0049] (6) Poynting vector and its components; The Poynting flux is calculated and decomposed into a parallel component along the direction of the background magnetic field and a perpendicular component perpendicular to the direction of the background magnetic field, which is used to characterize the directional relationship of the energy flux relative to the background magnetic field.
[0050] (7) Results are formed; We obtain PSD, elliptic polarizability, θk, The plane wave characteristics and Poynting flux parallel / vertical components are bound to the event identifier and observation segment identifier, and used as inputs for the consistency determination in step seven.
[0051] Step Six: Propagation Modeling and Analysis; Based on the ionospheric background parameters and geomagnetic field parameters obtained in step three, a layered modeling analysis of the propagation of electromagnetic disturbances in the ionosphere is performed: within the D-layer height range, Joule heating is calculated using finite-difference time-domain (FDTD) and equivalent attenuation is given to illustrate the energy loss of electromagnetic disturbances in the lower ionosphere; above the D-layer, the full-wave solution method (FWM) based on horizontally layered media is used for spatial domain solution, and the power spectral density and Poynting flux are calculated at the satellite orbital altitude to provide comparable modeling results for step seven.
[0052] (1) Layering range and background parameters; Based on the altitude range, step size, and D-layer boundary altitude given in step three, the modeling region is divided into a lower-layer region (dominated by the D-layer) and an upper-layer region (above the D-layer, covering up to the satellite orbital altitude). The modeling parameters are provided in step three and include at least the electron density profile, collision frequency profile, and background geomagnetic field vector.
[0053] (2) Lower layer region: FDTD loss calculation; In the lower layer region, FDTD is used for time-domain solution to obtain the cumulative distribution of Joule heating with height; and based on this, an equivalent attenuation characterization quantity is given to reflect the overall attenuation effect of the D layer on electromagnetic disturbances.
[0054] (3) Upper region: FWM spatial domain solution (horizontal layering); In the upper region, a full-wave method is used for spatial domain solution. The full-wave method introduces electron density, collision frequency, and background geomagnetic field parameters layer by layer according to the horizontal stratification assumption to solve for the propagation of electromagnetic disturbances in the stratified medium. Model results that can be directly compared with observations are extracted at the satellite orbital altitude, including at least the power spectral density and Poynting flux at the orbital altitude, and the parallel and perpendicular components of the Poynting flux relative to the background magnetic field are given.
[0055] (4) Results organization and recording; A hierarchical modeling result set is generated and recorded along with information such as event identifiers, background parameter versions, modeling height range, D-layer boundary height, and height step size. The modeling results should include at least: the cumulative distribution of Joule heating and equivalent attenuation characteristics in the lower layer; the model power spectral density at orbital height; and the model Poynting flux and its parallel / vertical components at orbital height.
[0056] Step 7: Feature consistency determination; The measured propagation parameters obtained in step five are compared with the modeling results obtained in step six to determine whether the measured electromagnetic signal meets the penetration criteria. The consistency analysis includes at least consistency in propagation direction and consistency in spectral structure, and a joint criterion is used to give a conclusion.
[0057] (1) Consistency analysis of propagation direction; Compare the measured propagation parameters with the modeling results to see if the energy flow direction at the orbital altitude is consistent, including at least: The direction of propagation reflected by the wave normal angle θk is either parallel or perpendicular to the background magnetic field; Azimuth The propagation orientation reflected is related to the direction of the modeled energy flow in the meridional plane; for the ambiguity of ±180° in magnetic field SVD, a reasonable directional branch is selected based on wave properties and prior constraints before judgment; Whether the directionality of the Poynting flux relative to the background magnetic field is consistent, with a focus on comparing the dominance of the parallel and perpendicular components.
[0058] (2) Spectral structure consistency analysis; Compare the spectral structure of the measured PSD with that of the model PSD to determine if they are consistent, including at least the correspondence between the main frequency band positions, spectral width range, and band structure. If necessary, the PSD can be normalized before comparing the spectral shapes to reduce the impact of absolute amplitude differences. The D-layer attenuation and Joule heating results obtained in step six are used to explain the sources of spectral intensity differences.
[0059] (3) Joint criteria and penetration determination; When both the consistency of propagation direction and the consistency of spectral structure are satisfied, the measured electromagnetic signal is determined to meet the penetration determination condition; otherwise, it is determined that the condition is not met or the evidence is insufficient. The determination criteria are recorded together.
[0060] (4) Results recording; Record the consistency conclusions of propagation direction, spectral structure, and final penetration determination, and save key comparison charts or key parameter tables for verification.
[0061] Step 8: Output the penetration recognition results; Based on the consistency analysis results, the system outputs an identification result indicating whether lightning-related electromagnetic signals possess the characteristic of propagating through the ionosphere.
[0062] 1. The recognition result can be represented as a binary determination result.
[0063] 2. The identification result can also be expressed as a quantitative parameter characterizing the degree of penetration.
[0064] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.
Claims
1. A lightning penetration ionospheric electromagnetic identification method based on the Zhang Heng-1 satellite, characterized in that: Includes the following steps: Step 1: Read the lightning records output by the ground-based lightning location system, obtain the lightning occurrence time and geographical coordinates, and generate two types of event constraint parameters: spatial limitation parameters and time window parameters; Step 2: Based on the lightning occurrence time, geographical coordinates, and time window from Step 1, extract matching satellite observation data from the electromagnetic field observation data of Zhang Heng-1 satellite to form an electromagnetic observation dataset to be analyzed. Step 3: Based on the space reference benchmark in Step 1 and the satellite observation segment in Step 2, call the background model to obtain ionospheric and geomagnetic field parameters, and organize them into a background parameter package; Step 4: Call the electromagnetic field waveform data of Zhang Heng-1 satellite, establish the field coordinate MFAC and complete the electromagnetic field component coordinate transformation, calculate the power spectral density and save the processed data; Step 5: Calculate the wave propagation parameters using the SVD method in the MFAC coordinate system. These propagation parameters include at least the power spectral density (PSD), elliptic polarizability, wave normal angle θk, and azimuth angle. Planarity and the parallel and perpendicular components of the Poynting vector; Step Six: Based on the background parameters in Step Three, perform layered modeling analysis on the propagation of electromagnetic disturbances in the ionosphere. In the lower ionosphere, the finite-difference time-domain method is used to calculate Joule heating and equivalent attenuation, while in the upper region, the full-wave solution algorithm is used for spatial domain solution. The results are then compiled into a layered modeling result set. Step 7: Perform a consistency analysis on the propagation direction and spectral structure of the measured propagation parameters from Step 5 and the modeling results from Step 6, and use a joint criterion to determine whether the measured electromagnetic signal meets the penetration determination condition. Step 8: Based on the consistency analysis results of Step 7, output the identification results of whether lightning-related electromagnetic signals have the characteristic of penetrating the ionosphere.
2. The method for electromagnetic identification of lightning penetrating the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: In step one, the ground-based lightning location system is a global lightning location network or a regional lightning detection network; The spatial limitation parameters are set with the lightning's latitude and longitude as the center, and are represented by a radius range or a latitude and longitude window; The time window is set centered on the time of lightning occurrence and is represented by the start and end times.
3. The electromagnetic identification method for lightning penetration of the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: In step two, satellite observation data matching includes three sub-steps: time matching, spatial matching, and forming an electromagnetic observation dataset to be analyzed. The time matching process involves extracting the corresponding observation record from the satellite electromagnetic field observation data according to the time window in step one, obtaining the satellite observation segment and recording the start and end times; The spatial matching involves reading the satellite orbit latitude and longitude or the surface projection latitude and longitude of satellite observation segments and eliminating records that do not fall within the spatial limit range of step one. The electromagnetic observation dataset to be analyzed includes at least electromagnetic field waveform data, observation time information and segment start and end times, satellite orbit latitude and longitude or Earth surface projection latitude and longitude, event identifiers, time windows and spatial limitation range parameters.
4. The electromagnetic identification method for lightning penetration of the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: In step three, the background parameter values are taken from the latitude and longitude of the lightning center in step one, and the time of taking the values is the midpoint of the observation segment in step two. Based on the preset lower and upper limits of height and height step size, a discrete height grid is generated. Under the corresponding time, location and height range conditions, the electron density profile and collision frequency profile are obtained by calling the ionospheric empirical model, and the geomagnetic field vector parameters are obtained by calling the geomagnetic field model or equivalent geomagnetic field data source. The background parameter package includes at least the event identifier, center latitude and longitude, representative time, preset altitude range and altitude step size, discrete altitude grid, electron density profile, collision frequency profile, and geomagnetic field vector parameters.
5. The electromagnetic identification method for lightning penetration of the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: In step four, the waveform data of the three components of the electric field and the three components of the magnetic field of the Zhang Heng-1 satellite and their sampling information are read. The field coordinate system is established as follows: the Z-axis is along the direction of the background magnetic field, the Y-axis is the cross product of the Z-axis and the satellite position vector, and the X-axis is supplemented with a right-handed coordinate system. Calculate the power spectral density of electric and magnetic field waveform data in the MFAC coordinate system with a fixed window length and step size, and save the waveform data and power spectral density results after coordinate transformation, along with the event identifier and observation segment identifier.
6. The electromagnetic identification method for lightning penetration of the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: In step five, the calculation and discrimination rules for each propagation parameter are as follows: Based on the electromagnetic field waveform under MFAC, points below a preset threshold can be eliminated. According to the SVD algorithm, positive values are right-handed, negative values are left-handed, and values close to 0 are linear polarization. The azimuth angle is obtained by calculating the wave vector direction using the SVD algorithm. Let be the angle between the projection direction of the wave vector onto the X–Y plane of the MFAC and the X-axis, with a range of values. Up to 180°; -180°≤ ≤-90° or 90°≤ ≤180° means towards the Earth and inwards, -90°≤ ≤90° is outward; 0°≤ ≤180° is eastward, -180°≤ ≤0° represents the westward direction. Combining wave properties and a priori rules, the inherent ambiguity of the magnetic field SVD in the ±180° direction of the wave vector is eliminated. The output of SVD serves as an auxiliary indicator of the reliability of propagation parameters. Calculate the Poynting vector and decompose it into a parallel component along the background magnetic field and a perpendicular component to the background magnetic field.
7. The electromagnetic identification method for lightning penetration of the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: In step six, the modeling region of the layered modeling is divided into a lower layer and an upper layer, with the top height of layer D (approximately 90 km) as the boundary. The modeling parameters include at least the electron density profile, the collision frequency profile, and the background geomagnetic field vector. The layered modeling result set includes at least the following: the cumulative distribution of Joule heating in the ionospheric layer D and the equivalent attenuation characterization quantity, the model power spectral density at the orbital height, the model Poynting flux at the orbital height and its parallel / vertical components, and is bound and recorded with event identifiers, background parameter versions, modeling height range, the upper boundary height of layer D, and height step information.
8. The method for electromagnetic identification of lightning penetrating the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: In step seven, the propagation direction consistency analysis includes at least comparing the propagation direction's relative to the background magnetic field, as reflected by the wave normal angle θk, to determine whether it is partially parallel or partially perpendicular, and the azimuth angle. The propagation orientation reflected is related to the direction of the modeled energy flow in the meridional plane, and the dominance of the parallel / vertical components of the Poynting flux relative to the background magnetic field. Spectral structure consistency analysis includes at least comparing the main frequency band positions, spectral width range and band structure correspondence between the measured PSD and the model PSD. The PSD can be compared after uniform normalization, and the differences in spectral intensity can be explained by combining the D-layer attenuation and Joule heating results. The joint criterion is that when both the consistency of propagation direction and the consistency of spectral structure are satisfied, the measured electromagnetic signal is determined to meet the penetration determination condition; otherwise, it is determined that the condition is not met or the evidence is insufficient. The basis for the determination, the consistency conclusion, and the final penetration determination conclusion are recorded.
9. The electromagnetic identification method for lightning penetration of the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: The recognition results described in step eight can be represented in two forms: binary determination results and quantitative parameters characterizing the degree of penetration.
10. The electromagnetic identification method for lightning penetration of the ionosphere based on the Zhang Heng-1 satellite according to claim 1, characterized in that: The hardware platform and software environment for implementing this method include: a satellite payload data module for acquiring six-component electromagnetic field waveform data in the ELF / VLF band recorded by the inductive coil magnetometer (SCM) and electric field detector (EFD) of the Zhang Heng-1 satellite; a high-performance computing server for performing large-scale numerical simulation and matrix decomposition operations; and an external data interface for acquiring lightning parameters from the Global Lightning Location Network (WWLLN). The software environment includes an FDTD time-domain simulation program written in C language for calculating the dynamic ionospheric permeation process of lightning pulses, a Fortran language environment modeling program that integrates the IRI model, and a MATLAB core algorithm program that includes the SVD feature extraction algorithm and the FWM calculation program.