Solar flare intensity determination method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a solar flare intensity determination method and device, electronic equipment and a storage medium. The method comprises the steps that solar flare data and original observation data of a receiver are acquired; resolving the original observation data to obtain an electron time sequence corresponding to the ionized layer; smoothing the electronic time sequence to obtain a processed electronic time sequence; according to the solar flare data and the processed electronic time sequence, calculating the disturbance intensity grade of the solar flare on the electronic time sequence; and determining the intensity of the solar flare corresponding to the to-be-detected moment based on the disturbance intensity grade and the correlation of the solar flare data. According to the scheme, the accuracy of monitoring the solar flare intensity can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, electronic device and storage medium for determining the intensity of a solar flare. Background Art

[0002] Solar flares are one of the most powerful explosive phenomena in solar activity. They are sudden events in the process of reconnection of the magnetic field on the surface of the sun, which can release huge energy, including electromagnetic radiation, particle radiation (such as protons and electrons), as well as X-rays and ultraviolet rays. These radiation and particle flows propagate to the earth and have a significant impact on the earth's ionosphere.

[0003] The ionosphere is a region in the Earth's atmosphere, located between about 50 km and 1000 km in altitude, containing a large number of free electrons and ions. The intense radiation released during a solar flare can increase the ionization rate in the ionosphere, especially when the flare reaches near-Earth space. The increase in ultraviolet and X-ray radiation can cause a significant increase in the electron density of the E layer (about 90-150 km altitude) and the F layer (about 150-500 km altitude) in the ionosphere. This phenomenon is called "Sudden Ionospheric Disturbance" (SID).

[0004] Although many solar observation satellites are able to monitor the intensity of solar flares in real time or near real time, most solar observation satellites can only monitor the sun from a specific viewing angle, which limits the understanding of the overall picture of the sun and results in poor accuracy in the monitored solar flare intensity. Summary of the invention

[0005] The embodiments of the present application provide a solar flare intensity determination system, method, electronic device, and storage medium, which can improve the accuracy of monitored solar flare intensity.

[0006] In a first aspect, an embodiment of the present application provides a method for determining the intensity of a solar flare, comprising:

[0007] Obtain solar flare data and raw observation data from receivers;

[0008] Solving the original observation data to obtain an electron time series corresponding to the ionosphere;

[0009] Performing smoothing processing on the electronic time series to obtain a processed electronic time series;

[0010] Calculating the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series;

[0011] Based on the disturbance intensity level and the correlation of the solar flare data, the intensity of the solar flare corresponding to the time to be detected is determined.

[0012] Optionally, in some embodiments of the present application, the solving the original observation data to obtain the electron time series corresponding to the ionosphere includes:

[0013] Obtain precise ephemeris and satellite clock errors;

[0014] Extracting original pseudorange and carrier phase from the original observation data;

[0015] Constructing original pseudorange and carrier phase observation equations according to the original pseudorange, carrier phase, precise ephemeris and satellite clock error;

[0016] The original observation data is solved based on the original pseudorange and carrier phase observation equation to obtain an electron time series corresponding to the ionosphere.

[0017] Optionally, in some embodiments of the present application, solving the original observation data based on the original pseudorange and carrier phase observation equation to obtain an electron time series corresponding to the ionosphere includes:

[0018] Reorganizing the original pseudorange and carrier phase observation equations based on parameter reorganization to obtain an ionospheric delay expression;

[0019] Get the preset differential encoding deviation;

[0020] The original observation data is solved according to the ionospheric delay expression and the differential coding deviation to obtain the electronic time series corresponding to the ionosphere.

[0021] Optionally, in some embodiments of the present application, the smoothing of the electronic time series to obtain a processed electronic time series includes:

[0022] Get the preset filter;

[0023] Determine the polynomial order and window size;

[0024] The electronic time series is smoothed according to the filter, the polynomial order and the window size to obtain a processed electronic time series.

[0025] Optionally, in some embodiments of the present application, calculating the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series includes:

[0026] determining an electron content map corresponding to the processed electron time series;

[0027] Based on the processed electron time series and electron content map, a disturbance intensity level model corresponding to the solar flare is established;

[0028] The disturbance intensity level of the solar flare on the electronic time series is calculated according to the disturbance intensity level model.

[0029] Optionally, in some embodiments of the present application, establishing a disturbance intensity level model corresponding to a solar flare based on the processed electron time series and electron content map includes:

[0030] Determine, in the processed electronic time series, a deviation point of the ionosphere from a preset value and a peak point corresponding to the deviation peak value;

[0031] Determining the disturbance angle between the starting point and the peak point of the ionospheric disturbance according to the deviation point and the electron content map;

[0032] Based on the processed electron time series, disturbance angle and electron content map, a disturbance intensity level model corresponding to the solar flare is established.

[0033] Optionally, in some embodiments of the present application, determining the intensity of the solar flare corresponding to the time to be detected based on the correlation between the disturbance intensity level and the solar flare data includes:

[0034] Dividing the disturbance intensity level into a plurality of preset levels;

[0035] Extracting solar flare disturbance events within a preset time from the solar flare data;

[0036] Establishing a correlation relationship between the solar flare disturbance event and a preset level according to the peak intensity corresponding to the solar flare event;

[0037] Based on the preset statistical method and the association relationship, the correlation between the disturbance intensity level and the solar flare data is constructed, and the intensity of the solar flare corresponding to the time to be detected is determined based on the correlation.

[0038] In a second aspect, an embodiment of the present application provides a solar flare intensity determination device, comprising:

[0039] An acquisition module is used to acquire solar flare data and raw observation data of the receiver;

[0040] A solution module, used for solving the original observation data to obtain the electron time series corresponding to the ionosphere;

[0041] A processing module, used for smoothing the electronic time series to obtain a processed electronic time series;

[0042] A calculation module, used for calculating the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series;

[0043] A determination module is used to determine the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data.

[0044] Correspondingly, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of any of the above methods when executing the program.

[0045] The present application also provides a storage medium, wherein the storage medium stores a computer program, and the computer program implements any of the above methods when the computer program is executed by a processor.

[0046] The present application provides a method, device, electronic device and storage medium for determining the intensity of a solar flare. After obtaining the solar flare data and the original observation data of the receiver, the original observation data is solved to obtain the electronic time series corresponding to the ionosphere. Then, the electronic time series is smoothed to obtain the processed electronic time series. Then, according to the solar flare data and the processed electronic time series, the disturbance intensity level of the solar flare on the electronic time series is calculated. Finally, based on the correlation between the disturbance intensity level and the solar flare data, the intensity of the solar flare corresponding to the time to be detected is determined. In the scheme for determining the intensity of a solar flare provided in the present application, the original observation data can be solved to obtain the electronic time series corresponding to the ionosphere, and the disturbance intensity level of the solar flare on the electronic time series is calculated based on the electronic time series and combined with the solar flare data. Finally, the intensity of the solar flare corresponding to the time to be detected is determined by using the disturbance intensity level and the correlation between the solar flare data, thereby quickly and accurately determining the intensity of the solar flare corresponding to the time to be detected. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 It is a flow chart of a method for determining the intensity of a solar flare provided in an embodiment of the present application;

[0049] Figure 2is another schematic flow chart of the method for determining the solar flare intensity provided in an embodiment of the present application;

[0050] Figure 3 is a schematic diagram of the structure of a solar flare intensity determination device provided in an embodiment of the present application;

[0051] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of systems and methods consistent with the examples detailed in the attached claims, or with some aspects of the present application.

[0053] It should be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover descriptions such as non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0054] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0055] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0056] Embodiments of the present application provide a method, device, electronic device, and storage medium for determining the intensity of a solar flare.

[0057] Among them, the solar flare intensity determination device can be deployed in a terminal, and the terminal can be a smart phone, a tablet, an intelligent audio and video interactive device, a smart home appliance, a vehicle-mounted terminal, an aircraft, a wearable intelligent device, a medical device, etc. As mentioned above, the terminal 102 is often configured with a display device, and the display device can also be a display, a display screen, a touch screen, etc. The touch screen can also be a touch screen, a touch panel, etc., but is not limited to this. The terminal can communicate with the server in a wired or wireless manner. The server can include an independently running server or a distributed server, or a server cluster composed of multiple servers. The terminal can include a mobile phone, a tablet computer or a personal computer (PC, Personal Computer).

[0058] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0059] The present application provides a method for determining the intensity of a solar flare, comprising: acquiring solar flare data and original observation data of a receiver; solving the original observation data to obtain an electronic time series corresponding to the ionosphere; smoothing the electronic time series to obtain a processed electronic time series; calculating the disturbance intensity level of the solar flare on the electronic time series based on the solar flare data and the processed electronic time series; and determining the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data.

[0060] See also Figure 1 , Figure 1 : is a flow chart of a method for determining the intensity of a solar flare provided in the present application, and the method for determining the intensity of a solar flare specifically includes the following process:

[0061] 101. Obtain solar flare data and original observation data from the receiver.

[0062] Solar flare data include the specific date and time of the flare; the approximate location of the flare on the solar surface, including the solar longitude and latitude; the type of radiation produced by the flare, including X-rays, ultraviolet rays, radio waves, etc.; particle emission events that may be accompanied by flares, such as the emission of protons and electrons; and the duration of the flare event, from start to finish. These data are usually collected by solar observation satellites, solar telescopes and other related equipment, and analyzed and released by space weather monitoring agencies.

[0063] The raw observation data of the receiver usually refers to the unprocessed signal data collected by the GNSS (Global Navigation Satellite System) receiver. The raw observation data can specifically include the following information:

[0064] Pseudorange observation: The signal propagation time from the satellite to the receiver measured by the receiver, expressed in distance units, usually in meters. Carrier phase observation: The phase information of the carrier signal measured by the receiver, providing higher measurement accuracy than pseudorange. Signal frequency band: The observation data may include signals in multiple frequency bands, such as L1, L2, L5, etc. Different frequency bands have different sensitivities to ionospheric delay. Receiver clock error: The deviation between the receiver's internal clock and GPS time. Satellite clock error: The deviation between the satellite clock and GPS time. Hardware delay: The signal propagation delay caused by the receiver and satellite hardware. Ionospheric delay: The delay caused by the presence of free electrons when the GNSS signal passes through the ionosphere. Tropospheric delay: The delay caused by the atmospheric conditions when the GNSS signal passes through the troposphere. Integer ambiguity: The unknown integer number of cycles in the carrier phase measurement. Observation noise: Random error introduced in the measurement process. Multipath effect: The additional path length caused by the reflection or scattering of the signal before reaching the receiver. Data timestamp: The precise time stamp corresponding to each observation data point.

[0065] 102. The original observation data is solved to obtain the electron time series corresponding to the ionosphere.

[0066] The electron time series corresponding to the ionosphere refers to the data series of the total electron content (TEC) of the ionosphere obtained by solving the GNSS (Global Navigation Satellite System) observation data and changing with time.

[0067] For example, the raw observation data recorded by the GNSS receiver can be collected, including pseudorange and carrier phase data. Then, the clock bias of the receiver and the satellite is corrected to obtain precise time synchronization. Next, the position of the satellite is determined using precise ephemeris data, and the position of the receiver is determined using a known receiver position or through a positioning algorithm. Then, the geometric path of the signal is calculated based on the position of the satellite and the receiver. Next, a model such as the Hopfield model or the Saastamoinen model is used to correct the tropospheric delay, and the hardware delay of the receiver and the satellite is corrected at the same time. Then, the ionospheric delay is calculated using a dual-frequency signal. Signals of different frequencies are affected differently by the ionospheric delay. Specifically, the phase and pseudorange observations of the dual-frequency signal can be used to eliminate the integer ambiguity by differential calculation to calculate the ionospheric delay. Finally, the ionospheric delay is converted into TEC values, such as using a mapping function to convert the ionospheric slant delay (Slant TEC) into vertical TEC (VTEC). At the same time, a mapping function (such as the Klobuchar function) is used to convert the ionospheric slant delay into TEC in the vertical direction, and the processed TEC data are arranged in chronological order to form an ionospheric electronic time series.

[0068] Optionally, in some embodiments of the present application, the step of “solving the original observation data to obtain the electron time series corresponding to the ionosphere” may specifically include:

[0069] Obtain precise ephemeris and satellite clock errors;

[0070] Extracting raw pseudorange and carrier phase from raw observation data;

[0071] According to the original pseudorange, carrier phase, precise ephemeris and satellite clock error, the original pseudorange and carrier phase observation equations are constructed;

[0072] The original observation data are solved based on the original pseudorange and carrier phase observation equations to obtain the electron time series corresponding to the ionosphere.

[0073] Among them, the precise ephemeris provides accurate information about the satellite position, and the satellite clock error corrects the difference between the satellite clock and the GPS time. The raw pseudorange is the distance measurement between the receiver and the satellite, which is affected by the ionospheric delay. The carrier phase is a more accurate distance measurement, but contains integer ambiguity. Therefore, the extracted raw pseudorange and carrier phase can be used in combination with the precise ephemeris and satellite clock error to construct the observation equation.

[0074] The observation equation usually includes geometric distance, satellite and receiver clock errors, ionospheric delay, tropospheric delay and other terms. The observation equation and double difference technique are used to eliminate the influence of satellite and receiver clock errors, because radio waves of different frequencies are affected differently by the ionosphere. Then, based on the dual-frequency observation data, the difference in ionospheric delay at the two frequencies is calculated. Finally, a mapping function is used to convert the ionospheric slant delay (Slant TEC) into vertical TEC (VTEC), and the processed TEC data are arranged in chronological order, thereby obtaining the electronic time series corresponding to the ionosphere.

[0075] Optionally, in some embodiments of the present application, the step of “solving the original observation data based on the original pseudorange and carrier phase observation equation to obtain the electron time series corresponding to the ionosphere” may specifically include:

[0076] The original pseudorange and carrier phase observation equations are reorganized based on parameter reorganization to obtain the ionospheric delay expression.

[0077] Get the preset differential encoding deviation;

[0078] The original observation data is solved according to the ionospheric delay expression and differential coding deviation to obtain the electron time series corresponding to the ionosphere.

[0079] For example, the original pseudorange and carrier phase observation equations are reorganized based on parameter reorganization, and then the original observation data are solved using the Differential Code Bias (DCB) to obtain the electronic time series corresponding to the ionosphere.

[0080] Specifically, the GNSS original observation data is used as the data source, the precise ephemeris and clock error products use the post (or fast) precise ephemeris and clock error released by IGS, and the differential code bias (DCB) uses the DCB product released by CAS; the non-differential and non-combined precise single point positioning method is used to solve the slant TEC (Slant TEC, STEC) and vertical TEC (Vertical TEC, VTEC) measurement data of the satellite penetration point of the GNSS station during the solar flare period.

[0081] The GNSS raw pseudorange and carrier phase observation equations are as follows:

[0082]

[0083] Where s represents the GNSS satellite number, r represents the receiver, and f represents the signal frequency band (such as L1 and L2). represents the observed value of pseudorange, represents the geometric distance from the receiver antenna to the satellite antenna, c is the speed of light, Δt r is the receiver clock error, Δt s represents the satellite clock error, represents the receiver hardware delay of the pseudorange, Satellite hardware delay representing pseudorange, is the ionospheric delay that needs to be solved, represents the tropospheric delay, is the phase observation value, represents the carrier phase wavelength, represents the integer ambiguity, The receiver hardware delay representing the phase, Satellite hardware delay ε representing the phase P and ε L represents other errors in pseudorange and phase measurements.

[0084] The ionospheric slant delay is obtained by recombining the parameters causing rank deficiency in equation (1) using the parameter recombination method. The expression is:

[0085]

[0086] in represents the ionospheric slant delay of satellite s in frequency band 1, br,2 -b r,1 and If it is DCB, it can be eliminated according to the DCB file.

[0087] The ionospheric slant delay can be converted into the ionospheric slant TEC, which can then be converted into the ionosphere using a projection function, in which the cosine function is used for the conversion.

[0088] 103. Smoothing the electronic time series to obtain a processed electronic time series.

[0089] Smoothing the electron time series is done to reduce random noise in the data while retaining important signal features, such as peaks in ionospheric disturbances and other significant events.

[0090] For example, after obtaining the electron time series, which records the changes in the electron content of the ionosphere within a certain period of time, the electron time series can be smoothed through a filter to obtain a smoother curve (i.e., the processed electron time series). This curve reduces random fluctuations while retaining important disturbance features, which is convenient for subsequent evaluation of the impact of solar flares on the ionosphere.

[0091] Optionally, in some embodiments of the present application, the step of “smoothing the electronic time series to obtain a processed electronic time series” may specifically include:

[0092] Get the preset filter;

[0093] Determine the polynomial order and window size;

[0094] The electronic time series is smoothed according to the filter, the polynomial order and the window size to obtain a processed electronic time series.

[0095] For example, you can choose a Savitzky-Golay filter for data smoothing. The Savitzky-Golay filter is a digital filter used for data smoothing. It works by fitting a least squares polynomial to a subset of the original data points to produce smoothed values. This method can effectively smooth the data while maintaining data features such as peaks, valleys, and widths.

[0096] The main advantage of the Savitzky-Golay filter is that it combines the functions of data smoothing and differentiation. By properly choosing the order of the polynomial and the window size, it is possible to reduce noise while retaining the important features of the signal. This method usually performs better than simple moving average or linear filtering methods.

[0097] The basic mathematical expression of the filter can be expressed as:

[0098]

[0099] Among them, y′ i is the smoothed data point, y i+j is the original data point, c j are the coefficients calculated from the least squares polynomial fit, n is the normalization factor of the coefficients (to ensure that the sum of the coefficients is 1), and k is the window half-width (the window size is 2k+1).

[0100] Choosing the right polynomial order and window size has a significant impact on the performance of the filter. Generally speaking, the higher the polynomial order, the better the filter fits the data, but it is also more susceptible to noise; the larger the window, the better the smoothing effect, but the local features of the signal may be blurred. Here, a 4th-order polynomial is selected for fitting, and the window size is 61 sampling intervals.

[0101] 104. Based on the solar flare data and the processed electron time series, calculate the disturbance intensity level of the solar flare on the electron time series.

[0102] First, ensure that the solar flare data and the electronic time series are synchronized in time, that is, the time resolution and time range of the two are matched. At the same time, identify the time point and duration of the solar flare based on the solar flare data. During the solar flare, extract the corresponding data segment from the electronic time series. Calculate the change in ionospheric TEC during this period, which can be obtained by calculating the TEC difference between the starting point and the end point of the disturbance, so as to determine the intensity level of the disturbance of the electronic time series by the solar flare.

[0103] Optionally, in some embodiments of the present application, the step of “calculating the disturbance intensity level of the solar flare on the electron time series based on the solar flare data and the processed electron time series” includes:

[0104] determining an electron content map corresponding to the processed electron time series;

[0105] Based on the processed electron time series and electron content map, a disturbance intensity level model corresponding to solar flares is established;

[0106] According to the disturbance intensity level model, the disturbance intensity level of solar flares on the electron time series is calculated.

[0107] For example, a two-dimensional or three-dimensional map of the ionospheric electron content is generated using the processed electron time series in combination with the geographic location information of the GNSS station. Specifically, the vertical TEC (VTEC) can be converted into the ionospheric slant delay (Slant TEC, STEC), which can then be represented on the map. Then, based on the solar flare data, the time points and durations of specific flare events are identified, and these time points are synchronized with the electron time series. Next, during the solar flare, the corresponding data segments are extracted from the electron time series and the electron content map, and the disturbance amount of the ionospheric TEC during this period is calculated, including the starting value, peak value, and duration of the disturbance. Finally, based on the size and characteristics of the disturbance amount, a disturbance intensity level model is established, such as normalizing the disturbance amount and associating it with the intensity level of the solar flare.

[0108] Optionally, in some embodiments of the present application, the step of “establishing a disturbance intensity level model corresponding to the solar flare based on the processed electron time series and electron content map” may specifically include:

[0109] Determine the deviation point of the ionosphere from the preset value and the peak point corresponding to the deviation peak value in the processed electronic time series;

[0110] Based on the deviation points and the electron content map, the disturbance angle between the starting point and the peak point of the ionospheric disturbance is determined;

[0111] Based on the processed electron time series, disturbance angle and electron content map, a disturbance intensity level model corresponding to solar flares is established.

[0112] For example, a preset reference value of ionospheric TEC can be determined based on a long-term average or other benchmark model. Then, in the processed electronic time series, the time points at which the TEC value deviates significantly from the preset reference value for the first time are identified. These points are called deviation points. Continue to track the time series to find the highest point reached by the TEC value during the deviation, which is called the peak point. Then, use the electronic content map to determine the spatial distribution of ionospheric disturbances, especially the spatial positions of deviation points and peak points. Next, based on the electronic content map, determine the starting point and peak point of the ionospheric disturbance, which correspond to the deviation points and peak points in the time series. Next, determine the disturbance angle between the starting point and the peak point. This usually involves calculating the positions of two points on the map and measuring the angles between them and a reference direction (such as geographic north). Finally, a disturbance intensity level model is established based on the deviation amount, peak amount and disturbance angle in the time series.

[0113] 105. Based on the disturbance intensity level and the correlation of the solar flare data, determine the intensity of the solar flare corresponding to the time to be detected.

[0114] For example, the solar flare event data at the time to be detected is collected, including time, location, estimated intensity level, etc. Then, the processed electronic time series is analyzed to determine the change in the ionospheric TEC value at the time of the solar flare. Next, the disturbance intensity level is calculated based on the disturbance amount observed in the electronic time series (such as the degree of deviation from the preset value, the difference between the peak value and the starting value, etc.). Finally, using historical data, a correlation model between the disturbance intensity level and the solar flare intensity level is established, such as regression analysis, to determine the relationship between the two.

[0115] Optionally, in some embodiments of the present application, the step of “determining the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data” may specifically include:

[0116] Divide the disturbance intensity level into multiple preset levels;

[0117] Extracting solar flare disturbance events within a preset time from solar flare data;

[0118] According to the peak intensity corresponding to the solar flare event, the correlation relationship between the solar flare disturbance event and the preset level is established;

[0119] Based on the preset statistical method and the association relationship, the correlation between the disturbance intensity level and the solar flare data is constructed, and the intensity of the solar flare corresponding to the time to be detected is determined based on the correlation.

[0120] In order to further understand the solar flare intensity determination scheme of the present application, the following will further explain that first, ground-based (air-based) GNSS original observation data, space weather data and solar flare data are obtained, and the ionospheric TEC is solved using the non-difference non-combined precise single-point positioning method, and a clean TEC time series is obtained after deducting the satellite and receiver DCB; then the ionospheric TEC sequence is smoothed based on the Savitzky-Golay filter, and the smoothed TEC sequence is subjected to first-order difference processing from both a single satellite and all visible satellites to form a temporal and spatial TEC disturbance sequence; the influence range of the solar flare on the ionosphere is determined based on the spatial disturbance distribution, and a disturbance intensity level model is established based on the temporal disturbance sequence; finally, a correlation analysis is performed between the disturbance intensity and the flare level to determine the corresponding relationship. When solar flare intensity detection is required, the solar flare intensity can be output quickly and accurately based on the corresponding relationship. The specific process for determining the corresponding relationship is as follows: Figure 2 As shown, the details are as follows:

[0121] (1) Ionospheric TEC solution

[0122] The GNSS original observation data is used as the data source, the precise ephemeris and clock products use the post-event (or fast) precise ephemeris and clock products released by IGS, and the differential code bias (DCB) uses the DCB products released by CAS. The slant TEC (Slant TEC, STEC) and vertical TEC (Vertical TEC, VTEC) measurement data of the satellite penetration point of the GNSS station during the solar flare period are obtained by using the non-differential non-combined precise single point positioning method.

[0123] The GNSS raw pseudorange and carrier phase observation equations are as follows:

[0124]

[0125] Where s represents the GNSS satellite number, r represents the receiver, and f represents the signal frequency band (such as L1 and L2). represents the observed value of pseudorange, represents the geometric distance from the receiver antenna to the satellite antenna, c is the speed of light, Δt r is the receiver clock error, Δt s represents the satellite clock error, represents the receiver hardware delay of the pseudorange, Satellite hardware delay representing pseudorange, is the ionospheric delay that needs to be solved, represents the tropospheric delay, is the phase observation value, represents the carrier phase wavelength, represents the integer ambiguity, The receiver hardware delay representing the phase, Satellite hardware delay ε representing the phase P and ε L represents other errors in pseudorange and phase measurements.

[0126] The ionospheric slant delay is obtained by recombining the parameters causing rank deficiency in equation (4) using the parameter recombination method. The expression is:

[0127]

[0128] in represents the ionospheric slant delay of satellite s in frequency band 1, b r,2 -b r,1 and If it is DCB, it can be eliminated according to the DCB file.

[0129] The ionospheric slant delay can be converted into the ionospheric slant TEC, which can then be converted into the ionosphere using a projection function, in which the cosine function is used for the conversion.

[0130] (2) Smoothed ionospheric TEC sequence

[0131] The resolved clean ionospheric TEC series is smoothed based on the Savitzky-Golay filter. The Savitzky-Golay filter is a digital filter used for data smoothing. It works by fitting a least squares polynomial to a subset of the original data points to produce smoothed values. This method can effectively smooth the data while maintaining data features such as peaks, valleys, and widths.

[0132] The main advantage of the Savitzky-Golay filter is that it combines the functions of data smoothing and differentiation. By properly choosing the order of the polynomial and the window size, it is possible to reduce noise while retaining the important features of the signal. This method usually performs better than simple moving average or linear filtering methods.

[0133] The basic mathematical expression of the filter can be expressed as:

[0134]

[0135] Among them, y′ i is the smoothed data point, y i+j is the original data point, c j are the coefficients calculated from the least squares polynomial fit, n is the normalization factor of the coefficients (to ensure that the sum of the coefficients is 1), and k is the window half-width (the window size is 2k+1).

[0136] Choosing the right polynomial order and window size has a significant impact on the performance of the filter. Generally speaking, the higher the polynomial order, the better the filter fits the data, but it is also more susceptible to noise; the larger the window, the better the smoothing effect, but the local features of the signal may be blurred. Here, a 4th-order polynomial is selected for fitting, and the window size is 61 sampling intervals.

[0137] (3) Ionospheric TEC sequence after differential smoothing

[0138] Based on the ionospheric TEC sequence smoothed by the Savitzky-Golay filter, the first-order difference of the TEC sequence is performed in both time and space (single satellite and all visible satellites), namely: A time-based one-dimensional ionospheric ddTEC sequence and a space-based two-dimensional ionospheric ddTEC map are formed.

[0139] (4) Determine the scope and intensity of the impact of solar flares on the ionosphere

[0140] Based on the two-dimensional ionospheric ddTEC map, the range and intensity of ionospheric disturbances when solar flares occur are screened. Based on the one-dimensional ionospheric ddTEC sequence, the overall disturbance impact on the ionospheric TEC time series during the solar flare is defined as the disturbance intensity level, namely DIL. The angle between the direction of the line connecting the initial value of the disturbance and the maximum value of the disturbance and the X-axis of the coordinate system is defined as the disturbance angle, represented by the letter θ. On the basis of the disturbance amount, the disturbance rate v is introduced to express the impact on DIL, and it is defined as a function of the flare duration t and the disturbance angle θ. The proportion of each disturbance angle is obtained by normalizing the size of each disturbance angle to the angle n, and the value of n is 90°, which better constrains the unidirectional impact of the disturbance amount on DIL and reflects the intensity of the solar flare on the ionospheric TEC disturbance. The established disturbance intensity level model is as follows:

[0141]

[0142] Among them, DIL refers to the disturbance intensity level of the flare on TEC (in TECU), ddTEC beg Refers to the starting value of TEC disturbance, ddTEC max represents the maximum value of TEC disturbance, t beg With t max represents the starting time and peak time of the disturbance, and θ represents the disturbance angle of TEC.

[0143] (5) Correlation analysis between disturbance intensity and flare level

[0144] Combined with the variation range of DIL values, the disturbance intensity is divided into five intensity levels in the order of weak disturbance, weak disturbance, strong disturbance, strong disturbance and severe disturbance, corresponding to the five levels of solar flares. The disturbance intensity levels of long-term solar flares on ionospheric TEC are counted, and the linear correlation between the disturbance intensity level and the solar flare intensity level is determined by correlation analysis. Then, the corresponding solar flare intensity level can be determined by calculating the disturbance intensity level of ionospheric TEC during the solar flare.

[0145] The above is the process for determining the solar flare intensity provided in the embodiment of the present application.

[0146] In summary, after obtaining the solar flare data and the original observation data of the receiver, the embodiment of the present application solves the original observation data to obtain the electronic time series corresponding to the ionosphere, then smoothes the electronic time series to obtain the processed electronic time series, and then calculates the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series, and finally, based on the correlation between the disturbance intensity level and the solar flare data, determines the intensity of the solar flare corresponding to the time to be detected. In the scheme for determining the intensity of solar flares provided in the present application, the original observation data can be solved to obtain the electronic time series corresponding to the ionosphere, and on the basis of the electronic time series, combined with the solar flare data, calculate the disturbance intensity level of the solar flare on the electronic time series, and finally, using the disturbance intensity level and the correlation between the solar flare data, determine the intensity of the solar flare corresponding to the time to be detected, thereby quickly and accurately determining the intensity of the solar flare corresponding to the time to be detected.

[0147] In order to facilitate better implementation of the solar flare intensity determination method of the embodiment of the present application, the embodiment of the present application also provides a solar flare intensity determination device. The meanings of the terms are the same as those in the above-mentioned solar flare intensity determination system, and the specific implementation details can refer to the description in the system embodiment.

[0148] See also Figure 3 , Figure 3 A schematic diagram of the structure of a solar flare intensity determination device provided in an embodiment of the present application, wherein the solar flare intensity determination device may specifically include an acquisition module 201, a solution module 202, a processing module 203, a calculation module 204, and a determination module 205, which may be specifically as follows:

[0149] The acquisition module 201 is used to acquire solar flare data and original observation data of the receiver.

[0150] The solution module 202 is used to solve the original observation data to obtain the electron time series corresponding to the ionosphere.

[0151] The processing module 203 is used to perform smoothing processing on the electronic time series to obtain a processed electronic time series.

[0152] The calculation module 204 is used to calculate the disturbance intensity level of the solar flare on the electronic time series based on the solar flare data and the processed electronic time series.

[0153] The determination module 205 is used to determine the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data.

[0154] Optionally, in some embodiments of the present application, the solving module 202 may be specifically used for:

[0155] Obtain precise ephemeris and satellite clock errors;

[0156] Extracting raw pseudorange and carrier phase from raw observation data;

[0157] According to the original pseudorange, carrier phase, precise ephemeris and satellite clock error, the original pseudorange and carrier phase observation equations are constructed;

[0158] The original observation data is solved based on the original pseudorange and carrier phase observation equation to obtain the electron time series corresponding to the ionosphere.

[0159] Optionally, in some embodiments of the present application, the solving module 202 may be specifically used for:

[0160] Reorganizing the original pseudorange and carrier phase observation equations based on parameter reorganization to obtain an ionospheric delay expression;

[0161] Get the preset differential encoding deviation;

[0162] The original observation data is solved according to the ionospheric delay expression and differential coding deviation to obtain the electron time series corresponding to the ionosphere.

[0163] Optionally, in some embodiments of the present application, the processing module 203 may be specifically used to:

[0164] Get the preset filter;

[0165] Determine the polynomial order and window size;

[0166] The electronic time series is smoothed according to the filter, the polynomial order and the window size to obtain a processed electronic time series.

[0167] Optionally, in some embodiments of the present application, the calculation module 204 may be specifically used for:

[0168] determining an electron content map corresponding to the processed electron time series;

[0169] Based on the processed electron time series and electron content map, a disturbance intensity level model corresponding to the solar flare is established;

[0170] The disturbance intensity level of the solar flare on the electronic time series is calculated according to the disturbance intensity level model.

[0171] Optionally, in some embodiments of the present application, the calculation module 204 may be specifically used for:

[0172] Determine the deviation point of the ionosphere from the preset value and the peak point corresponding to the deviation peak value in the processed electronic time series;

[0173] Based on the deviation points and the electron content map, the disturbance angle between the starting point and the peak point of the ionospheric disturbance is determined;

[0174] Based on the processed electron time series, disturbance angle and electron content map, a disturbance intensity level model corresponding to solar flares is established.

[0175] Optionally, in some embodiments of the present application, the determination module 205 may be specifically used to:

[0176] Divide the disturbance intensity level into multiple preset levels;

[0177] Extracting solar flare disturbance events within a preset time from solar flare data;

[0178] According to the peak intensity corresponding to the solar flare event, the correlation relationship between the solar flare disturbance event and the preset level is established;

[0179] Based on the preset statistical method and the association relationship, the correlation between the disturbance intensity level and the solar flare data is constructed, and the intensity of the solar flare corresponding to the time to be detected is determined based on the correlation.

[0180] The embodiment of the present application provides a solar flare intensity determination device. After the acquisition module 201 acquires the solar flare data and the original observation data of the receiver, the solution module 202 solves the original observation data to obtain the electronic time series corresponding to the ionosphere. Then, the processing module 203 smoothes the electronic time series to obtain the processed electronic time series. Then, the calculation module 204 calculates the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series. Finally, the determination module 205 determines the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data. In the scheme for determining the solar flare intensity provided in the present application, the original observation data can be solved to obtain the electronic time series corresponding to the ionosphere, and the disturbance intensity level of the solar flare on the electronic time series is calculated based on the electronic time series combined with the solar flare data. Finally, the disturbance intensity level and the correlation of the solar flare data are used to determine the intensity of the solar flare corresponding to the time to be detected, thereby quickly and accurately determining the solar flare intensity corresponding to the time to be detected.

[0181] In addition, the present application also provides an electronic device, such as Figure 4 As shown, it shows a schematic diagram of the structure of the electronic device involved in the embodiment of the present application, specifically:

[0182] The electronic device may include components such as a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, a power supply 303, and an input unit 304. Those skilled in the art will appreciate that Figure 4 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0183] The processor 301 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0184] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and the solar flare intensity determination method by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0185] The electronic device also includes a power supply 303 for supplying power to each component. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 303 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0186] The electronic device may further include an input unit 304, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0187] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302, thereby realizing various functions, as follows:

[0188] Acquire solar flare data and original observation data of the receiver; solve the original observation data to obtain the electronic time series corresponding to the ionosphere; smooth the electronic time series to obtain the processed electronic time series; calculate the disturbance intensity level of the solar flare on the electronic time series based on the solar flare data and the processed electronic time series; determine the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data.

[0189] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0190] After obtaining the solar flare data and the original observation data of the receiver, the embodiment of the present application solves the original observation data to obtain the electronic time series corresponding to the ionosphere, then smoothes the electronic time series to obtain the processed electronic time series, and then calculates the disturbance intensity level of the solar flare on the electronic time series based on the solar flare data and the processed electronic time series, and finally, based on the correlation between the disturbance intensity level and the solar flare data, determines the intensity of the solar flare corresponding to the time to be detected. In the scheme for determining the solar flare intensity provided in the present application, the original observation data can be solved to obtain the electronic time series corresponding to the ionosphere, and on the basis of the electronic time series, combined with the solar flare data, calculate the disturbance intensity level of the solar flare on the electronic time series, and finally, using the disturbance intensity level and the correlation between the solar flare data, determine the intensity of the solar flare corresponding to the time to be detected, thereby quickly and accurately determining the solar flare intensity corresponding to the time to be detected.

[0191] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0192] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any of the solar flare intensity determination methods provided in the embodiments of the present application. For example, the instructions can execute the following steps:

[0193] Acquire solar flare data and original observation data of the receiver; solve the original observation data to obtain the electronic time series corresponding to the ionosphere; smooth the electronic time series to obtain the processed electronic time series; calculate the disturbance intensity level of the solar flare on the electronic time series based on the solar flare data and the processed electronic time series; determine the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data.

[0194] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0195] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0196] Since the instructions stored in the storage medium can execute the steps in any one of the methods for determining the intensity of a solar flare provided in the embodiments of the present application, the beneficial effects that can be achieved by any one of the methods for determining the intensity of a solar flare provided in the embodiments of the present application can be achieved. For details, please refer to the previous embodiments and will not be repeated here.

[0197] The above is a detailed introduction to a method, device, electronic device and storage medium for determining the intensity of a solar flare provided in an embodiment of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for determining the intensity of a solar flare, characterized in that: include: Obtain solar flare data and raw observation data from receivers; Solving the original observation data to obtain an electron time series corresponding to the ionosphere; Performing smoothing processing on the electronic time series to obtain a processed electronic time series; Calculating the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series; Based on the disturbance intensity level and the correlation of the solar flare data, the intensity of the solar flare corresponding to the time to be detected is determined.

2. The method for determining the intensity of a solar flare according to claim 1, characterized in that: The processing of the original observation data to obtain an electron time series corresponding to the ionosphere includes: Obtain precise ephemeris and satellite clock errors; Extracting original pseudorange and carrier phase from the original observation data; Constructing original pseudorange and carrier phase observation equations according to the original pseudorange, carrier phase, precise ephemeris and satellite clock error; The original observation data is solved based on the original pseudorange and carrier phase observation equation to obtain an electron time series corresponding to the ionosphere.

3. The method for determining the intensity of a solar flare according to claim 2, characterized in that: The method of solving the original observation data based on the original pseudorange and carrier phase observation equation to obtain an electron time series corresponding to the ionosphere includes: Reorganizing the original pseudorange and carrier phase observation equations based on parameter reorganization to obtain an ionospheric delay expression; Get the preset differential encoding deviation; The original observation data is solved according to the ionospheric delay expression and the differential coding deviation to obtain the electronic time series corresponding to the ionosphere.

4. The method for determining the intensity of a solar flare according to claim 1, characterized in that: The step of smoothing the electronic time series to obtain a processed electronic time series includes: Get the preset filter; Determine the polynomial order and window size; The electronic time series is smoothed according to the filter, the polynomial order and the window size to obtain a processed electronic time series.

5. The method for determining the intensity of a solar flare according to claim 1, characterized in that: The step of calculating the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series comprises: determining an electron content map corresponding to the processed electron time series; Based on the processed electron time series and electron content map, a disturbance intensity level model corresponding to the solar flare is established; The disturbance intensity level of the solar flare on the electronic time series is calculated according to the disturbance intensity level model.

6. The method for determining the intensity of a solar flare according to claim 5, characterized in that: The method of establishing a disturbance intensity level model corresponding to a solar flare based on the processed electron time series and electron content map comprises: Determine, in the processed electronic time series, a deviation point of the ionosphere from a preset value and a peak point corresponding to the deviation peak value; Determining the disturbance angle between the starting point and the peak point of the ionospheric disturbance according to the deviation point and the electron content map; Based on the processed electron time series, disturbance angle and electron content map, a disturbance intensity level model corresponding to the solar flare is established.

7. The method for determining the solar flare intensity according to any one of claims 1 to 6, characterized in that: The determining, based on the correlation between the disturbance intensity level and the solar flare data, the intensity of the solar flare corresponding to the time to be detected comprises: Dividing the disturbance intensity level into a plurality of preset levels; Extracting solar flare disturbance events within a preset time from the solar flare data; Establishing a correlation relationship between the solar flare disturbance event and a preset level according to the peak intensity corresponding to the solar flare event; Based on the preset statistical method and the association relationship, the correlation between the disturbance intensity level and the solar flare data is constructed, and the intensity of the solar flare corresponding to the time to be detected is determined based on the correlation.

8. A device for determining the intensity of a solar flare, characterized in that: include: An acquisition module is used to acquire solar flare data and raw observation data of the receiver; A solution module, used for solving the original observation data to obtain the electron time series corresponding to the ionosphere; A processing module, used for smoothing the electronic time series to obtain a processed electronic time series; A calculation module, used for calculating the disturbance intensity level of the solar flare on the electronic time series according to the solar flare data and the processed electronic time series; A determination module is used to determine the intensity of the solar flare corresponding to the time to be detected based on the disturbance intensity level and the correlation of the solar flare data.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for determining the intensity of a solar flare are performed as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method for determining the solar flare intensity according to any one of claims 1 to 7.

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