Ionospheric data determination method, apparatus and computer device
By acquiring and filtering ionospheric parameters, and combining Kalman filtering and the Prophet model, the problem of insufficient accuracy in determining ionospheric VTEC was solved, and high-precision ionospheric VTEC prediction was achieved.
Patent Information
- Application Number
- CN202211480319.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-11-24
- Publication Date
- 2026-01-20
- Estimated Expiration
- 2042-11-24
AI Technical Summary
In existing technologies, the accuracy of determining the VTEC of the ionosphere is poor, and the accuracy of traditional models is not good.
By acquiring ionospheric parameters, including the ionospheric index, published electron content, and monitored electron content, and after filtering, the data is input into the electron content prediction model. The electron content prediction model is used for prediction, and Kalman filtering and Prophet model are used for data processing to improve accuracy.
It improved the prediction accuracy of ionospheric VTEC values and achieved high-precision forecasts in the medium and short term.
Smart Images
Figure CN115826098B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the ionosphere VTEC (Vertical Total Electron Content) prediction technical field, in particular to an ionosphere data determination method and device, computer equipment, storage medium and computer program product. BACKGROUND
[0002] With the development of navigation positioning, wireless communication, aerospace, weather prediction and other fields, the ionosphere has a huge impact on the refraction, scattering, reflection and absorption effects of electromagnetic waves. For GNSS (Global Navigation Satellite System) users, ionospheric delay is the main error source in navigation positioning, and vertical total electron content (VTEC) is an important parameter of ionospheric delay. Therefore, the determination and prediction of VTEC are of great significance.
[0003] At present, when determining VTEC, it is mainly based on empirical models and mathematical theory derived from long-term period data, but the accuracy of the traditional model is poor, resulting in poor accuracy of the finally determined VTEC value. SUMMARY
[0004] Therefore, it is necessary to provide an ionosphere data determination method, device, computer equipment, computer readable storage medium and computer program product capable of improving the accuracy of VTEC value determination.
[0005] In a first aspect, the present application provides an ionosphere data determination method, which comprises:
[0006] obtaining ionosphere parameters, the ionosphere parameters comprising ionosphere indices, published electron content at each preset time, and monitored electron content at each preset time;
[0007] performing filtering processing on the published electron content and the monitored electron content at each preset time to obtain a target electron data pair after filtering processing;
[0008] inputting the ionosphere indices and the target electron data pair into an electron content prediction model to obtain a target electron content prediction value through the electron content prediction model.
[0009] In one embodiment, the target electron data pair comprises an intermediate fitting electron content and a monitored electron content corresponding to the same time as the intermediate fitting electron content;
[0010] The filtering processing on the published electron content and the monitored electron content at each preset time to obtain a target electron data pair after filtering processing comprises:
[0011] determining an electronic data set corresponding to a target time period, the target time period including a preset number of continuous preset time points, the electronic data set including a published electronic content and a monitored electronic content in the target time period;
[0012] determining initial expression coefficients of an initial ionospheric expression based on the electronic data set, to obtain an intermediate ionospheric expression;
[0013] fitting to obtain an intermediate fitted electronic content of a next time point after the target time period according to the published electronic content of the next time point and the intermediate ionospheric expression;
[0014] if a difference between the intermediate fitted electronic content of the next time point and the monitored electronic content satisfies a preset difference condition, retaining the intermediate fitted electronic content of the next time point and the monitored electronic content;
[0015] adding the published electronic content and the monitored electronic content of the next time point to the electronic data set, updating the target time period based on the next time point, and continuing to execute the step of determining the initial expression coefficients of the initial ionospheric expression based on the electronic data set until a preset stop condition is reached, to obtain a target electronic data pair.
[0016] In one of the embodiments, the target electronic data pair further includes an updated fitted electronic content and a monitored electronic content corresponding to a same time point as the updated fitted electronic content, and the method further includes:
[0017] if the difference between the intermediate fitted electronic content of the next time point and the monitored electronic content does not satisfy the preset difference condition, performing interpolation processing on the published electronic content and the monitored electronic content in the electronic data set to obtain an interpolated data set;
[0018] updating the initial expression coefficients based on the interpolated data set to obtain an updated ionospheric expression;
[0019] fitting to obtain an updated fitted electronic content of the next time point according to the published electronic content of the next time point and the updated ionospheric expression;
[0020] if a difference between the updated fitted electronic content of the next time point and the monitored electronic content satisfies the preset difference condition, retaining the updated fitted electronic content of the next time point and the monitored electronic content.
[0021] In one of the embodiments, the method further includes:
[0022] If the difference between the updated fitting electron content and the monitored electron content does not satisfy the preset difference condition, the interpolation data set is updated to obtain an updated interpolation data set, and the step of updating the initial expression coefficient based on the interpolation data set to obtain an updated ionospheric expression is returned; when the number of times of updating the interpolation data set reaches a preset update number threshold, and the difference between the updated fitting electron content and the monitored electron content still does not satisfy the preset difference condition, the published electron content and the monitored electron content at the next time point after the target time period are discarded.
[0023] In one of the embodiments, the obtaining the ionospheric parameter comprises:
[0024] An ionospheric grid product file is obtained, and the published electron content at each preset time point in the target area is read from the ionospheric grid product file.
[0025] The ionospheric index corresponding to the target area is obtained.
[0026] The satellite system monitoring data corresponding to the target area is obtained.
[0027] Based on the satellite system monitoring data, the monitored electron content at each preset time point is determined.
[0028] In one of the embodiments, the ionospheric index comprises a solar radiation index and a geomagnetic activity index; and the electron content prediction model comprises a trend term, a periodic term, a holiday term, and an error term.
[0029] The inputting the ionospheric index and the target electron data pair into the electron content prediction model to predict a target electron content prediction value via the electron content prediction model comprises:
[0030] The target electron data pair, the solar radiation index, and the geomagnetic activity index are inputted into the trend term, the periodic term, the holiday term, and the error term, the target electron data is processed for non-periodic change via the trend term, the target electron data is processed for periodic change via the periodic term, the solar radiation index and the geomagnetic activity index are processed for special time event via the holiday term, and the target electron data pair, the solar radiation index, and the geomagnetic activity index are processed for error via the error term to obtain corresponding processing results.
[0031] The processing results are accumulated to predict a target electron content prediction value.
[0032] In a second aspect, the present application provides an ionospheric data determination device, which comprises:
[0033] The data acquisition module is used to acquire ionospheric parameters, including the ionospheric index, the published electron content at each preset time, and the monitored electron content at each preset time.
[0034] The data processing module is used to filter the published electron content and monitored electron content at each preset time to obtain the target electron data pair after filtering.
[0035] The prediction module is used to input the ionospheric index and the target electron data pair into the electron content prediction model, and obtain the target electron content prediction value through the electron content prediction model.
[0036] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the above-described ionospheric data determination method.
[0037] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the above-described ionospheric data determination method.
[0038] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the above-described ionospheric data determination method.
[0039] The aforementioned method, apparatus, computer equipment, storage medium, and computer program product for determining ionospheric data acquire ionospheric parameters, including the ionospheric index, the emitted electron content at each preset time, and the monitored electron content at each preset time. The emitted and monitored electron contents at each preset time are then filtered to obtain a target electron data pair. The ionospheric index and the target electron data pair are input into an electron content prediction model, which predicts the target electron content. Because the emitted and monitored electron contents are filtered out, a more reliable target electron data pair is obtained, thereby effectively improving the accuracy of the subsequent electron content prediction model. Attached Figure Description
[0040] Figure 1 This is a flowchart illustrating a method for determining ionospheric data in one embodiment;
[0041] Figure 2 This is a flowchart illustrating the ionospheric data determination method in another embodiment;
[0042] Figure 3This is a flowchart illustrating the ionospheric data determination method in another embodiment;
[0043] Figure 4 This is a flowchart of a method for determining ionospheric data in one embodiment;
[0044] Figure 5 This is a structural block diagram of an ionospheric data determination device in one embodiment;
[0045] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation
[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0047] The ionospheric data determination method provided in this application embodiment can be applied to a terminal. Specifically, the terminal can run an electron content prediction model, which allows the terminal to predict the electron content and obtain an accurate electron content. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Optionally, the ionospheric data determination method provided in this application embodiment can also be applied to a server, which can be implemented using a standalone server or a server cluster composed of multiple servers.
[0048] In one embodiment, such as Figure 1 As shown, a method for determining ionospheric data is provided. Taking the application of this method to a terminal as an example, the method includes the following steps:
[0049] Step S102: Obtain ionospheric parameters, including the ionospheric index, the published electron content at each preset time, and the monitored electron content at each preset time.
[0050] Among them, the ionospheric index can refer to parameters that affect the characteristics of the ionosphere. Specifically, the ionospheric index can refer to the geomagnetic index, the solar radiation index, and the Kp index (an index describing global geomagnetic activity). The published electron content can refer to the VTEC (total vertical electron content) extracted from the GIM (ionospheric grid product) file published by IGS (International Service). The monitored electron content can refer to the VTEC calculated from the data monitored by GNSS (Global Navigation Satellite System).
[0051] Furthermore, the preset time for the release of electron content refers to the time point at which the release electron content is obtained, determined based on the release time interval. Specifically, the release time interval can be 2 hours. Each time the release interval is reached, the terminal can obtain the release electron content at the corresponding time. For monitoring electron content, the terminal can also obtain the corresponding observation data each time the interval is reached, and then calculate the monitoring electron content based on the observation data, etc.
[0052] In one embodiment, obtaining ionospheric parameters includes: obtaining an ionospheric grid product file and reading the published electron content at each preset time in the target area from the ionospheric grid product file; obtaining the ionospheric index corresponding to the target area; obtaining satellite system monitoring data corresponding to the target area; and determining the monitored electron content at each preset time based on the satellite system monitoring data.
[0053] Among them, the ionospheric grid product file refers to the file that stores the published electron content of multiple regions. The target region is the region selected by the terminal to determine the predicted value of the target electron content. The latitude and longitude range of the target region selected by the terminal can be 87.5°N~87.5°S. The target region can be a region composed of multiple grids. Each grid has latitude and longitude coordinates, and each grid will have a corresponding published electron content at each preset time.
[0054] Furthermore, satellite system monitoring data can refer to GNSS observation station data, clock error files, ephemeris files, etc. obtained from GNSS monitoring. After determining the target area, the terminal will also acquire data such as geomagnetic index, solar radiation index, and Kp index of the target area, as well as satellite system monitoring data of the target area at each preset time. The terminal can calculate and determine the monitoring electron content at each preset time based on the satellite system monitoring data.
[0055] In the above embodiments, the terminal obtains the ionospheric index, the published electron content at each preset time, and the monitored electron content at each preset time for subsequent prediction of the target electron content, which can provide users with fast, high-precision, and highly available forecast products in real time.
[0056] Step S104: Filter the published electron content and monitored electron content at each preset time to obtain the target electron data pair after filtering.
[0057] Among them, the filtering process refers to a fast filtering process on the published electron content and the monitored electron content at each preset time to obtain a target electron data pair with better accuracy than the current published electron content and monitored electron content, which can improve the accuracy of the subsequent electron content prediction model.
[0058] Step S106: Input the ionospheric index and target electron data into the electron content prediction model, and obtain the target electron content prediction value through the electron content prediction model.
[0059] The target electron content prediction value can refer to the predicted ionospheric VTEC value. When the terminal uses the electron content prediction model for prediction, it can achieve the prediction of the ionospheric VTEC value in the short to medium term. Specifically, after obtaining the target electron data pair, the terminal can input the ionospheric index and the target electron data pair into the electron content prediction model, and the target electron content prediction value is obtained through the electron content prediction model.
[0060] In the above-mentioned method for determining ionospheric data, ionospheric parameters are acquired, including the ionospheric index, the electron content emitted at each preset time, and the electron content monitored at each preset time. The emitted and monitored electron contents at each preset time are filtered out to obtain a target electron data pair after filtering. The ionospheric index and the target electron data pair are input into the electron content prediction model, and the predicted value of the target electron content is obtained by the electron content prediction model. Since the emitted and monitored electron contents are filtered out, a more reliable target electron data pair can be obtained, thereby effectively improving the accuracy of the subsequent electron content prediction model.
[0061] In one embodiment, the target electron data pair includes an intermediate fitted electron content and a monitored electron content at the same time corresponding to the intermediate fitted electron content.
[0062] The target electron data pair can refer to the intermediate fitted electron content and the monitored electron content at the same time. The intermediate fitted electron content refers to the electron content obtained by fitting the published electron content and the ionospheric expression.
[0063] Specifically, the electron content of the published data and the electron content of the monitored data at each preset time are filtered out to obtain the target electron data pair after filtering, including the following steps:
[0064] Step S204: Determine the electronic dataset corresponding to the target time period. The target time period includes a preset number of consecutive preset times. The electronic dataset includes the published electronic content and the monitored electronic content within the target time period.
[0065] The target time period can refer to the time period set to determine the coefficients of the subsequent initial expression. The target time period can include a preset number of consecutive preset times. For example, if the terminal acquires the published electron content and monitored electron content at multiple consecutive preset times such as T1, T2, T3, T4, etc., the terminal can select a portion of consecutive preset times (such as T1, T2, T3) as the target time period in chronological order. Correspondingly, the electron dataset can be the published electron content and monitored electron content within the time periods T1, T2, and T3.
[0066] Step S206: Determine the initial expression coefficients of the initial ionosphere expression based on the electron dataset to obtain the intermediate ionosphere expression.
[0067] The initial ionospheric expression can refer to the expression constructed to fit the monitored electron content and obtain the fitted electron content. The initial expression coefficients refer to the coefficients of the initial expression determined based on the electron dataset corresponding to the target time period. After determining the initial ionospheric expression, the intermediate ionospheric expression can be determined after determining the initial expression coefficients.
[0068] In one embodiment, the formula for the initial expression is shown below:
[0069] VTEC=a0B 2 +a1B+a2L 2 +a3L+a4VTEC0+a5VTEC0+a6
[0070] Wherein, VTEC refers to monitoring electron content, VTEC0 refers to releasing electron content, B and L represent latitude and longitude, and a0, a1, a2, a3, a4, a5, and a6 are initial expression coefficients.
[0071] Step S208: Based on the published electron content and intermediate ionosphere expression at the next moment after the target time period, the intermediate fitted electron content at the next moment is obtained by fitting.
[0072] The next moment after the target time period refers to the next moment connected to the target time period. For example, if T1, T2, and T3 are selected as target time periods, then the next moment after the target time period is T4. If T1, T2, T3, and T4 are selected as target time periods, then the next moment after the target time period is T5. Specifically, if T1, T2, and T3 are selected as target time periods, then the next moment after the target time period is T4. The terminal can then fit the intermediate fitted electron content at time T4 based on the published electron content and the intermediate ionosphere expression at time T4.
[0073] Step S210: If the difference between the intermediate fitted electron content and the monitored electron content at the next time step meets the preset difference condition, then the intermediate fitted electron content and the monitored electron content at the next time step are retained.
[0074] The preset difference condition can refer to the difference between the intermediate fitted electron content and the monitored electron content being within the difference threshold range. If the difference threshold is exceeded, it means that the preset difference condition is not met. Specifically, the difference between the intermediate fitted electron content and the monitored electron content can refer to the residual. When the terminal determines that the residual meets the preset difference condition, the intermediate fitted electron content and the monitored electron content at the next moment can be retained.
[0075] Step S212: Add the published electron content and monitored electron content of the next moment to the electron dataset, update the target time period based on the next moment, and return to the step of determining the initial expression coefficients of the initial ionospheric expression based on the updated electron dataset and the updated target time period to continue execution until the preset stopping condition is met, and the target electron data pair is obtained.
[0076] The preset stop condition can be a set number of times the electronic dataset is updated. When the set number of updates is reached, the iteration stops. Alternatively, the preset stop condition can be a set time to stop the iteration. When that time is reached, the iteration stops. The preset stop condition can be adjusted adaptively according to the actual situation.
[0077] Once the terminal determines that the difference between the intermediate fitted electron content and the monitored electron content at the next moment meets the preset difference condition, the published electron content and the monitored electron content at the next moment can be added to the electron dataset. At this time, the target time period has been updated, and the corresponding electron dataset has also been updated. The terminal can then update the target time period based on the next moment, and return to the step of determining the initial expression coefficients of the initial ionospheric expression based on the updated electron dataset and the updated target time period to continue execution. That is, the initial expression coefficients are recalculated until the preset stopping condition is met, and the target electron data pair is obtained.
[0078] In the above embodiments, when the terminal determines the target electron data pair, it obtains a more accurate intermediate fitted electron content by fitting. Then, based on the residual between the intermediate fitted electron content and the corresponding monitored electron content, it determines whether to retain the intermediate fitted electron content and the monitored electron content. Furthermore, for the next moment of the target time period, the corresponding intermediate fitted electron content will be obtained. The target electron data pair obtained in this way is more reliable and effectively improves the accuracy of the subsequent prediction of the target electron content.
[0079] In one embodiment, the target electron data pair further includes an updated fitted electron content and a monitored electron content at the same time corresponding to the updated fitted electron content. The updated fitted electron content refers to the electron content calculated by updating the ionospheric expression and publishing the electron content after the difference between the intermediate fitted electron content and the monitored electron content at the next time step no longer meets a preset difference condition.
[0080] Specifically, when determining the updated fitted electron content and the monitored electron content at the same time corresponding to the updated fitted electron content, the terminal also includes the following steps:
[0081] Step S302: If the difference between the intermediate fitted electron content and the monitored electron content at the next moment does not meet the preset difference condition, then the published electron content and the monitored electron content in the electron dataset are interpolated to obtain the interpolated dataset.
[0082] If the difference between the intermediate fitted electron content and the monitored electron content at the next moment does not meet the preset difference condition, the terminal can update the coefficients of the initial expression to obtain the updated fitted electron content. Specifically, after updating the fitted electron content, the published electron content and the monitored electron content in the electron dataset can be interpolated to increase the amount of data in the target time period and obtain the published electron content at any time and any latitude and longitude coordinate in the target time period.
[0083] Specifically, when performing interpolation, the following formula can be used:
[0084]
[0085] The electron content of a point (at any time and with any latitude and longitude coordinates) can be expressed as a function of longitude L, latitude B, and epoch t, where t is the target time and Ti+1 and Ti are two adjacent epochs.
[0086] Step S304: Based on the interpolation dataset, update the coefficients of the initial expression to obtain the updated ionospheric expression.
[0087] After obtaining the interpolation dataset, the terminal can recalculate the coefficients of the initial expression, thereby obtaining the updated ionospheric expression.
[0088] When updating the coefficients of the initial expression, the terminal can use Kalman filtering to estimate and update the coefficients. Specifically, the basic principle of Kalman filtering is as follows:
[0089] For discrete systems, the function model is as follows:
[0090] X(k)=Φk，k-1 X(k-1)+W(k-1)
[0091] Z(k)=H k X(k)+Δ(k)
[0092] Where, Φ k，k-1 For t k-1 Time to t k The state transition matrix at time X k For in t k The state vector at time x k-1 For in t k-1 The state vector at time W k-1 For the system noise, H k Let be the observation matrix, and Δk be the observation noise.
[0093] Kalman filtering mainly consists of two stages: prediction and recursive updating. Specifically, it includes the following steps:
[0094] ① Using the state transition matrix Φ k，k-1 Calculation and t k The coefficient matrix value X at time t k =Φ k-1 X k-1 +ε, where Φ k-1 The state transition matrix is determined by solving the differential equation from the measured data, where s is random noise. The coefficient values at this point are the predicted values, denoted as X(k, k-1), t k The GNSS-VTEC value at time t is denoted as GTEC(k), and the GIM-VTEC value is denoted as TEC(k). The observation equation is GTEC(k) = f(TEC(k))X(k) + Δ, and f(TEC(k)) is denoted as H. k Where Δ is the residual between GNSS-TEC and GIM-TEC.
[0095]
[0096] ② Calculate the variance P, gain matrix K, and innovation matrix V of the predicted value, and filter to obtain the X(k) value, which is the updated coefficient value.
[0097]
[0098]
[0099] V(k, k-1) = GTEC(k) - H k X(k, k-1)
[0100] X(k) = X(k, k-1) + k k V(k, k-1)
[0101] Step S306: Based on the published electron content at the next moment of the target time period and the updated ionospheric expression, the updated fitted electron content at the next moment is obtained by fitting.
[0102] If T1, T2, and T3 are the target time periods, then the next time period is T4. The terminal can then use the published electron content at time T4 and the updated ionospheric expression to fit the updated fitted electron content at time T4.
[0103] Step S308: If the difference between the updated fitted electron content and the monitored electron content at the next time step meets the preset difference condition, then the updated fitted electron content and the monitored electron content at the next time step are retained.
[0104] The difference between the updated fitted electron content and the monitored electron content can refer to the residual. When the terminal determines that the residual meets the preset difference condition, the updated fitted electron content and the monitored electron content at the next moment can be retained.
[0105] In the above embodiments, when the terminal determines the target electron data pair, if the difference between the intermediate fitted electron content and the monitored electron content at the next moment does not meet the preset difference condition, an interpolation dataset will be generated, and the coefficients of the initial expression will be updated to obtain the updated fitted electron content. Based on the updated fitted electron content and the monitored electron content, the target electron data pair can be determined, thereby effectively improving the accuracy of the subsequent prediction of the target electron content.
[0106] In one embodiment, the method further includes: if the difference between the updated fitted electron content and the monitored electron content does not meet a preset difference condition, then the interpolation dataset is updated to obtain the updated interpolation dataset, and the steps of updating the initial expression coefficients based on the interpolation dataset to obtain the updated ionospheric expression are returned; when the number of times the interpolation dataset is updated reaches a preset update number threshold, and the difference between the updated fitted electron content and the monitored electron content still does not meet the preset difference condition, the published electron content and the monitored electron content at the next moment after the target time period are discarded.
[0107] When the terminal determines that the difference between the updated fitted electron content and the monitored electron content does not meet the preset difference condition, it will re-update the interpolation dataset using the above interpolation method to obtain a richer interpolation dataset, and update the initial expression coefficients again to obtain the updated ionospheric expression. If the number of times the terminal updates the interpolation dataset reaches the preset update number threshold, and the difference between the updated fitted electron content and the monitored electron content still does not meet the preset difference condition, the published electron content and monitored electron content at the next moment after the target time period will be discarded.
[0108] In the above embodiments, on the one hand, the terminal obtains the updated ionospheric expression by updating the interpolation dataset, thereby ensuring a more accurate target electron data pair. On the other hand, when the preset update threshold is reached, if the difference between the fitted electron content and the monitored electron content still does not meet the preset difference condition, the terminal will discard the published electron content and monitored electron content at the next moment after the target time period, thereby avoiding resource waste.
[0109] In one embodiment, the ionospheric index includes the solar radiation index and the geomagnetic activity index; the electron content prediction model includes a trend term, a periodic term, a holiday term, and an error term; inputting the ionospheric index and the target electron data pair into the electron content prediction model, and predicting the target electron content value through the electron content prediction model, includes: inputting the target electron data pair, the solar radiation index, and the geomagnetic activity index into the trend term, the periodic term, the holiday term, and the error term; performing aperiodic variation processing on the target electron data through the trend term; performing periodic variation processing on the target electron data through the periodic term; performing special event processing on the solar radiation index and the geomagnetic activity index through the holiday term; and performing error processing on the target electron data pair, the solar radiation index, and the geomagnetic activity index through the error term to obtain the corresponding processing results; and accumulating the processing results to predict the target electron content value.
[0110] The electron content prediction model can refer to the Prophet (time series prediction) model. Specifically, the expression for the electron content prediction model can be shown in the following formula:
[0111] y(t)=g(t)+s(t)+h(t)+ε t
[0112] The electron content prediction model mainly includes a trend term, a periodic term, a holiday term, and an error term. y(t) represents the value of the original time series at time t, g(t) represents the trend term of non-periodic changes such as piecewise linear growth or logical growth in the fitted time series, s(t) represents the periodic term (also known as the seasonal term) of various periodic changes in the fitted time series, h(t) represents the irregular holiday term (holiday effect), and ε... t This is the error term (Gaussian noise term).
[0113] After obtaining the target electron data pair, solar radiation index, and geomagnetic activity index, the terminal can input these data into the trend term, periodic term, holiday term, and error term. The trend term can process the target electron data for non-periodic changes, while the periodic term can process it for periodic changes. Specifically, when processing periodic changes, since the ionosphere exhibits periodicity and short-term diurnal variations, the model uses a Fourier series to represent the periodicity (i.e., the s(t) part), as shown in the following equation.
[0114]
[0115] Among them, c n Let be the coefficient to be estimated, satisfying P represents the period of the time series; the parameter N is the number of approximations used to fit the periodicity. Within a certain range, the larger N is, the better the fitting effect is on the complex changes in the periodicity of the series.
[0116] Holiday terms are used to process the solar radiation index and geomagnetic activity index for special events. For special event data, the geomagnetic index, solar radiation index, and Kp index are considered as prior data in h(t), making the model more robust to interference from special events. The expression for h(t) is shown below:
[0117]
[0118] Error processing is performed on the target electron data pair, solar radiation index, and geomagnetic activity index using an error term to obtain the corresponding processing results. Finally, all processing results are summed to predict the target electron content.
[0119] In the above embodiments, when the terminal predicts the target electron content, it can obtain accurate short-to-medium-term electron content predictions because it uses the Prophet (time series prediction) model.
[0120] In one embodiment, such as Figure 4 The following is a flowchart of a method for determining ionospheric data in one embodiment:
[0121] Among them, such as Figure 4The flowchart shown includes a data acquisition module, a data processing module, and a data broadcasting module. The data acquisition module acquires GIM and GNSS data, using VTEC data calculated from GNSS and ionospheric grid data released by IGS as prior values. Then, the GIM and GNSS data are input into the data processing module, along with geomagnetic indices, solar radiation indices, and Kp indices. The data is first processed through a Kalman filter and then fed into the Prophet model for training, fitting the predicted VTEC data. The specific implementation steps are as follows:
[0122] 1) First, acquire ionospheric grid products, and simultaneously acquire the geomagnetic index Dst, solar radiation index F10.7, and kp index. This is used to subsequently consider the impact of solar activity and geomagnetic storms on ionospheric values. Specifically, during acquisition, the data can be downloaded from a server. The IGS product time interval is 2 hours, covering 87.5°S~87.5°N. Depending on the user's target area, the VTEC value of a point can be expressed as a function of longitude L, latitude B, and epoch t, as shown in the following formula:
[0123]
[0124] Where t is the target time, and Ti+1 and Ti are two adjacent epochs.
[0125] 2) GNSS Data Acquisition. GNSS-related data includes precise satellite ephemeris, satellite orbit data, O-files, N-files, satellite clock bias data, etc. The GNSS-VTEC value is obtained by smoothing the pseudorange using carrier phase. The GNSS-VTEC value is calculated as follows:
[0126]
[0127]
[0128] In this system, superscripts i and j represent different epochs, subscript k represents different carrier frequencies, P represents pseudorange observations, and L represents carrier phase observations. ρ is the distance from the receiver to the satellite, c represents the speed of light, superscripts T and R represent the satellite and receiver respectively, N represents the integer ambiguity of the carrier phase observation, Ion represents ionospheric delay, Tro represents tropospheric delay, d and b represent hardware delay, M and m represent multipath error, and ε represents observation noise.
[0129] The expression for TEC can be obtained from the observation equation as follows:
[0130]
[0131]
[0132] Since the ambiguity remains constant throughout the continuous observation period, and the system's hardware delay tends to stabilize and can be considered constant, processing the carrier phase observations and pseudorange observations yields a high-precision absolute TEC value at time N. Then, based on the projection function, a high-precision GNSS-VTEC value can be obtained.
[0133]
[0134] 3) A polynomial model is used to fit the VTEC value, and the formula is as follows, where B is latitude, L is longitude, and VTEC0 is the GIM-VTEC value.
[0135] VTEC=a0B 2 +a1B+a2L 2 +a3L+a4VTEC0+a5VTEC0+a6
[0136] The VTEC value is updated and predicted using Kalman filtering, and a maximum a posteriori estimation is performed. Data with large variance and significant solar or geomagnetic activity on the same day are marked as special events, while data with large variance but no significant geomagnetic or solar activity are discarded.
[0137] The state equation for the Kalman filter is shown below.
[0138]
[0139] For discrete systems, the function model is as follows:
[0140] X(k)=Φ k，k-1 X(k-1)+W(k-1)
[0141] Z(k)=H k X(k)+Δ(k)
[0142] Where Φ k，k-1 For t k-1 Time to t k The state transition matrix at time X k For in t k The state vector at time X k-1 For in t k-1 The state vector at time W k-1 For the system noise, H k Let be the observation matrix, and Δ(k) be the observation noise. Kalman filtering mainly has two stages: first, predicting the filter, and second, recursively updating it.
[0143] ① In terms of filtering prediction, the state is predicted based on the changing characteristics of the entire system. The predicted state is treated as a virtual observation, and then the actual observation is introduced to estimate the state together. The formulas for state prediction and variance prediction are as follows:
[0144]
[0145]
[0146] ② Regarding filtering updates, a difference information matrix V between the predicted and actual observed values is set. z With the gain matrix K k As shown in the following formula:
[0147] V Z (k, k-1) = Z(k) - Z(k, k-1)
[0148]
[0149] The magnitude of the gain matrix Kk determines the degree of influence of the observed value on the filtered value X. The state value can be updated using the gain matrix and the innovation matrix. The following formulas represent the updated filter and the variance of the filter:
[0150]
[0151]
[0152] 4) The VTEC values obtained by Kalman filtering and GNSS-VTEC are fed into the Prophet model for training to obtain high-precision VTEC forecast values. The Prophet model directly combines historical data for smoothing and prediction, without requiring preprocessing such as interpolation or stabilization. It is a fitting additive model with good fitting performance for ionospheric discrete and high-noise data. The Prophet model is as follows:
[0153] y(t)=g(t)+s(t)+h(t)+ε t
[0154] Where y(t) is the value of the original time series at time t, g(t) is the trend term of non-periodic changes such as piecewise linear growth or logistic growth in the fitted time series, s(t) is the seasonal or periodic term of various periodic changes in the fitted time series, h(t) is the irregular holiday effect, and ε t This is the error term, also known as the Gaussian noise term.
[0155] Since the transformation of the ionosphere is periodic, exhibiting diurnal variation in the short term, the periodicity is represented by a Fourier series in the model (i.e., the s(t) part), as shown in the following equation.
[0156]
[0157] Among them, c n Let be the coefficient to be estimated, satisfying P represents the period of the time series; the parameter N is the number of approximations used to fit the periodicity. Within a certain range, the larger N is, the better the fitting effect is on the complex changes in the periodicity of the series.
[0158] For data on special events, the geomagnetic index, solar radiation index, and Kp index are considered as prior data in h(t), making the model more robust to interference from special events. The expression for h(t) is as follows:
[0159]
[0160] The VTEC values obtained in this way have a better initial value, resulting in a longer validity period and higher accuracy compared to the ordinary Prophet model. Finally, the predicted VTEC values are broadcast to users through the data broadcasting module. In practical implementation, this system can be automated by combining computer software technology, from data acquisition to data processing and data broadcasting.
[0161] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.
[0162] Based on the same inventive concept, this application also provides an ionospheric data determination apparatus for implementing the ionospheric data determination method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the ionospheric data determination apparatus provided below can be found in the limitations of the ionospheric data determination method described above, and will not be repeated here.
[0163] In one embodiment, such as Figure 5 As shown, an ionospheric data determination device is provided, comprising: a data acquisition module, a data processing module, and a prediction module, wherein:
[0164] The data acquisition module 502 is used to acquire ionospheric parameters, including the ionospheric index, the published electron content at each preset time, and the monitored electron content at each preset time.
[0165] The data processing module 504 is used to filter the published electron content and monitored electron content at each preset time to obtain the target electron data pair after filtering.
[0166] The prediction module 506 is used to input the ionospheric index and target electron data into the electron content prediction model, and obtain the target electron content prediction value through the electron content prediction model.
[0167] In one embodiment, the target electron data pair includes intermediate fitted electron content and monitored electron content at the same time corresponding to the intermediate fitted electron content. The data processing module is further configured to determine an electron dataset corresponding to a target time period, the target time period including a preset number of consecutive preset times, and the electron dataset including the published electron content and monitored electron content within the target time period; determine the initial expression coefficients of the initial ionospheric expression based on the electron dataset to obtain the intermediate ionospheric expression; fit the intermediate fitted electron content at the next time period based on the published electron content at the next time period and the intermediate ionospheric expression; if the difference between the intermediate fitted electron content and the monitored electron content at the next time period meets a preset difference condition, then retain the intermediate fitted electron content and the monitored electron content at the next time period; add the published electron content and the monitored electron content at the next time period to the electron dataset; update the target time period based on the next time period; and return to the step of determining the initial expression coefficients of the initial ionospheric expression based on the electron dataset based on the updated electron dataset and the updated target time period to continue execution until a preset stopping condition is met, thereby obtaining the target electron data pair.
[0168] In one embodiment, the target electron data pair further includes an updated fitted electron content and a monitored electron content at the same time corresponding to the updated fitted electron content; the data processing module is further configured to, if the difference between the intermediate fitted electron content and the monitored electron content at the next time moment does not meet a preset difference condition, perform interpolation processing on the published electron content and the monitored electron content in the electron dataset to obtain an interpolated dataset; update the coefficients of the initial expression based on the interpolated dataset to obtain an updated ionospheric expression; fit the updated fitted electron content at the next time moment according to the published electron content at the next time moment of the target time period and the updated ionospheric expression; if the difference between the updated fitted electron content and the monitored electron content at the next time moment meets the preset difference condition, then retain the updated fitted electron content and the monitored electron content at the next time moment.
[0169] In one embodiment, the data processing module is further configured to update the interpolation dataset if the difference between the updated fitted electron content and the monitored electron content does not meet a preset difference condition, obtain an updated interpolation dataset, and return a step of updating the initial expression coefficients based on the interpolation dataset to obtain an updated ionospheric expression; when the number of times the interpolation dataset is updated reaches a preset update number threshold, and the difference between the updated fitted electron content and the monitored electron content still does not meet the preset difference condition, the published electron content and monitored electron content at the next moment after the target time period are discarded.
[0170] In one embodiment, the data acquisition module is further configured to acquire an ionospheric grid product file and read the published electron content at each preset time in the target area from the ionospheric grid product file; acquire the ionospheric index corresponding to the target area; acquire the satellite system monitoring data corresponding to the target area; and determine the monitored electron content at each preset time based on the satellite system monitoring data.
[0171] In one embodiment, the ionospheric index includes the solar radiation index and the geomagnetic activity index; the electron content prediction model includes a trend term, a periodic term, a holiday term, and an error term; the prediction module is further configured to input the target electron data pair, the solar radiation index, and the geomagnetic activity index into the trend term, the periodic term, the holiday term, and the error term; perform aperiodic variation processing on the target electron data through the trend term; perform periodic variation processing on the target electron data through the periodic term; perform special event processing on the solar radiation index and the geomagnetic activity index through the holiday term; and perform error processing on the target electron data pair, the solar radiation index, and the geomagnetic activity index through the error term to obtain the corresponding processing results; and accumulate the processing results to predict the target electron content value.
[0172] Each module in the aforementioned ionospheric data determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.
[0173] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements an ionospheric data determination method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.
[0174] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0175] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described ionospheric data determination method.
[0176] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described ionospheric data determination method.
[0177] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the above-described ionospheric data determination method.
[0178] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.
[0179] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.
[0180] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0181] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.
Claims
1. A method for determining ionospheric data, characterized in that, The method includes: The ionospheric parameters are obtained, including the ionospheric index, the published electron content at each preset time, and the monitored electron content at each preset time. The published electron content and monitored electron content at each preset time are filtered out to obtain the target electron data pair after filtering. The ionospheric index and the target electron data are input into the electron content prediction model, and the target electron content prediction value is obtained by the electron content prediction model. The target electron data pair includes the intermediate fitted electron content and the monitored electron content at the same time corresponding to the intermediate fitted electron content; The step of filtering out the published electron content and monitored electron content at each preset time to obtain the target electron data pair after filtering includes: Determine the electronic dataset corresponding to the target time period, wherein the target time period includes a preset number of consecutive preset moments, and the electronic dataset includes the published electronic content and the monitored electronic content within the target time period; The initial expression coefficients of the initial ionosphere expression are determined based on the electron dataset, and the intermediate ionosphere expression is obtained. Based on the published electron content at the next moment after the target time period and the intermediate ionosphere expression, the intermediate fitted electron content at the next moment is obtained by fitting. If the difference between the intermediate fitted electron content and the monitored electron content at the next time moment meets the preset difference condition, then the intermediate fitted electron content and the monitored electron content at the next time moment are retained. The published electron content and monitored electron content at the next moment are added to the electron dataset. The target time period is updated based on the next moment. Based on the updated electron dataset and the updated target time period, the step of determining the initial expression coefficients of the initial ionospheric expression based on the electron dataset is returned to continue execution until the preset stopping condition is met, and the target electron data pair is obtained.
2. The method according to claim 1, characterized in that, The target electron data pair further includes an updated fitted electron content and a monitored electron content at the same time corresponding to the updated fitted electron content. The method further includes: If the difference between the intermediate fitted electron content and the monitored electron content at the next time moment does not meet the preset difference condition, then the published electron content and the monitored electron content in the electron dataset are interpolated to obtain the interpolated dataset. Based on the interpolation dataset, the coefficients of the initial expression are updated to obtain the updated ionospheric expression; Based on the published electron content at the next moment of the target time period and the updated ionospheric expression, the updated fitted electron content at the next moment is obtained by fitting. If the difference between the updated fitted electron content and the monitored electron content at the next time step satisfies the preset difference condition, then the updated fitted electron content and the monitored electron content at the next time step are retained.
3. The method according to claim 2, characterized in that, The method further includes: If the difference between the updated fitted electron content and the monitored electron content does not meet the preset difference condition, the interpolation dataset is updated to obtain the updated interpolation dataset, and the steps of updating the initial expression coefficients based on the interpolation dataset are returned to obtain the updated ionospheric expression. When the number of times the interpolation dataset is updated reaches a preset update threshold, and the difference between the updated fitted electron content and the monitored electron content still does not meet the preset difference condition, the published electron content and monitored electron content at the next moment after the target time period are discarded.
4. The method according to claim 1, characterized in that, The acquisition of ionospheric parameters includes: Obtain the ionospheric grid product file, and read the published electron content at each preset time in the target area from the ionospheric grid product file; Obtain the ionospheric index corresponding to the target region; Obtain satellite system monitoring data corresponding to the target area; Based on the monitoring data from the satellite system, the monitoring electron content at each preset time is determined.
5. The method according to claim 1, characterized in that, The ionospheric index includes the solar radiation index and the geomagnetic activity index; the electron content prediction model includes a trend term, a periodic term, a holiday term, and an error term. The step of inputting the ionospheric index and the target electron data pair into the electron content prediction model, and predicting the target electron content value through the electron content prediction model, includes: The target electron data pair, solar radiation index, and geomagnetic activity index are input into the trend term, periodic term, holiday term, and error term. The target electron data is processed for non-periodic changes through the trend term, for periodic changes through the periodic term, for special events through the holiday term, and for errors through the error term, to obtain the corresponding processing results. The results of each processing step are summed to obtain the predicted value of the target electron content.
6. An ionospheric data determination device, characterized in that, The device includes: The data acquisition module is used to acquire ionospheric parameters, including the ionospheric index, the published electron content at each preset time, and the monitored electron content at each preset time. The data processing module is used to filter the published electron content and monitored electron content at each preset time to obtain the target electron data pair after filtering. The prediction module is used to input the ionospheric index and the target electron data into the electron content prediction model, and to predict the target electron content value through the electron content prediction model. The target electron data pair includes the intermediate fitted electron content and the monitored electron content at the same time corresponding to the intermediate fitted electron content; The data processing module is further configured to determine an electronic dataset corresponding to a target time period, wherein the target time period includes a preset number of consecutive preset times, and the electronic dataset includes the emitted electron content and the monitored electron content within the target time period; determine the initial expression coefficients of the initial ionospheric expression based on the electronic dataset to obtain an intermediate ionospheric expression; fit the emitted electron content at the next time period after the target time period and the intermediate ionospheric expression to obtain the intermediate fitted electron content at the next time period; if the difference between the intermediate fitted electron content and the monitored electron content at the next time period meets a preset difference condition, then retain the intermediate fitted electron content and the monitored electron content at the next time period; add the emitted electron content and the monitored electron content at the next time period to the electronic dataset; update the target time period based on the next time period; and return to the step of determining the initial expression coefficients of the initial ionospheric expression based on the electronic dataset based on the updated electronic dataset and the updated target time period to continue execution until a preset stopping condition is met, thereby obtaining a target electron data pair.
7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.
8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.
9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.