Autonomous solar radio F10.7 index calibration method and device

Abstract

The invention provides an autonomous solar radio F10.7 index calibration method and device, and the method comprises the steps: obtaining original data, and carrying out the preprocessing of the original data; the original data comprises autonomous observation data and international data; determining a correction factor S0 based on the original data, and performing abnormal value detection on the correction factor S0; performing trend and difference value double-feedback optimization and physical constraint correction on the correction factor S0; and determining an autonomous F10.7 index based on the corrected correction factor S0, and carrying out homogenization processing on the autonomous F10.7 index to obtain a final autonomous F10.7 index. According to the method and the device, the difficulty of deviation accumulation caused by a static initial value of a traditional method can be overcome, and the problem of poor precision of independent measurement and calculation of the F10.7 index in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of solar activity monitoring technology, and in particular to an autonomous solar radio F10.7 index calibration method and device. Background Technology

[0002] The solar radio flux index at the F10.7 cm band (F10.7 index) is a good indicator of the intensity of solar activity and has become one of the core parameters of solar activity intensity. Because the F10.7 index can be monitored and acquired from the ground over long periods, it is commonly used as an input in many important ionospheric and upper-atmosphere models to represent solar activity levels. Therefore, monitoring and acquiring the F10.7 index will play a crucial role in solar activity forecasting and research, both in the past, present, and future. However, existing space weather activity forecasts based on F10.7 are mainly based on international monitoring data. Currently, several independent solar radio flux monitoring platforms have been built (such as the Langfang Radio Telescope platform), and a basic F10.7 index calibration process has been established. However, in practical engineering applications, the current calibration method still has core issues that require optimization.

[0003] 1. Traditional correction mechanisms are rigid and lack stability: Traditional correction factors S0 (the core coefficient for calibrating domestic local observational data with the international F10.7 index) often employ a fixed threshold method. If the S0 correction factor value is greater than or equal to a certain threshold, it is considered an outlier and immediately adjusted to a fixed value (26.12). However, this method fails to adequately differentiate the S0 calibration factor if the F10.7 data being tested is excessively large (an F10.7 index greater than 250 sfu is considered large) or if extreme solar activity scenarios occur. This results in significant fluctuations in the S0 calibration factor with the observed data, thus affecting the stability of the autonomous F10.7 index.

[0004] 2. System feedback optimization was not performed: The original calibration method failed to combine the historical trend of the correction factor S0 with the residual values ​​of the international F10.7 index and the domestic F10.7 index on the corresponding dates for iterative optimization. It could not make good use of the core patterns of time series data, making it difficult to reduce systematic errors. As a result, the S0 correction factor deviated from the actual value for a long time, and the gap between the domestic domestic F10.7 data and the international F10.7 index accumulated.

[0005] 3. Low degree of autonomy, heavily reliant on international data: The existing F10.7 index data all use the international F10.7 index released by the Penticton Observatory in Canada as the sole standard. If the international F10.7 index is delayed or interrupted on the same day, the domestic space environment business will be in a passive situation. Moreover, many domestic independent solar radio platforms can now independently acquire raw data, but they lack a good calibration method, making it difficult to fit the international F10.7 index.

[0006] There is currently no effective solution to the problem of poor accuracy in the independent calculation of the F10.7 exponent in existing related technologies. Summary of the Invention

[0007] This invention provides an autonomous solar radio F10.7 index calibration method and apparatus to address the shortcomings of existing related technologies in terms of poor accuracy of autonomous F10.7 index calculation.

[0008] In a first aspect, the present invention provides an autonomous solar radio F10.7 index calibration method, comprising: Acquire raw data and preprocess the raw data; the raw data includes autonomous observation data and international data; Based on the original data, a correction factor S0 is determined, and outlier detection is performed on the correction factor S0. The correction factor S0 is optimized using both trend and difference feedback, as well as physical constraint correction. The autonomous F10.7 index is determined based on the modified correction factor S0, and the autonomous F10.7 index is homogenized to obtain the final autonomous F10.7 index.

[0009] According to the autonomous solar radio F10.7 index calibration method provided by the present invention, raw data is acquired and the raw data is preprocessed, including: Multiple files that meet specific time conditions are selected from the autonomous observation data as the solar radiation data and cold air radiation data for the day, and the mean is calculated and zero value is processed. The international F10.7 index is obtained, and the international F10.7 index is processed to unify its format so that the international F10.7 index is consistent with the format of the autonomous observation data.

[0010] According to the autonomous solar radio F10.7 index calibration method provided by the present invention, the mean calculation and zero-value detection processing are performed, including: The average values ​​of the daily solar radiation data and the daily cold air radiation data are calculated to obtain the average daily solar radiation data and the average daily cold air radiation data. If the number of files selected within a time period does not reach the preset standard, the average value of the corresponding data will be assigned to zero. Detect all zero values; if a zero value appears on the first day, assign zero to the mean of the following day. If the zero value appears on the last day, then the mean of the previous day is assigned the zero value.

[0011] According to the present invention, an autonomous solar radio F10.7 index calibration method is provided, which determines the correction factor S0 based on the original data, including: Calculate the ratio of the average daily cold air radiation data to the average daily solar radiation data; The correction factor S0 is determined by multiplying the ratio by the international F10.7 index.

[0012] According to the autonomous solar radio F10.7 index calibration method provided by the present invention, outlier detection is performed on the correction factor S0, including: Based on the solar flux of the international F10.7 index, determine whether the date corresponding to the correction factor S0 is a date of extreme solar activity; On days of extreme solar activity, it is determined whether the value of the correction factor S0 exceeds the standard threshold. If so, the correction factor S0 is identified as an outlier and anomaly processing is performed. If the correction factor S0 does not exceed the standard threshold, then based on 3 The principle is to determine whether the correction factor S0 meets the monitoring data error. If it does, the correction factor S0 is handled as an anomaly.

[0013] According to the autonomous solar radio F10.7 index calibration method provided by the present invention, if the correction factor S0 exceeds the standard threshold, the correction factor S0 is subjected to mean smoothing. If the correction factor S0 satisfies the monitoring data error, then the median of the correction factor S0 over N days is used to replace the current correction factor S0.

[0014] According to the autonomous solar radio F10.7 index calibration method provided by the present invention, the correction factor S0 is optimized by trend and difference dual feedback, including: Calculate the rolling average of the international F10.7 index and the rolling average of the autonomous F10.7 index over the past N days, and determine the trend ratio; The correction factor S0 after outlier processing is trend-adjusted based on the trend ratio. Calculate the difference between the international F10.7 index and the domestic F10.7 index over the past M days, and then calculate the average of the differences. The correction factor S0 is calibrated based on the mean of the differences.

[0015] According to the autonomous solar radio F10.7 index calibration method provided by the present invention, the correction factor S0 is physically constrained and corrected, including adjusting the reasonable range of the correction factor S0 to [25, 40].

[0016] According to the present invention, an autonomous solar radio F10.7 index calibration method is provided, which determines the autonomous F10.7 index based on the corrected correction factor S0, and homogenizes the autonomous F10.7 index to obtain the final autonomous F10.7 index, including: Calculate the ratio of the average daily solar radiation data to the average daily cold air radiation data, and determine the autonomous F10.7 index by combining the correction factor S0; Calculate the root mean square error and correlation coefficient between the autonomous F10.7 index and the international F10.7 index; The autonomous F10.7 index under non-solar extreme activity conditions was averaged. The root mean square error and correlation coefficient of the homogenized autonomous F10.7 index and the international F10.7 index are calculated and compared with the initial root mean square error and correlation coefficient. The autonomous F10.7 index with the smallest root mean square error and the highest correlation coefficient is retained as the final autonomous F10.7 index.

[0017] Secondly, the present invention also provides an autonomous solar radio F10.7 index calibration device, comprising: An acquisition module is used to acquire raw data and preprocess the raw data; the raw data includes autonomous observation data and international data. The detection module is used to determine the correction factor S0 based on the original data and to perform outlier detection on the correction factor S0. The optimization module is used to perform trend and difference dual feedback optimization and physical constraint correction on the correction factor S0; The processing module is used to determine the autonomous F10.7 index based on the modified correction factor S0, and to homogenize the autonomous F10.7 index to obtain the final autonomous F10.7 index.

[0018] Thirdly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the autonomous solar radio F10.7 index calibration method as described in the first aspect above.

[0019] In a fourth aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the autonomous solar radio F10.7 index calibration method as described in the first aspect above.

[0020] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the autonomous solar radio F10.7 index calibration method as described in the first aspect above.

[0021] Compared with the prior art, the present invention has the following beneficial effects: The autonomous solar radio F10.7 index calibration method provided by this invention overcomes the difficulty of deviation accumulation caused by static initial values ​​in traditional methods by combining outlier correction of correction factor S0, trend calibration and residual calibration, physical constraints and meanization processing. It also solves the problem of poor accuracy of autonomous F10.7 index calculation in existing related technologies. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart of the autonomous solar radio F10.7 index calibration method provided by the present invention; Figure 2 This is a flowchart of outlier detection and dynamic calibration in an embodiment of the present invention; Figure 3 This is a flowchart illustrating the dual optimization of trend calibration and difference calibration in this embodiment of the invention; Figure 4 This is a structural block diagram of the autonomous solar radio F10.7 index calibration device provided by the present invention; Figure 5 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0025] This invention provides an autonomous solar radio F10.7 index calibration method. Figure 1 This is a flowchart of the autonomous solar radio F10.7 index calibration method provided by the present invention, as shown below. Figure 1 As shown, the method includes the following steps: Step S101: Obtain raw data and preprocess the raw data; the raw data includes autonomous observation data and international data. Step S102: Determine the correction factor S0 based on the original data, and perform outlier detection on the correction factor S0. Step S103: Perform trend and difference dual feedback optimization and physical constraint correction on the correction factor S0; Step S104: Determine the autonomous F10.7 index based on the corrected correction factor S0, and homogenize the autonomous F10.7 index to obtain the final autonomous F10.7 index.

[0026] In this method, firstly, raw data is acquired and preprocessed to facilitate subsequent use. Then, a correction factor S0 is determined based on the raw data, and outlier detection is performed on S0. Outliers in the correction factor S0 are a key factor affecting its stability. By detecting and correcting outliers in S0, unnecessary losses caused by undetected extreme solar activity can be addressed, achieving accurate positioning and rebound calibration. To correct systematic biases in the correction factor S0, this method also performs trend and difference dual-feedback optimization and physical constraint correction. Finally, the autonomous F10.7 index is determined based on the corrected correction factor S0 and homogenized to obtain the final autonomous F10.7 index. In the above process, the combined processing of outlier correction, trend and residual calibration, physical constraints, and averaging of the correction factor S0 overcomes the difficulty of bias accumulation caused by static initial values ​​in traditional methods, solving the problem of poor accuracy in autonomous F10.7 index calculation in existing related technologies.

[0027] To address issues such as missing raw data and inconsistent date formats, in some embodiments, step S101 involves acquiring raw data and preprocessing it, including: selecting multiple files from the autonomous observation data that meet specific time conditions as the solar radiation data and cold air radiation data for the day, and performing mean calculation and zero value processing; acquiring the international F10.7 index and performing format unification processing on the international F10.7 index to ensure that the format of the international F10.7 index is consistent with that of the autonomous observation data.

[0028] Specifically, the process involves averaging and zero-value detection, including: calculating the average value based on the daily solar radiation data and the daily cold air radiation data to obtain the daily average solar radiation data and the daily average cold air radiation data; assigning zero to the average value of the corresponding data if the number of files selected within a time period does not reach a preset standard; detecting all zero values, assigning zero to the average value of the following day if a zero value appears on the first day; and assigning zero to the average value of the previous day if a zero value appears on the last day.

[0029] For example, for self-observational data, four files meeting specific time conditions between 12:00 and 14:00 are selected from the daily raw data as the solar radiation data for that day, and four files meeting specific time conditions between 0:00 and 2:00 are selected as the cold air radiation data for that day. If fewer than four files are selected within a time period, they are treated the same as all missing data for that day, and are automatically assigned a zero value when calculating the daily file average. After the daily files generate the daily solar radiation average and the daily cold air radiation average, all zero values ​​are checked. If a zero value appears on the first day, the value of the following day is assigned a zero value; if it is the last day, the data value of the previous day is assigned a zero value; for the remaining days, the average of the preceding and following days is used.

[0030] For international data, the F10.7 index published by the Penticton Observatory in Canada was retrieved. The daily automatically acquired data was formatted uniformly, and duplicates were removed by the DATE field to ensure that one DATE corresponds to only one F10.7 index. The format of the DATE field column was standardized to be the same as the DATE format generated by the preprocessing of the self-observation data, i.e., YYYY / MM / DD, to avoid data matching errors caused by DATE format issues.

[0031] In some embodiments, step S102, determining the correction factor S0 based on the original data, includes: calculating the ratio of the average daily cold air radiation data to the average daily solar radiation data; and determining the correction factor S0 based on the product of the ratio and the international F10.7 index.

[0032] The correction factor S0 is actually the ratio coefficient between domestic local observation data and international standard data. It is an essential coefficient for outputting the independent F10.7 index. When there are no abnormalities in domestic monitoring data, the difference between the independent F10.7 index and the international F10.7 index fundamentally depends on the value of the correction factor S0. The key to fitting the international F10.7 index is to properly handle the correction factor S0.

[0033] For example, the formula for calculating the correction factor S0 is as follows:

[0034] Wherein, solar_mean represents the average daily solar radiation data, and sky_mean represents the average daily cold air radiation data. In this embodiment, the international F10.7 is the standard F10.7 index released by the Penticton Observatory in Canada for the previous day; solar_mean is also the solar data received by the domestic observatory on the previous day (the same day as the international F10.7) between 12:00 and 14:00, prioritizing four data points that meet the criteria and receiving them via channel 2840. The power is then converted from logarithmic to linear, and the mean of the four data points is calculated to obtain the solar_mean data for the current day; the sky_mean data can be obtained in the same way.

[0035] Based on this, step S102 involves outlier detection of the correction factor S0, including: determining whether the date corresponding to the correction factor S0 is a date of extreme solar activity based on the solar flux of the international F10.7 index; on days of extreme solar activity, determining whether the value of the correction factor S0 exceeds the standard threshold; if so, the correction factor S0 is identified as an outlier and anomaly processing is performed; if the correction factor S0 does not exceed the standard threshold, then based on 3 The principle is to determine whether the correction factor S0 meets the monitoring data error. If it does, then the correction factor S0 is handled as an anomaly.

[0036] In this embodiment, if the correction factor S0 exceeds the standard threshold, mean smoothing is applied to the correction factor S0; if the correction factor S0 meets the monitoring data error, the median of the correction factor S0 over N days is used to replace the current correction factor S0.

[0037] For example, Figure 2 This is a flowchart of outlier detection and dynamic calibration in an embodiment of the present invention, as shown below. Figure 2 As shown, firstly, extreme solar activity is assessed. When the international F10.7 index is less than or equal to 300 sfu (sfu is a unit of solar flux), it is considered normal solar activity and no outlier calibration is triggered. Conversely, it is considered extreme solar activity, and an anomaly assessment using the correction factor S0 is performed.

[0038] When the international F10.7 index exceeds 300 sfu, the correction factor S0 for that day is then assessed. If its value exceeds a certain threshold, the S0 value for that day is classified as an outlier. According to the formula for calculating the correction factor S0, the value of the correction factor S0 for that day is affected by the extreme solar activity of the previous day. However, since the domestic independent radio platform did not capture any extreme solar eruption activity that day, to avoid this value having a greater impact on the F10.7 index of the following day, it is processed as an outlier.

[0039] If the value of the correction factor S0 is less than its threshold, then based on 3 The principle is to determine whether the candidate correction factor S0 meets the monitoring data error criteria. Calculate the rolling mean and rolling standard deviation of the correction factor S0 over the past N days (rolling window size). If the candidate correction factor S0 meets the following formula, it is determined to be an outlier caused by observation error, and outlier processing is performed. The specific formula is as follows:

[0040] Where S0_candidate represents the candidate correction factor S0, roll_mean represents the rolling mean of correction factor S0 over the past N days, and roll_std represents the rolling standard deviation of correction factor S0 over the past N days.

[0041] If the current correction factor S0 exceeds the threshold range set for extreme solar activity due to the influence of the previous day's extreme solar activity, mean smoothing is applied to it, as shown in the following formula:

[0042] Where S0_prev is the previous day's correction factor S0 data.

[0043] Under extreme solar activity, the correction factor S0 does not exceed the threshold but satisfies 3. In principle, the median of the correction factor S0 over N days is used to replace the abnormal candidate correction factor S0.

[0044] To correct the systematic bias of the correction factor S0, in some embodiments, step S103 involves performing trend and difference dual-feedback optimization on the correction factor S0, including: calculating the rolling average of the international F10.7 index and the rolling average of the autonomous F10.7 index over the past N days, and determining the trend ratio; adjusting the correction factor S0 after outlier processing based on the trend ratio; calculating the difference between the international F10.7 index and the autonomous F10.7 index over the past M days, and obtaining the average difference; and calibrating the correction factor S0 based on the average difference.

[0045] For example, Figure 3 This is a flowchart of the dual optimization of trend calibration and difference calibration in an embodiment of the present invention, as shown below. Figure 3 As shown, for the international index trend, the rolling average of the international F10.7 index over the past N days (foreign_roll_trend) is calculated. For the autonomous index trend, the rolling average of the autonomously generated F10.7 index over the past N days is calculated based on the historical correction factor S0 and the solar radio radiation power data for the same period. The specific formula is as follows:

[0046] Here, `gen_roll_trend` represents the rolling average of the self-generated F10.7 exponent. Then, the trend ratio is calculated using the following formula:

[0047] Where foreign_roll_trend represents the rolling average of the international F10.7 index. To avoid extreme ratios, a reasonable range is set based on historical data, constraining the trend ratio within the interval [0.7, 1.3]. Then, the trend adjustment of the correction factor S0 is performed, with the specific formula as follows:

[0048] After trend calibration, difference calibration is performed. Daily, the difference between the previously generated F10.7 index (S0×solar_mean / sky_mean) and the international F10.7 index is added: Difference = Autonomous F10.7 Index - International F10.7 Index, retaining the difference from the most recent 10 days (to avoid the influence of outdated data). When the difference data volume is greater than or equal to 5 days (residual_roll_window=5), the mean of the differences from the most recent 5 days (residual_mean) is calculated, and the correction factor S0 is adjusted accordingly based on this mean. The specific formula is as follows:

[0049] Wherein, residual_mean represents the mean of the differences. In this embodiment, the correction logic is as follows: if the mean of the differences is positive (the autonomous F10.7 index is high), then the correction factor S0 is decreased; otherwise, the correction factor S0 is increased to ensure that the residuals converge relatively.

[0050] In some of these embodiments, the correction factor S0 is physically constrained, including adjusting the reasonable range of the correction factor S0 to [25, 40].

[0051] Based on long-term observation data from my country's Langfang independent radio telescope platform, the reasonable range for the correction factor S0 is adjusted to [25, 40]. A correction factor S0 below 25 will lead to an underestimation of the autonomous F10.7 index, so the correction factor S0 is brought back to 25. A correction factor S0 above 40 will lead to an overestimation of the autonomous F10.7 index, so the correction factor S0 is brought back to 40. Therefore, the final correction factor S0 must meet the following conditions. .

[0052] Based on the above embodiments, step S104, determining the autonomous F10.7 index based on the corrected correction factor, and homogenizing the autonomous F10.7 index to obtain the final autonomous F10.7 index, includes: calculating the ratio of the average daily solar radiation data to the average daily cold air radiation data, and determining the autonomous F10.7 index in combination with the correction factor S0; calculating the root mean square error and correlation coefficient between the autonomous F10.7 index and the international F10.7 index; homogenizing the autonomous F10.7 index under non-solar extreme activity; calculating the root mean square error and correlation coefficient between the homogenized autonomous F10.7 index and the international F10.7 index, and comparing them with the initial root mean square error and correlation coefficient, retaining the autonomous F10.7 index with the smallest root mean square error and the highest correlation coefficient as the final autonomous F10.7 index.

[0053] For example, the autonomous F10.7 index is calculated based on the correction factor S0 obtained from the previous day and the solar_mean / sky_mean of the current day. The autonomous F10.7 index is calculated as follows:

[0054] The correction factor S0 is the same day that is calibrated with the international F10.7 index, which is the previous day of solar_mean and sky_mean in the formula.

[0055] For the finally generated autonomous F10.7 index, its root mean square error (RMSE) and correlation coefficient (COR) with the international F10.7 index are calculated. Next, the autonomous F10.7 index values ​​under non-solar extreme activity conditions are averaged (i.e., smoothed by moving average) using a time window M, centered, to generate a new autonomous F10.7 index. The RMSE and correlation coefficient of the new data with international data are then calculated. Comparing the two indices of the original autonomously generated F10.7 data and the newly generated F10.7 data under international data, the index with the smallest RMSE and the highest correlation coefficient is retained as the final autonomous F10.7 index.

[0056] If the international F10.7 index data is interrupted or delayed on any given day, the domestically calculated F10.7 index can be obtained using the above formula, based on the previously calculated correction factor S0 (after optimization) and the solar radio radiation power monitored domestically that day. The correction factor S0 is updated daily based on monitoring data and the international F10.7 index, accurately capturing the daily fluctuations in solar activity and ensuring that the final calculated index value more closely approximates the true international F10.7 index.

[0057] To verify the accuracy of the correction factor S0 in the above method, the root mean square error (RMSE) and correlation coefficient are used to evaluate S0. The smaller the RMSE (the more accurate the S0 calculation), and the closer the correlation coefficient is to 1 (the better the fit between the independent and international F10.7 index), the more accurate the calculation is. The formulas are as follows:

[0058]

[0059] in, N Indicates the number of days. i The date number is indicated. For performance verification, using raw data from the independent Langfang radio telescope platform for a full year (July 10, 2024 to July 9, 2025) and raw data from January 28, 2022 to September 13, 2022 (229 days), the results of comparing this method with traditional methods and the international F10.7 index are shown in Table 1. Table 1. Comparison of this method, traditional method, and international F10.7 index.

[0060] As shown in the table above, the bias accumulation problem caused by the static initial values ​​of the original method can be solved by combining trend calibration and residual calibration of the correction factor S0, physical constraints, and meanization. In terms of the fit between the domestic F10.7 index and the international F10.7 index in 2022, the current method reduces the RMSE by 3.302 and increases the correlation coefficient by 0.056. In 2025, compared to the original method, the current method reduces the RMSE by 3.616 and increases the correlation coefficient by 0.0207. This method further refines the anomaly handling logic caused by extreme solar activity and observational errors, ensuring data continuity and maintaining the reliability of the correction factor S0 even under extreme solar activity scenarios. The data preprocessing within this method can handle issues such as missing data, redundancy, and format errors, ensuring data compatibility, guaranteeing the continuity of observational data from my country's domestic stations, and eliminating the risk of computational interruption. Furthermore, the output format specification of the autonomous F10.7 index value calculated by the above method supports API interface calls and can be directly connected to the F10.7 numerical prediction system to realize the complete process of data preprocessing, data calculation, and autonomous F10.7 index generation.

[0061] This invention provides an autonomous solar radio F10.7 index calibration device. The autonomous solar radio F10.7 index calibration device provided by this invention will be described below. The autonomous solar radio F10.7 index calibration device described below can be referred to in correspondence with the autonomous solar radio F10.7 index calibration method described above. Figure 4 This is a structural block diagram of the autonomous solar radio F10.7 index calibration device provided by the present invention, as shown below. Figure 4As shown, the device includes: The acquisition module 401 is used to acquire raw data and preprocess the raw data; the raw data includes autonomous observation data and international data. The detection module 402 is used to determine the correction factor S0 based on the original data and to detect outliers in the correction factor S0. Optimization module 403 is used to perform trend and difference dual feedback optimization and physical constraint correction on the correction factor S0; The processing module 404 is used to determine the autonomous F10.7 index based on the modified correction factor S0, and to homogenize the autonomous F10.7 index to obtain the final autonomous F10.7 index.

[0062] In operation, the device first acquires raw data using module 401 and preprocesses it for later use. Then, detection module 402 determines a correction factor S0 based on the raw data and performs outlier detection on S0. Outliers in correction factor S0 are a key factor affecting its stability. By detecting and correcting outliers, unnecessary losses caused by undetected extreme solar activity can be addressed, enabling precise positioning and rebound calibration. To correct systematic biases in correction factor S0, optimization module 403 performs trend and difference dual-feedback optimization and physical constraint correction. Finally, processing module 404 determines the autonomous F10.7 index based on the corrected correction factor S0 and homogenizes it to obtain the final autonomous F10.7 index. In the above process, by combining outlier correction of correction factor S0, trend calibration and residual calibration, physical constraint and meanization processing, the difficulty of deviation accumulation caused by static initial value in traditional methods can be overcome, and the problem of poor accuracy of self-calculated F10.7 exponent in existing related technologies can be solved.

[0063] Figure 5 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 5 As shown, the electronic device may include: a processor 501, a communication interface 502, a memory 503, and a communication bus 504. The processor 501, communication interface 502, and memory 503 communicate with each other via the communication bus 504. The processor 501 can call logical instructions from the memory 503 to execute an autonomous solar radio F10.7 index calibration method, which includes: Acquire raw data and preprocess it; the raw data includes self-observational data and international data. The correction factor S0 is determined based on the original data, and outlier detection is performed on the correction factor S0. The correction factor S0 is optimized using both trend and difference feedback, as well as physical constraint correction. The autonomous F10.7 index is determined based on the modified correction factor S0, and then homogenized to obtain the final autonomous F10.7 index.

[0064] Furthermore, the logical instructions in the aforementioned memory 503 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0065] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the autonomous solar radio F10.7 index calibration method provided by the above methods, the method comprising: Acquire raw data and preprocess it; the raw data includes self-observational data and international data. The correction factor S0 is determined based on the original data, and outlier detection is performed on the correction factor S0. The correction factor S0 is optimized using both trend and difference feedback, as well as physical constraint correction. The autonomous F10.7 index is determined based on the modified correction factor S0, and then homogenized to obtain the final autonomous F10.7 index.

[0066] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the autonomous solar radio F10.7 index calibration method provided by the methods described above, the method comprising: Acquire raw data and preprocess it; the raw data includes self-observational data and international data. The correction factor S0 is determined based on the original data, and outlier detection is performed on the correction factor S0. The correction factor S0 is optimized using both trend and difference feedback, as well as physical constraint correction. The autonomous F10.7 index is determined based on the modified correction factor S0, and then homogenized to obtain the final autonomous F10.7 index.

[0067] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0068] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An autonomous solar radio F10.7 index calibration method, characterized in that, include: Obtain the raw data and preprocess the raw data; The raw data includes autonomous observation data and international data; Based on the original data, a correction factor S0 is determined, and outlier detection is performed on the correction factor S0. The correction factor S0 is optimized using both trend and difference feedback, as well as physical constraint correction. The autonomous F10.7 index is determined based on the modified correction factor S0, and the autonomous F10.7 index is homogenized to obtain the final autonomous F10.7 index.

2. The autonomous solar radio F10.7 index calibration method according to claim 1, characterized in that, Acquire raw data and preprocess the raw data, including: Multiple files that meet specific time conditions are selected from the autonomous observation data as the solar radiation data and cold air radiation data for the day, and the mean is calculated and zero value is processed. The international F10.7 index is obtained, and the international F10.7 index is processed to unify its format so that the international F10.7 index is consistent with the format of the autonomous observation data.

3. The autonomous solar radio F10.7 index calibration method according to claim 2, characterized in that, The process includes mean calculation and zero detection, including: The average values ​​of the daily solar radiation data and the daily cold air radiation data are calculated to obtain the average daily solar radiation data and the average daily cold air radiation data. If the number of files selected within a time period does not reach the preset standard, the average value of the corresponding data will be assigned to zero. Detect all zero values; if a zero value appears on the first day, assign zero to the mean of the following day. If the zero value appears on the last day, then the mean of the previous day is assigned the zero value.

4. The autonomous solar radio F10.7 index calibration method according to claim 3, characterized in that, Determining the correction factor S0 based on the original data includes: Calculate the ratio of the average daily cold air radiation data to the average daily solar radiation data; The correction factor S0 is determined by multiplying the ratio by the international F10.7 index.

5. The autonomous solar radio F10.7 index calibration method according to claim 2, characterized in that, Outlier detection is performed on the correction factor S0, including: Based on the solar flux of the international F10.7 index, determine whether the date corresponding to the correction factor S0 is a date of extreme solar activity; On days of extreme solar activity, it is determined whether the value of the correction factor S0 exceeds the standard threshold. If so, the correction factor S0 is identified as an outlier and anomaly processing is performed. If the correction factor S0 does not exceed the standard threshold, then based on 3 The principle is to determine whether the correction factor S0 meets the monitoring data error. If it does, the correction factor S0 is handled as an anomaly.

6. The autonomous solar radio F10.7 index calibration method according to claim 5, characterized in that, If the correction factor S0 exceeds the standard threshold, then mean smoothing is applied to the correction factor S0. If the correction factor S0 satisfies the monitoring data error, then the median of the correction factor S0 over N days is used to replace the current correction factor S0.

7. The autonomous solar radio F10.7 index calibration method according to claim 2, characterized in that, The correction factor S0 is optimized using a dual feedback mechanism of trend and difference, including: Calculate the rolling average of the international F10.7 index and the rolling average of the autonomous F10.7 index over the past N days, and determine the trend ratio; The correction factor S0 after outlier processing is trend-adjusted based on the trend ratio. Calculate the difference between the international F10.7 index and the domestic F10.7 index over the past M days, and then calculate the average of the differences. The correction factor S0 is calibrated based on the mean of the differences.

8. The autonomous solar radio F10.7 index calibration method according to claim 1, characterized in that, Physical constraint correction is performed on the correction factor S0, including adjusting the reasonable range of the correction factor S0 to [25, 40].

9. The autonomous solar radio F10.7 index calibration method according to claim 2, characterized in that, The autonomous F10.7 index is determined based on the modified correction factor S0, and the autonomous F10.7 index is homogenized to obtain the final autonomous F10.7 index, including: Calculate the ratio of the average daily solar radiation data to the average daily cold air radiation data, and determine the autonomous F10.7 index by combining the correction factor S0; Calculate the root mean square error and correlation coefficient between the autonomous F10.7 index and the international F10.7 index; The autonomous F10.7 index under non-solar extreme activity conditions was averaged. The root mean square error and correlation coefficient of the homogenized autonomous F10.7 index and the international F10.7 index are calculated and compared with the initial root mean square error and correlation coefficient. The autonomous F10.7 index with the smallest root mean square error and the highest correlation coefficient is retained as the final autonomous F10.7 index.

10. An autonomous solar radio F10.7 index calibration device, characterized in that, include: An acquisition module is used to acquire raw data and preprocess the raw data; The raw data includes autonomous observation data and international data; The detection module is used to determine the correction factor S0 based on the original data and to perform outlier detection on the correction factor S0. The optimization module is used to perform trend and difference dual feedback optimization and physical constraint correction on the correction factor S0; The processing module is used to determine the autonomous F10.7 index based on the modified correction factor S0, and to homogenize the autonomous F10.7 index to obtain the final autonomous F10.7 index.

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