A method, device and storage medium for identifying sudden ionospheric disturbance based on shortwave timing signal

Abstract

The invention discloses a method for identifying sudden ionospheric disturbance based on shortwave timing signals, comprising the following steps: step 1, collecting high-frequency Doppler and signal level observation data of various ionospheric observation stations in China, and preprocessing the data; step 2, analyzing the Doppler frequency shift and the attenuation change law of the received signal during the flare, and studying the change law of the sudden ionospheric disturbance effect caused by the solar flare; step 3, according to the Doppler frequency shift and the attenuation change law of the received signal, obtaining a single-station ionospheric disturbance event identification method; step 4, comprehensively analyzing the multi-station data, establishing a prediction model for sudden ionospheric disturbance events in China, and using the prediction model to identify whether sudden ionospheric disturbance occurs. The method disclosed by the invention can use the high-frequency Doppler and signal level observation data in China, analyze the Doppler frequency shift and the attenuation change law of the received signal during the flare, study the ionospheric disturbance feature extraction technology based on the shortwave receiving field strength and Doppler frequency shift, and obtain a single-station ionospheric disturbance event identification method.

Description

Technical Field

[0001] The invention belongs to the research field of ionospheric environment monitoring, and particularly relates to a method, a device and a storage medium for identifying sudden ionospheric disturbance based on shortwave timing signals in the field. Background Art

[0002] When high-frequency radio waves propagate in the ionosphere, high-frequency Doppler frequency shifts will be generated due to changes in the electron concentration of the ionosphere or changes in the condition of the reflecting surface. Analysis of high-frequency Doppler frequency shifts can obtain information such as ionospheric disturbances. High-frequency Doppler detection can be used to monitor the radio wave propagation environment of the ionosphere, and then analyze and study various ionospheric disturbances caused by the neutral atmosphere and solar activity, as well as the propagation characteristics of atmospheric acoustic gravity waves. High-frequency Doppler observations have the characteristics of high detection sensitivity, good event continuity, and low system costs. More importantly, the use of passive, multi-station co-source signal reception and monitoring is an effective means of ionospheric environment observation, especially ionospheric disturbance detection. The ionospheric high-frequency Doppler observation data not only reflects the changes in the Doppler frequency shift caused by ionospheric disturbances over time, but also reflects the changes in the signal field strength over time, and can monitor the audio information transmitted by the timing center.

[0003] The ionospheric Doppler effect can be attributed to two reasons: one is the change of the wave propagation path itself, and the other is the change of the wave refractive index caused by the change of the ionosphere on the propagation path. Generally speaking, these two factors are inseparable, and their effects are uniformly manifested as the influence of phase path changes.

[0004] Usually, the change of Doppler shift of high-frequency radio waves is caused by many reasons. In addition to the daily change of the ionosphere, solar flares, solar eclipses, magnetic storms, earthquakes, typhoons, nuclear explosions, and atmospheric acoustic-gravity waves stimulated by catastrophic weather can all cause abnormal changes in Doppler shift.

[0005] There are many reasons for the sudden change of Doppler shift. In addition to sunrise and sunset, the most important ones are solar flares and magnetic storms. Among them, the sudden change of Doppler shift caused by solar flare is the most obvious. When a solar flare erupts, the sudden increase of extreme ultraviolet rays and X-rays reaches the earth in about 8 minutes, directly causing a rapid increase in the electron density of the ionosphere on the sunward side, causing a relatively large change in the electron density at the height of the ionosphere, mainly occurring in the D layer of the ionosphere, causing sudden ionospheric disturbance. The impact of solar flares on the ionosphere can be better observed using high-frequency Doppler technology. For example, within a few minutes after the flare erupts, the frequency shift shows a positive steep rise, and the ionospheric absorption loss increases significantly. Usually, the increase in ionospheric electron concentration caused by small-scale solar flares mainly comes from the increase in electron concentration in the lower ionosphere (near the D and E regions); in this case, the higher the detection frequency, the smaller the Doppler shift. Summary of the invention

[0006] The technical problem to be solved by the present invention is to use the ionospheric disturbance observation data in China to statistically analyze the Doppler frequency shift change characteristics and the received signal amplitude fading characteristics caused by solar flares, and to provide a method, device and storage medium for identifying sudden ionospheric disturbances based on shortwave timing signals.

[0007] The present invention adopts the following technical solution:

[0008] A method for identifying sudden ionospheric disturbance based on shortwave timing signals, the improvement of which is that it comprises the following steps:

[0009] Step 1: Collect high-frequency Doppler and signal level observation data from various ionospheric observation stations in China, preprocess the data, remove invalid data, and obtain valid sample data:

[0010] Use ionospheric disturbance detection technology to obtain Doppler frequency shift and received signal data of each ionospheric observation station; establish a method to determine the validity of observation data; pre-process historical data and eliminate invalid data;

[0011] Step 2: Analyze the changing laws of Doppler frequency shift and received signal attenuation during the flare period, and study the changing laws of the sudden disturbance effect of the ionosphere caused by solar flares;

[0012] Step 3, according to the Doppler frequency shift and the received signal attenuation change law, study the ionospheric sudden disturbance feature extraction technology based on shortwave receiving field strength and Doppler frequency shift, and obtain a single-station ionospheric sudden disturbance event identification method;

[0013] Step 4: Comprehensively analyze the data from multiple stations, establish a prediction model for sudden ionospheric disturbance events in China, and use the prediction model to identify whether sudden ionospheric disturbance occurs.

[0014] Furthermore, the method for judging the validity of the observation data in step 1 includes a level data method and a spectrum data method;

[0015] The level data method is as follows: the 5MHz frequency signal level is high at night and low during the day; the 10MHz frequency signal level is high during the day and low at night; the 15MHz frequency signal level is high during the day;

[0016] The spectrum data method is as follows: in the absence of ionospheric disturbances, if the spectrum data center position of 5MHz, 10MHz, and 15MHz spectrum data is found to be near 0Hz for more than 4 hours during the day, the observed data is normal; otherwise, the observed data is considered to be of poor quality.

[0017] A device for identifying sudden ionospheric disturbances based on shortwave timing signals, the improvement of which is that it comprises: a processor; a memory in which executable instructions of the processor are stored; and the processor is configured to execute the steps of the above method by executing the executable instructions.

[0018] A computer-readable storage medium is used to store a program, wherein the improvement lies in that the steps of the above method are implemented when the program is executed.

[0019] The beneficial effects of the present invention are:

[0020] The method disclosed in the present invention can use the high-frequency Doppler and signal level observation data in China to analyze the Doppler frequency shift and the change law of the received signal attenuation during the flare, study the ionospheric sudden disturbance feature extraction technology based on the shortwave receiving field strength and Doppler frequency shift, and obtain the single-station ionospheric sudden disturbance event identification method. Comprehensively analyze the multi-station data, establish the ionospheric sudden disturbance event prediction model in China, and use the prediction model to identify whether the ionospheric sudden disturbance occurs, which provides good technical support for the design and operation and maintenance of the radio system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic flow diagram of the method of the present invention;

[0022] Figure 2 This is a schematic diagram of the monitoring work of ionospheric disturbance characteristics;

[0023] Figure 3 This is the interface diagram of the Doppler frequency shift monitoring window;

[0024] Figure 4 This is the interface diagram of the signal level monitoring window;

[0025] Figure 5 It is the Doppler shift anomaly graph;

[0026] Figure 6 This is a solar X-ray flux map observed by the GOES satellite;

[0027] Figure 7 This is the result of Doppler shift observations at 10MHz, 15MHz, and 5MHz during the flare;

[0028] Figure 8 This is the change diagram of the signal level of the 5MHz channel of the Xinxiang-Xi'an link during the flare period;

[0029] Fig. 9 This is the change of signal level of 10MHz channel in Suzhou-Xi'an link during the flare period;

[0030] Fig.10This is the change of signal level of 15MHz channel of Xinxiang-Xi'an link during the flare period;

[0031] Fig.11 This is the Xi'an-Qingdao receiving field strength and high-frequency Doppler shift observation results;

[0032] Fig.12 This is the observation result of Lhasa Station during the solar flare;

[0033] Fig.13 This is the observation result during the solar flare at Xinxiang Station;

[0034] Fig.14 This is the observation result of Urumqi Station during the solar flare;

[0035] Fig.15 This is the observation result of Lanzhou Station during the solar flare;

[0036] Fig.16 This is the observation result of Suzhou Station during the solar flare;

[0037] Fig.17 These are the observation results during the solar flare at Changchun Station. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0039] Example 1: This example discloses a method for identifying sudden ionospheric disturbances based on shortwave timing signals. It collects high-frequency Doppler and signal level observation data from Manchuria, Changchun, Kunming, Xinxiang, Qingdao, Lanzhou, Urumqi, Chongqing, Guangzhou, Haikou, Suzhou and Lhasa stations, statistically analyzes the Doppler frequency shift caused by solar flares and the fading characteristics of the received signal amplitude, analyzes the propagation and evolution of ionospheric disturbances during sudden ionospheric disturbances, and establishes a method for identifying sudden ionospheric disturbances in China. Figure 1 As shown, the specific steps include:

[0040] Step 1: Collect high-frequency Doppler and signal level observation data from various ionospheric observation stations in China, preprocess the data, remove invalid data, and obtain valid sample data:

[0041] like Figure 2 As shown, the Doppler frequency shift and received signal data of each ionospheric observation station are obtained by using ionospheric disturbance detection technology; Figure 3 This is the interface diagram of the Doppler frequency shift monitoring window; Figure 4It is the interface diagram of the signal level monitoring window; establish the validity judgment method of the observation data; pre-process the historical data, eliminate invalid data, and ensure that the Doppler frequency shift and received signal data sets are complete and valid; Figure 5 This is a Doppler frequency shift anomaly diagram, where (a) reflects the periodic oscillation of the Doppler frequency shift of the 5MHz, 10MHz, and 15MHz signals. It is judged that the equipment hardware is faulty and the receiver crystal oscillation self-excited oscillation causes Doppler frequency shift anomaly. The observed data is marked as invalid data and cannot be used in data analysis. Invalid data is eliminated. (b) reflects the noise spectrum obtained by Fourier transform of the noise level.

[0042] The above data extraction is completed by relying on the National Defense Science and Technology Industry Radio Wave Environment Observation Station Network, including 12 ionospheric disturbance observation stations in Manchuria, Changchun, Kunming, Xinxiang, Qingdao, Lanzhou, Urumqi, Chongqing, Guangzhou, Haikou, Suzhou and Lhasa. High-frequency Doppler observation has the characteristics of high detection sensitivity, good event continuity and low system cost. More importantly, it adopts passive, multi-station homologous signal reception and monitoring, which is an effective means of ionospheric environment observation, especially ionospheric disturbance detection.

[0043] Normally, the Doppler shift fluctuates around the 0-frequency line; at sunrise (6:00-8:00), the ionospheric electron concentration changes dramatically, which usually causes changes in the Doppler shift, namely the sunrise effect; during flares, the Doppler shift of multiple stations rises sharply, accompanied by a sudden drop in signal level. Therefore, the methods for judging the validity of observation data include the level data method and the spectrum data method;

[0044] The level data method is as follows: Under normal circumstances, the 5MHz frequency signal level is high at night and low during the day; the 10MHz frequency signal level is high during the day and low at night; the 15MHz frequency signal level is high during the day; the signal level is meaningful only during the 9:00-17:00 time period.

[0045] Table 1 Timing Center Work Schedule

[0046] frequency Working hours Remark 5MHz All day Beijing Time 10MHz All day Beijing Time 15MHz 9:00-17:00 Beijing Time

[0047] Table 1 shows the timetable of the timing center. The 5MHz and 10MHz frequencies work all day, but the 15MHz frequency works from 09:00 to 17:00. Therefore, the data of the 5MHz and 10MHz frequencies are meaningful all day, while the data of the 15MHz frequency is meaningful only from 09:00 to 17:00.

[0048] The spectrum data method is as follows: the frequency deviation data range is -3Hz to +3Hz. In the absence of ionospheric disturbance, if the spectrum data center position of 5MHz, 10MHz, and 15MHz spectrum data is found to be near 0Hz for a long time (more than 4 hours) during the day, the observation data is normal; otherwise, it is considered that the observation equipment may be faulty and the observation data quality is poor.

[0049] Step 2: Analyze the changing laws of Doppler frequency shift and received signal attenuation during the flare period, and study the changing laws of the sudden disturbance effect of the ionosphere caused by solar flares;

[0050] A solar flare is a violent explosion that occurs in a local area of ​​the sun's atmosphere. Figure 6 This is a map of solar X-ray flux observed by the GOES satellite.

[0051] On June 25, 2015, from 16:02 to 17:05, the sun erupted with a M7.9 flare. Figure 7 It can be seen that during the flare period, stations in Qingdao, Chongqing, Xinxiang and other places observed obvious Doppler shifts on the 10MHz and 15MHz channels, that is, the Doppler shift caused by the solar flare was the most obvious. However, Chongqing station also observed obvious Doppler shifts on the 5MHz channel, and Suzhou station observed a noise spectrum, which may be related to factors such as the weak 5MHz signal during the day and the large ionospheric absorption loss.

[0052] Figure 8-10 The daily variation of the signal levels of 5MHz, 10MHz and 15MHz received by each station is given. After the flare began, the signal levels of each link at each frequency attenuated to varying degrees.

[0053] Step 3, according to the Doppler frequency shift and the received signal attenuation change law, study the ionospheric sudden disturbance feature extraction technology based on shortwave receiving field strength and Doppler frequency shift, and obtain a single-station ionospheric sudden disturbance event identification method;

[0054] like Fig.11 As shown, the field strength value adopts the field strength value after five-point smoothing. When a solar flare breaks out, the electron concentration suddenly increases, causing the Doppler frequency shift to suddenly increase to 1.514Hz, and then the absorption of the D area is enhanced, causing the radio wave signal to drop sharply, showing a typical Doppler effect caused by flares. Therefore, the sudden and obvious drop in signal level and the simultaneous occurrence of Doppler positive frequency shift can be used to infer the solar flare.

[0055] Step 4: Comprehensively analyze the data from multiple stations, establish a prediction model for sudden ionospheric disturbance events in China, and use the prediction model to identify whether sudden ionospheric disturbance occurs.

[0056] On March 29, 2023, at 10:18 (BJT), an X1.1-class flare broke out and ended at 10:40, lasting for 22 minutes, causing ionospheric disturbances in the Chinese region. The Doppler shift map is shown in Fig.12 and Fig.13 The upper, middle and lower curves in the figure represent the observation results of 5MHz, 10MHz and 15MHz respectively. 10MHz and 15MHz show the typical Doppler effect caused by flares, and 5MHz shows a noise spectrum. Among them, the great circle distances from Kunming to Lhasa and Xinxiang are about 1,800 kilometers and 550 kilometers respectively. Considering the universality, the identification method of sudden ionospheric disturbance events does not consider the Doppler frequency shift and signal level data of the 5MHz frequency point.

[0057] Urumqi Station is very far from Xi'an. Fig.14 As shown, when the operating frequencies are 5 MHz and 10 MHz, it usually displays a noise spectrum during the day, and the 15 MHz signal is weak, so the observation data of the Urumqi station are not considered.

[0058] In view of the above observation results, and considering the regional changes and ionospheric disturbance characteristics in China, the high-frequency Doppler observation data of 11 stations including Manzhouli, Changchun, Kunming, Xinxiang, Qingdao, Lanzhou, Chongqing, Guangzhou, Haikou, Suzhou and Lhasa are used to identify whether the sudden ionospheric disturbance occurs. The detection period is from 9:00 to 17:00 (BJT). The specific identification method is as follows:

[0059] If the Doppler shift of one of the 10MHz or 15MHz signals of a single station is greater than 1.5Hz and the other Doppler shift is greater than 1Hz, the received signal level drops sharply, indicating that sudden ionospheric disturbance has occurred.

[0060] When the Doppler frequency shift of 10MHz or 15MHz signals of two or more stations is greater than 1Hz, the received signal level drops sharply, which indicates that sudden ionospheric disturbance has occurred.

[0061] For example, Figure 15-17 As shown in the figure, after 10 o'clock, the Doppler frequency shift of Lanzhou, Suzhou and Changchun stations rose sharply and was greater than 1Hz, and the receiving level dropped sharply. According to the identification method, it is believed that a sudden ionospheric disturbance has occurred. According to data released by the National Oceanic and Atmospheric Administration (NOAA), around 10:33 on March 29, 2023, the sun erupted an X1.2-level flare, and the identification result is consistent with the actual situation.

[0062] This embodiment also discloses a device for identifying sudden ionospheric disturbances based on shortwave timing signals, comprising: a processor; a memory storing executable instructions of the processor; and the processor is configured to execute the steps of the above method by executing the executable instructions.

[0063] This embodiment also discloses a computer-readable storage medium for storing a program, wherein the improvement lies in that the program implements the steps of the above method when executed.

Claims

1. A method for identifying sudden ionospheric disturbance based on shortwave timing signals, characterized in that: The steps include: Step 1: Collect high-frequency Doppler and signal level observation data from various ionospheric observation stations in China, preprocess the data, remove invalid data, and obtain valid sample data: Use ionospheric disturbance detection technology to obtain Doppler frequency shift and received signal data of each ionospheric observation station; establish a method to determine the validity of observation data; pre-process historical data and eliminate invalid data; Step 2: Analyze the changing laws of Doppler frequency shift and received signal attenuation during the flare period, and study the changing laws of the sudden disturbance effect of the ionosphere caused by solar flares; Step 3, according to the Doppler frequency shift and the received signal attenuation change law, study the ionospheric sudden disturbance feature extraction technology based on shortwave receiving field strength and Doppler frequency shift, and obtain a single-station ionospheric sudden disturbance event identification method; Step 4: Comprehensively analyze the data from multiple stations, establish a prediction model for sudden ionospheric disturbance events in China, and use the prediction model to identify whether sudden ionospheric disturbance occurs.

2. The method for identifying sudden ionospheric disturbance based on shortwave timing signals according to claim 1, characterized in that: The methods for judging the validity of observation data in step 1 include the level data method and the spectrum data method; The level data method is as follows: the 5MHz frequency signal level is high at night and low during the day; The signal level of the 10MHz frequency point is high during the day and low at night; the signal level of the 15MHz frequency point is high during the day; The spectrum data method is as follows: in the absence of ionospheric disturbance, if the spectrum data center position of 5MHz, 10MHz, and 15MHz spectrum data is found to be near 0Hz for more than 4 hours during the day, the observed data is normal; Otherwise, the observed data are considered to be of poor quality.

3. An ionospheric sudden disturbance identification device based on shortwave timing signals, characterized in that: include: A processor; a memory in which executable instructions of the processor are stored; the processor is configured to perform the steps of the method of claim 1 by executing the executable instructions.

4. A computer-readable storage medium for storing a program, characterized in that: When the program is executed, the steps of the method according to claim 1 are implemented.

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