CN111323807A - Method for predicting change trend of Es in summer area - Google Patents
Method for predicting change trend of Es in summer area Download PDFInfo
- Publication number
- CN111323807A CN111323807A CN201911321227.5A CN201911321227A CN111323807A CN 111323807 A CN111323807 A CN 111323807A CN 201911321227 A CN201911321227 A CN 201911321227A CN 111323807 A CN111323807 A CN 111323807A
- Authority
- CN
- China
- Prior art keywords
- foes
- reflection point
- point
- value
- calculating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/29—Measurement performed on radiation beams, e.g. position or section of the beam; Measurement of spatial distribution of radiation
- G01T1/2914—Measurement of spatial distribution of radiation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/29—Measurement performed on radiation beams, e.g. position or section of the beam; Measurement of spatial distribution of radiation
- G01T1/2914—Measurement of spatial distribution of radiation
- G01T1/2992—Radioisotope data or image processing not related to a particular imaging system; Off-line processing of pictures, e.g. rescanners
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- High Energy & Nuclear Physics (AREA)
- Molecular Biology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention discloses a method for predicting the change trend of Es in a summer area, which comprises the following steps: the method comprises the steps of 1, calculating great circle distance and reflection point positions of an HF link according to position information of a transmitting and receiving point, 2, utilizing several sites foEs to carry out kriging reconstruction, drawing regional distribution conditions of the foEs, 3, analyzing the change characteristics of the foEs at intervals of 5 minutes and 15 minutes by depending on a national defense science and technology electric wave environment observation station network, researching the statistical characteristics of the change of the foEs along with time, analyzing whether a reflection point foEs layer exists or not, analyzing the change trend of the foEs, and further predicting the change trend of the foEs at the next moment of the reflection point.
Description
Technical Field
The invention belongs to the field of ionosphere environment prediction research, and particularly relates to a method for predicting change trend of Es in a summer area in the field.
Background
The sporadic E layer (Es layer) is a burst uneven structure of the E layer and is named because the occurrence time is not fixed. Generally, the Es layer in the equatorial region exists frequently in the daytime and does not have great seasonal variation; the values of the foEs in the mid-latitude areas are relatively low, and obvious seasonal changes exist. Particularly, the southeast area of China is an Es layer high-incidence area, Es often appears in summer of the years with lower solar black counts, and the values of FoEs are very high. The radio signal reflected by the Es layer is usually strong, but if the reflective layer is semi-transparent, it may cause trouble in communication due to signal fading.
ITU-R P.534-5 discloses a calculation method for predicting Es field intensity by using statistics of ionized layer attenuation values corresponding to foEs values with given incidence, and the doctor's paper of geology and geophysical research institute of Chinese academy of sciences analyzes that a wind field, planet waves, geomagnetic activity, weather and the like possibly play an important role in the Es layer, and provides a new method for researching the long-term change rule of the ionized layer Es layer by using an artificial neural network. Using 34 years of ionospheric altimeter observations, 16 foEs year-by-year averages from 1967 to 1982 were used as samples for training, and 8 samples from 1983 to 1990 were used as prognostic tests. The output value obtained by network training has high correlation with the actual expected value, the predicted value is very close to the observed value, the defect is that the real-time change of Es cannot be predicted, and no report related to short-term prediction research work of Es is published internationally.
Disclosure of Invention
The invention aims to provide a method for predicting the change trend of Es in a summer area.
The invention adopts the following technical scheme:
the improvement of a method for predicting the change trend of Es in a summer area is that the method comprises the following steps:
step 1, calculating the great circle distance and the position of a reflection point of an HF link according to the position information of the transmission and reception point, constructing a one-transmission-multiple-reception vertical measurement network near the reflection point, and acquiring the foEs values of ionosphere vertical measurements of a plurality of observation stations, wherein the method specifically comprises the following steps:
step 11: calculating the great circle distance of the oblique communication link according to the position information of the transmitting and receiving points, and inverting the coordinates of the reflection point of the high-frequency link;
the specific method for calculating the great circle distance of the communication link comprises the following steps:
if the ground transmitting point of the communication link is a and the receiving point is B, the great circle distance D between the two points A, B is:
D＝111.18Φ(°) (1)
wherein phi is a great circle geocentric angle between A, B points;
let the geographical latitude and longitude of points A and B be lA、aAAnd lB、aBIf north latitude is positive, south latitude is negative, east longitude is positive, and west longitude is negative, Φ satisfies:
cosΦ＝sin lAsin lB+cos lAcos lBcos(aA-aB)；
the specific method for calculating the coordinates of the reflection points of the communication link comprises the following steps:
for a communication link with a great circle distance less than 3000km, taking the middle point of the path as a reflection point of a link propagation path, and then taking the latitude and longitude l of the reflection pointn、anAnd geomagnetic latitude gnRespectively, as follows:
ln＝arcsin[sin lAcosΦn+cos lAsinΦncosΦA](3)
gn＝90°-arccos[sin 78.5° sinln+cos 78.5° cos lncos(an-69.0°)](5)
wherein phinIs the great circle geocentric angle between the A terminal and the reflection point, Delta a>0 is given a negative sign, Δ a<0 takes the positive sign; phiAIs the azimuth angle from the A terminal to the B terminal, phiBThe azimuth angle from the B end to the A end is defined as positive north being 0 degree and clockwise direction, i.e. positive east, phiAAnd phiBRespectively satisfy:
step 12: constructing a one-transmitting and multi-receiving vertical measurement network, acquiring an ionosphere vertical measurement frequency height map of each ionosphere observation station by utilizing an ionosphere vertical detection technology, and reading the foEs value of the vertical ionosphere;
step 21: performing kriging reconstruction by using several sites of the foEs, and drawing the regional distribution condition of the foEs;
step 22: calculating an ionized layer foEs value at the reflection point of the high-frequency link according to the position information of the HF link reflection point;
the specific method for reconstructing the data of the foEs near the reflection point of the specific short-wave communication link and calculating the value of the foEs at the reflection point comprises the following steps:
setting Z (x, y) as the characteristic parameter of the ionized layer, and obtaining the values Z (x) of the characteristic parameter of the ionized layer measured by n observation stations in the known areai,yi) 1,2,3, …, n, then any point (x) in the region0,y0) Kriging estimate Z ofp(x0,y0) Can be expressed as:
wherein WiIs a weight coefficient; wiSatisfies the following conditions:
wherein d isijIs the ionospheric distance between two points of the ionosphere,
wherein Lon (i), Lon (j) and Lat (i), Lat (j) respectively represent the geographic longitude and latitude of the receiving and transmitting stations, and SK and SF are respectively longitude or latitude related distance scale factors;
taking a reflection station as a center, taking the variation range of an area as +/-0.5 degrees and the longitude and latitude stepping value as 0.1 degrees, calculating the foEs value of each point in the network, carrying out foEs reconstruction on the characteristic point value of the area by utilizing a kriging interpolation method, drawing a foEs area distribution diagram at the moment, and calculating the foEs value at the reflection point;
step 31: by depending on a national defense science and technology industrial electric wave environment observation station network, calculating great circle distances from reflection points to different observation stations by using a great circle distance calculation formula (1), selecting ionized layer environment data of the nearest observation station, analyzing an ionized layer environment change rule, and taking the ionized layer environment change rule as a change characteristic of ionized layer foEs parameters near the reflection points;
step 32: analyzing the change characteristics of the foEs at intervals of 5 minutes and 15 minutes, and researching the statistical characteristics of the foEs along with the change of time;
analyzing the variation characteristics of the foEs at the interval of 5 minutes and 15 minutes, namely statistically analyzing the summer foEs statistical variation characteristics and the foEs variation rule in the period of three days;
and 4, step 4: analyzing whether a reflection point foEs layer exists or not according to the statistical characteristics of the foEs and the foEs regional distribution diagram, analyzing the variation trend of the foEs, and further predicting the variation trend of the foEs at the next moment of the reflection point, wherein the method specifically comprises the following steps:
step 41: if the foEs value at the reflection point is not more than 2.5MHz, the Es layer does not exist; if the foEs value is larger than 2.5MHz, the Es layer exists;
step 42: when an Es layer exists, calculating the values of the foEs in the small-area grid, and drawing a distribution diagram of the foEs area in the first hours; analyzing the change characteristic of the areas foEs near the reflection point according to the statistical characteristic of the foEs and the foEs area distribution map;
step 43: and analyzing the moving direction and the variation trend of the fos according to the variation characteristic of the fos and the reconstruction or measured value of the fos and combining a plurality of fos regional distribution graphs, and predicting the variation trend of the fos at the next moment of the reflecting point.
The invention has the beneficial effects that:
the invention provides a method for predicting the change trend of Es in a summer area for a user, which can comprehensively utilize small-area multi-station ionosphere verticality data, calculate the foEs value at a reflection point, judge whether the Es layer exists or not, further combine a foEs area distribution diagram to predict the change trend of the foEs value at the next time, and provide good technical support for the design and operation maintenance of a radio system.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic diagram of a one-shot multiple-shot vertical survey networking probe;
FIG. 3 is a ionospheric elevation diagram;
FIG. 4 is a distribution diagram of a domestic conventional observatory;
FIG. 5a is a graph of foEs observations at 5 min/point at 6, 13, 2015;
FIG. 5b is a graph of foEs observations at 15 min/point at 6, 13, 2015;
FIG. 6a is a graph of statistical variation characteristics of Chongqing stations fo Es of 3MHz or more in summer;
FIG. 6b is a graph of statistical variation of the station foEs of the Pacific lake, which is greater than or equal to 3MHz in summer;
FIG. 6c is a graph of statistical variation characteristics of the Chongqing stations fo Es of 5MHz or more in summer;
FIG. 6d is a graph showing the statistical variation of the station foEs of the Pacific lake, which is greater than or equal to 5MHz in summer;
FIG. 6e is a graph of statistical variation characteristics of the Chongqing stations foEs of 7MHz or more in summer;
FIG. 6f is a graph of statistical variation of the station foEs of the Pacific lake, which is greater than or equal to 7MHz in summer;
FIG. 7 is a graph of the observations of foEs at 6, 15/2015 at 4 different sites;
fig. 8a is a graph of data at 6 month, 17 day 9 in 2015: 00. reconstructing a result graph of the region when the foEs is more than or equal to 4MHz and less than or equal to 6 MHz;
fig. 8b is a graph of data at 6 month, 17 day 9 in 2015: 15. reconstructing a result graph of the region when the foEs is more than or equal to 4MHz and less than or equal to 6 MHz;
fig. 8c is a graph of 9 at 6 months and 17 days 2015: 30. reconstructing a result graph of the region when the foEs is more than or equal to 4MHz and less than or equal to 6 MHz;
fig. 8d is a graph of 9 at 6 months and 17 days 2015: 45. reconstructing a result graph of the region when the foEs is more than or equal to 4MHz and less than or equal to 6 MHz;
fig. 9a is a graph of 17 days 6 month 2015: 00. reconstructing a result graph of the region when the foEs is more than or equal to 7MHz and less than or equal to 10 MHz;
fig. 9b is 17 days 6 month 2015: 15. reconstructing a result graph of the region when the foEs is more than or equal to 7MHz and less than or equal to 10 MHz;
fig. 9c is 17 days 6 month 2015: 30. reconstructing a result graph of the region when the foEs is more than or equal to 7MHz and less than or equal to 10 MHz;
fig. 9d is 17 d at 6 months and 17 days 2015: 45. reconstructing a result graph of the region when the foEs is more than or equal to 7MHz and less than or equal to 10 MHz;
fig. 10a is a graph of 18 at 6 months and 17 days 2015: 00. a regional reconstruction result graph when the fos is larger than 10 MHz;
fig. 10b is a graph of 18 at 6 month 17 th 2015: 15. a regional reconstruction result graph when the fos is larger than 10 MHz;
fig. 10c is a graph of 18 at 6 months and 17 days 2015: 30. a regional reconstruction result graph when the fos is larger than 10 MHz;
fig. 10d is a graph of 18 at 6 month 17 th 2015: 45. a regional reconstruction result graph when the fos is larger than 10 MHz;
fig. 11a is a graph taken at 6 month and 17 day 1 in 2015: 45. reconstructing a result graph of the region when the fos is changed violently;
fig. 11b is a graph of 2 at 6 months and 17 days 2015: 00. reconstructing a result graph of the region when the fos is changed violently;
fig. 11c is a graph of 2 at 6 months and 17 days 2015: 15. reconstructing a result graph of the region when the fos is changed violently;
fig. 11d is a graph of 2 at 6 months and 17 days 2015: 30. reconstructing a result graph of the region when the fos is changed violently;
fig. 11e is a graph of 2 at 6 month 17 d 2015: 45. reconstructing a result graph of the region when the fos is changed violently;
fig. 11f is a graph taken at 6 month, 17 day 3 in 2015: 00. reconstructing a result graph of the region when the fos is changed violently;
fig. 11g is a graph taken at 6 months and 17 days 3 in 2015: 15. reconstructing a result graph of the region when the fos is changed violently;
fig. 11h is a graph taken at 6 months and 17 days 3 in 2015: 30. reconstructing a result graph of the region when the fos is changed violently;
fig. 11i is a graph taken at 6 month, 17 day 3 in 2015: 45. reconstructing a result graph of the region when the fos is changed violently;
fig. 11j is a graph taken at 6 month, 17 day, 4 in 2015: 00. reconstructing a result graph of the region when the fos is changed violently;
fig. 12 is a graph showing the results of regional reconstruction when foEs was small on day 27/5/2015.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The principle of the prediction method disclosed by the embodiment is that according to the characteristic of strong correlation of spatial change of Es in summer, a one-transmission multi-reception vertical measurement networking detection network is used in a certain small area, space-time scale information of Es change is constructed based on ionosphere real-time environment information of 4 stations, instantaneous values foEs of parameters of the 4 stations ionosphere Es are obtained, regional distribution characteristics of Es are reflected through regional reconstruction, and the change trend of the regional foEs is further predicted.
Embodiment 1, as shown in fig. 1, this embodiment discloses a method for predicting a change trend of Es in a summer area, which specifically includes the following steps:
step 1: and calculating the great circle distance and the position of a reflection point of the link according to the longitude and latitude of the HF link, and acquiring a plurality of foEs values near the reflection point. The method comprises the following steps:
step 11: calculating the great circle distance of the oblique communication link according to the position information of the transmitting and receiving points, and inverting the coordinates of the reflection point of the high-frequency link;
step 12: constructing a one-transmitting and multi-receiving vertical measurement network, acquiring an ionosphere vertical measurement frequency height map of each ionosphere observation station by utilizing an ionosphere vertical detection technology, and reading the foEs value of the vertical ionosphere;
the specific method for calculating the great circle distance of the communication link comprises the following steps:
if the ground transmitting point of the communication link is a and the receiving point is B, the great circle distance D between the two points A, B is:
D＝111.18Φ(°) (1)
wherein phi is a great circle geocentric angle between A, B points;
let the geographical latitude and longitude of points A and B be lA、aAAnd lB、aBIf north latitude is positive, south latitude is negative, east longitude is positive, and west longitude is negative, Φ satisfies:
cosΦ＝sin lAsin lB+cos lAcos lBcos(aA-aB) (2)
the specific method for calculating the coordinates of the reflection points of the communication link comprises the following steps:
for a communication link with a great circle distance less than 3000km, taking the middle point of the path as a reflection point of a link propagation path, and then taking the latitude and longitude l of the reflection pointn、anAnd geomagnetic latitude gnRespectively, as follows:
ln＝arcsin[sin lAcosΦn+cos lAsinΦncosΦA](3)
gn＝90°-arccos[sin 78.5°sin ln+cos 78.5°cos lncos(an-69.0°)](5)
wherein phinBetween the A terminal and the reflection pointGreat circle of central earth angle, Δ a>0 is given a negative sign, Δ a<0 takes the positive sign; phiAIs the azimuth angle from the A terminal to the B terminal, phiBThe azimuth angle from the B terminal to the A terminal is defined as positive north being 0 DEG and positive clockwise (i.e. east), then phiAAnd phiBRespectively satisfy:
according to the Smith method, the calculation formula of the radio wave radiation elevation angle is as follows:
wherein D is the great circle distance between the two points, h' is the oblique projection frequency fobThe corresponding virtual height;
the incident elevation α at an Es height of 110 km is calculated by:
wherein D is the jump length of the n-jump mode calculated by D ═ D/n, R0The radius of the earth.
Magnetic spin frequency f at Es layer control pointHThe calculation formula is as follows:
in the formula gnIs the latitude of geomagnetism, R0The radius of the earth.
The absorption of the E-mode ionization layer and the associated electron cyclotron frequencies were selected as shown in the table below.
| Path Length (Km) | |
| 0<D≤2000 | M |
| 2000<D≤4000 | T+1000,M,R-1000 |
M: a link intermediate point; t: a transmitter location; r: the receiver position.
A one-transmission multi-reception small area vertical measurement network is constructed, and a schematic diagram of one-transmission four-reception detection is shown in figure 2. And reading data in the graph by a manual-based method according to the frequency-height graph obtained by the vertical measurement, wherein the graph with few distinguishable traces is not adopted. In order to obtain better effect, common data processing methods such as interpolation, filtering and the like can be used for interpolating data which are missing in a small amount in the diagram, and smoothing is performed, wherein the ionosphere vertical diagram is shown in fig. 3. In ionospheric vertical sounding, the basic characteristics of ionospheric Es are usually described by two parameters, namely the false height of Es and foEs. And acquiring information such as multi-station foEs.
Step 2: and (4) performing kriging reconstruction by using several sites foEs, drawing the regional distribution condition of the foEs, and calculating the ionosphere foEs value at the high-frequency link reflection point. The method comprises the following steps:
step 21: performing kriging reconstruction by using several sites of the foEs, and drawing the regional distribution condition of the foEs;
step 22: calculating an ionized layer foEs value at the reflection point of the high-frequency link according to the position information of the HF link reflection point;
and reconstructing the data of the foEs near the reflection point of the specific short-wave communication link, and calculating the value of the foEs at the reflection point.
Let Z (x, y) be the characteristic parameter of ionosphere, n in known areaThe value Z (x) of the ionospheric characteristic parameter measured by the observation stationi,yi) 1,2,3, …, n, then any point (x) in the region0,y0) Kriging estimate Z ofp(x0,y0) Can be expressed as:
wherein WiIs a weight coefficient; wiSatisfies the following conditions:
wherein d isijIs the ionospheric distance between two points of the ionosphere,
where Lon (i), Lon (j) and Lat (i), Lat (j) respectively represent the geographical longitude and latitude of the receiving and transmitting stations, and SK and SF are respectively longitude-or latitude-related distance scale factors.
Taking a reflection station as a center, taking the variation range of the area as +/-0.5 degrees and the longitude and latitude stepping value as 0.1 degrees, calculating the foEs value of each point in the network, carrying out foEs reconstruction on the characteristic point value of the area by utilizing a kriging interpolation method, drawing a foEs area distribution diagram at the moment, and calculating the foEs value at the reflection point.
And step 3: by means of a national defense science and technology industrial electric wave environment observation station network, the change characteristics of the foEs at intervals of 5 minutes and 15 minutes are analyzed, and the statistical characteristics of the foEs changing along with time are researched. The method comprises the following steps:
step 31: searching a radio wave observation station near a reflection point by relying on a national defense science and technology industrial radio wave environment observation station network to obtain ionosphere environment data;
step 32: the foEs change characteristics were analyzed at 5-minute and 15-minute intervals and the statistical properties of the foEs over time were studied.
And analyzing the change rule of the ionospheric environment data of the observation station closest to the reflection point by depending on a national defense science and technology industrial electric wave environment observation station network, and taking the change rule as the change characteristic of parameters such as ionospheric foEs and the like near the reflection point. The specific process is as follows:
the electric wave observation stations of the national defense science and technology industrial electric wave environment observation station network carry out 24-hour uninterrupted ionosphere vertical detection all the year around, the distribution of the electric wave observation stations is shown as the attached figure 4, the checking work of manually checking the ionosphere monthly report data is carried out on the initially acquired interpretation data, all 18 observation stations are checked in a spot check mode, and the accuracy of the observation ionization diagram and the interpretation data is ensured.
And (3) calculating the great circle distance from the reflection point to different observation stations by using the great circle distance calculation formula (1), selecting the ionospheric environment data of the nearest observation station, analyzing the ionospheric environment change rule, and taking the ionospheric environment change rule as the change characteristics of parameters such as ionospheric foEs and the like near the reflection point.
The foEs change characteristics were analyzed at 5-minute and 15-minute intervals as shown in fig. 5a, 5 b. The 5-minute encrypted samples and the 15-minute encrypted samples reflect the same change trend of Es, but the 5-minute encrypted observation can better reflect the change details of Es. For example, 55 minutes of foEs at 0 have a peak of 11.3MHz, and the observation result at a sampling interval of 15 minutes only reflects that the foEs increases at about 1 hour, and the peak is 9.4MHz, which cannot reflect the change details of 11.3 MHz. The same occurs for variations in foEs at 12 and 20, with 15 minute sampling retaining the trend of variation in foEs, but with possible loss of sampling over peak and trough variations.
The summer foEs statistical variation characteristics are shown in fig. 6a-6 f. When the foEs are larger than 3MHz, although the incidence rate of the two stations can reach 100% before and after noon in summer, the continuous area of the Chongqing station is obviously larger than that of the Mandarin station, and the incidence rate of the Chongqing station is still over 60% in part of months and less than 40% in the Mandarin station at night. In winter and seasons, the probability that foEs is larger than 3MHz in the day part of the Chongqing station exceeds 80%, which is far higher than that of the Manchurian station. It can be seen from two groups of pictures with the foEs greater than or equal to 5MHz and 7MHz, that the maximum value of the incidence still appears at or near the noon in summer, but the maximum values of the two stations are greatly different, the maximum values of the Chongqing stations are respectively 70% and 46%, and the maximum values of the Chongqing stations are respectively 45% and 16%. And analyzing the short-term variation rule of the foEs in the period of the last three days.
In general, as shown in fig. 7, the ever-red, sunny and maran farm foEs have almost the same variation trend, and the four station foEs have jumping values around the night; the red light and the permanent red light are the closest, the overall variation trend of the foEs values is the closest, the kaland farm is the farthest from the red light, and the partial period of the foEs values are obviously reduced, which may be related to the measured variation area of the red light station foEs, the antenna gain and the distance received by the kaland farm, and other factors.
And 4, step 4: and analyzing whether the reflection point foEs layer exists or not according to the statistical properties of the foEs and the foEs region distribution diagram, and analyzing the variation analysis and trend of the FoEs so as to predict the variation trend of the foEs at the next moment of the reflection point. The method comprises the following steps:
step 41: if the foEs value at the reflection point is not more than 2.5MHz, the Es layer does not exist; if the foEs value is larger than 2.5MHz, the Es layer exists;
step 42: when the Es layer exists, drawing a foEs regional distribution map for the first hours; and analyzing the variation characteristic of the areas foEs near the reflection points according to the statistical characteristic of the foEs and the foEs area distribution diagram.
Step 43: and predicting the change trend of the foEs at the next moment according to the foEs change characteristics and the reconstructed or measured values of the foEs.
Drawing a foEs region distribution map for several hours before, and analyzing the change trend of the foEs region, wherein the specific method comprises the following steps: and judging whether the Es layer exists or not. And if the Es layer exists, calculating the values of the fos in the small area grid, and drawing a distribution map of the fos area in the first hours. And analyzing the movement direction and the variation trend of the foEs by combining a plurality of foEs region distribution graphs, and predicting the variation trend of the foEs at the next moment.
FIGS. 8a to 8d show the reconstruction results of the region where 4MHz < foEs > is less than or equal to 6MHz at 17 days 6 months in 2015, and when 4MHz < foEs > is less than or equal to 6MHz, the spatial variation of the value of foEs is less than or equal to 1MHz within 60 kilometers centering on a permanent red station. FIG. 8a shows that the longitude gradually decreases from left to right for fos, the fos value does not exceed 1MHz, and the spatial variation is obvious, reflecting that the Es peak is on the left side of the graph; FIG. 8b is a graph of the foEs continuing the trend of FIG. 8a, but the value of the foEs does not exceed 0.6MHz, which may mean that the peak of the foEs is far away from the region, and the Es moves to the lower left or gradually weakens, resulting in the observation region of the foEs becoming smaller; in fig. 8c, the variation trend of the fos is changed, the latitude gradually decreases from bottom to top, and the spatial variation of the fos value does not exceed 0.6MHz, which may be that a new weak Es layer appears; fig. 8d shows the longitude gradually decreasing from left to right for fos whose values vary spatially by no more than 0.6 MHz. From the above analysis, for example, for the point (42 ° N, 86.2 ° E), it is predicted that the foEs at the next time has a tendency to become smaller.
FIGS. 9a to 9d show the reconstructed results of the region 7MHz < foEs >10MHz at 17 days 6 and 6 months 2015, when the 7MHz < foEs >10MHz, the space change of the foEs is severe within 60 km with the Yonghong station as the center, a trough appears at the bottom of FIG. 9a, the latitude gradually increases from bottom to top, and the change of the foEs is not more than 0.5 MHz; in FIG. 9b, the fos spatial changes gradually, the longitude gradually decreases from left to right, the fos value does not change more than 2MHz, and the fos value spatial changes violently; in FIG. 9c, the variation trend of the foEs is changed suddenly, the latitude gradually decreases from bottom to top, and the variation of the foEs is not more than 0.6 MHz; in fig. 9d, the fos varies more gradually, and the fos varies no more than 0.5MHz, with the latitude gradually increasing from bottom to top, and the longitude gradually decreasing from left to right. Overall, the foEs values vary strongly in spatial situation.
Fig. 10a-10d show the reconstruction results of the area where foEs >10MHz at 17 th day 6/2015, when the foEs >10MHz, the variation of the foEs value within 60 km around the permanent red station exceeds 2MHz, the spatial variation is severe, but the spatial situation is not changed greatly with time. FIG. 10a shows a trough at the bottom, the latitude gradually increases from bottom to top, and the foEs value does not change more than 1 MHz; in FIG. 10b, the fos is spatially gradual, with longitude gradually decreasing from left to right, with a peak at the lower left, with the fos varying by more than 2 MHz; in FIG. 10c, the foEs continues to have a trend of 18:15, but the lower contour lines of the graph are drawn apart, which may mean that the peak of the foEs is far away from the region, and the Es moves to the lower left or gradually weakens, so that the observation region foEs becomes smaller; in fig. 10d, the trend of the fos changes from 18:30, the latitude gradually increases from bottom to top, and the longitude gradually decreases from left to right, but the variation of the fos value does not exceed 2MHz, which may mean that the fos peak value is far away from the area, and the Es moves to the lower left or gradually decreases, so that the observation area fos becomes smaller. From the above analysis, for example, for the point (42 ° N, 86.2 ° E), it is predicted that the foEs at the next time has a tendency to become smaller.
FIGS. 11a-11j show the results of region reconstruction when the fos was changed drastically at 1:45-4:00 on 17 days 6 months 6 years 2015, with one region reconstructed every 15 minutes for ten subgraphs. The values of the fos in fig. 11a do not exceed 2.8MHz at maximum, indicating that the area fos is in a quiet period, and the longitude gradually increases from left to right, reflecting a new Es layer moving from the upper right. FIG. 11b continues the trend of FIG. 11a, but the foEs value does not exceed 8MHz at maximum, the foEs value varies over 4MHz, and the spatial variation is severe. FIG. 11c continues the trend of FIG. 11b, with the maximum value of the foEs value increasing, and FIG. 11c shows that the foEs has a peak. FIG. 11d reflects that Es continues to move latitudinally, with the maximum value of foEs not exceeding 7MHz, beginning to decrease. FIG. 11e reflects that the foEs peak continues to move away from the region and the maximum value of the foEs value continues to decrease, not exceeding 4.2 MHz. FIG. 11f shows a new FoEs peak moving latitudinally upward from below, with the maximum value of the FoEs value not exceeding 11MHz and the value of the FoEs value not exceeding 2 MHz. FIG. 11g shows that the foEs has peaks, the maximum value of the foEs value does not exceed 13MHz, and the regional variation does not exceed 1 MHz. Fig. 11h shows that the foEs peaks gradually become weaker in intensity, the maximum value of the foEs values does not exceed 8MHz, and the regional variation does not exceed 0.8MHz, for example, for a point (42 ° N, 86.2 ° E), it can be predicted that the foEs at the next moment has a tendency to become smaller. FIG. 11i continues the trend of FIG. 11h, the maximum value of the foEs value does not exceed 7.8MHz, and the regional variation exceeds 1.5MHz, which reflects that the regional variation of the foEs is relatively large. The variation trend of fig. 11j is completely different from that of fig. 11i, and gradually decreases from right to left fos along longitude, the maximum value of the fos value does not exceed 6.6MHz, and a new Es layer appears. From the above analysis, for example, for the point (42 ° N, 86.2 ° E), it is predicted that the foEs at the next time has a tendency to become smaller.
Fig. 12 shows the regional reconstruction result when the foEs is very small in 5/27/2015, and if the value of the foEs is very small and does not reach 2.5MHz, it is predicted that strong Es does not appear at the next time.
Claims (1)
1. A method for predicting the change trend of Es in a summer area is characterized by comprising the following steps:
step 1, calculating the great circle distance and the position of a reflection point of an HF link according to the position information of the transmission and reception point, constructing a one-transmission-multiple-reception vertical measurement network near the reflection point, and acquiring the foEs values of ionosphere vertical measurements of a plurality of observation stations, wherein the method specifically comprises the following steps:
step 11: calculating the great circle distance of the oblique communication link according to the position information of the transmitting and receiving points, and inverting the coordinates of the reflection point of the high-frequency link;
the specific method for calculating the great circle distance of the communication link comprises the following steps:
if the ground transmitting point of the communication link is a and the receiving point is B, the great circle distance D between the two points A, B is:
D＝111.18Φ(°) (1)
wherein phi is a great circle geocentric angle between A, B points;
let the geographical latitude and longitude of points A and B be lA、aAAnd lB、aBIf north latitude is positive, south latitude is negative, east longitude is positive, and west longitude is negative, Φ satisfies:
cosΦ＝sinlAsinlB+coslAcoslBcos(aA-aB) (2)
the specific method for calculating the coordinates of the reflection points of the communication link comprises the following steps:
for a communication link with a great circle distance less than 3000km, taking the middle point of the path as a reflection point of a link propagation path, and then taking the latitude and longitude l of the reflection pointn、anAnd geomagnetic latitude gnRespectively, as follows:
ln＝arcsin[sinlAcosΦn+coslAsinΦncosΦA](3)
gn＝90°-arccos[sin78.5° sinln+cos78.5° coslncos(an-69.0°)](5)
wherein phinIs the great circle geocentric angle between the A terminal and the reflection point, Delta a>0 is given a negative sign, Δ a<0 takes the positive sign; phiAIs the azimuth angle from the A terminal to the B terminal, phiBThe azimuth angle from the B end to the A end is defined as positive north being 0 degree and clockwise direction, i.e. positive east, phiAAnd phiBRespectively satisfy:
step 12: constructing a one-transmitting and multi-receiving vertical measurement network, acquiring an ionosphere vertical measurement frequency height map of each ionosphere observation station by utilizing an ionosphere vertical detection technology, and reading the foEs value of the vertical ionosphere;
step 2, using several sites foEs to perform kriging reconstruction, drawing the regional distribution situation of the foEs, and calculating the ionosphere foEs value at the high-frequency link reflection point, specifically comprising:
step 21: performing kriging reconstruction by using several sites of the foEs, and drawing the regional distribution condition of the foEs;
step 22: calculating an ionized layer foEs value at the reflection point of the high-frequency link according to the position information of the HF link reflection point;
the specific method for reconstructing the data of the foEs near the reflection point of the specific short-wave communication link and calculating the value of the foEs at the reflection point comprises the following steps:
setting Z (x, y) as the characteristic parameter of the ionized layer, and obtaining the values Z (x) of the characteristic parameter of the ionized layer measured by n observation stations in the known areai,yi) 1,2,3, …, n, then any point (x) in the region0,y0) Kriging estimate Z ofp(x0,y0) Can be expressed as:
wherein WiIs a weight coefficient; wiSatisfies the following conditions:
wherein d isijIs the ionospheric distance between two points of the ionosphere,
wherein Lon (i), Lon (j) and Lat (i), Lat (j) respectively represent the geographic longitude and latitude of the receiving and transmitting stations, and SK and SF are respectively longitude or latitude related distance scale factors;
taking a reflection station as a center, taking the variation range of an area as +/-0.5 degrees and the longitude and latitude stepping value as 0.1 degrees, calculating the foEs value of each point in the network, carrying out foEs reconstruction on the characteristic point value of the area by utilizing a kriging interpolation method, drawing a foEs area distribution diagram at the moment, and calculating the foEs value at the reflection point;
step 3, analyzing the change characteristics of the foEs at intervals of 5 minutes and 15 minutes by depending on a national defense science and technology industrial electric wave environment observation station network, and researching the statistical characteristics of the foEs along with the change of time, wherein the method specifically comprises the following steps:
step 31: by depending on a national defense science and technology industrial electric wave environment observation station network, calculating great circle distances from reflection points to different observation stations by using a great circle distance calculation formula (1), selecting ionized layer environment data of the nearest observation station, analyzing an ionized layer environment change rule, and taking the ionized layer environment change rule as a change characteristic of ionized layer foEs parameters near the reflection points;
step 32: analyzing the change characteristics of the foEs at intervals of 5 minutes and 15 minutes, and researching the statistical characteristics of the foEs along with the change of time;
analyzing the variation characteristics of the foEs at the interval of 5 minutes and 15 minutes, namely statistically analyzing the summer foEs statistical variation characteristics and the foEs variation rule in the period of three days;
and 4, step 4: analyzing whether a reflection point foEs layer exists or not according to the statistical characteristics of the foEs and the foEs regional distribution diagram, analyzing the variation trend of the foEs, and further predicting the variation trend of the foEs at the next moment of the reflection point, wherein the method specifically comprises the following steps:
step 41: if the foEs value at the reflection point is not more than 2.5MHz, the Es layer does not exist; if the foEs value is larger than 2.5MHz, the Es layer exists;
step 42: when an Es layer exists, calculating the values of the foEs in the small-area grid, and drawing a distribution diagram of the foEs area in the first hours; analyzing the change characteristic of the areas foEs near the reflection point according to the statistical characteristic of the foEs and the foEs area distribution map;
step 43: and analyzing the moving direction and the variation trend of the fos according to the variation characteristic of the fos and the reconstruction or measured value of the fos and combining a plurality of fos regional distribution graphs, and predicting the variation trend of the fos at the next moment of the reflecting point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911321227.5A CN111323807B (en) | 2019-12-20 | 2019-12-20 | Method for predicting change trend of Es in summer area |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911321227.5A CN111323807B (en) | 2019-12-20 | 2019-12-20 | Method for predicting change trend of Es in summer area |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111323807A true CN111323807A (en) | 2020-06-23 |
| CN111323807B CN111323807B (en) | 2022-03-25 |
Family
ID=71168661
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911321227.5A Active CN111323807B (en) | 2019-12-20 | 2019-12-20 | Method for predicting change trend of Es in summer area |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111323807B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150192670A1 (en) * | 2014-01-08 | 2015-07-09 | Electronics And Telecommunications Research Institute | Method and apparatus for extracting ionospheric trace |
| CN105116469A (en) * | 2015-08-05 | 2015-12-02 | 中国电子科技集团公司第二十二研究所 | Method for forecasting occurrence probability of ionospheric scintillation in low-latitude areas of China |
| RU2660119C1 (en) * | 2017-06-19 | 2018-07-05 | Федеральное государственное автономное образовательное учреждение высшего образования "Национальный исследовательский Нижегородский государственный университет им. Н.И. Лобачевского" | Method for determining the atomic mass of metal ions in the sporadic layer e (es) |
| CN109490641A (en) * | 2019-01-05 | 2019-03-19 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | A kind of calculation method of middle latitude area Sporadic E layer short wave field strength |
-
2019
- 2019-12-20 CN CN201911321227.5A patent/CN111323807B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150192670A1 (en) * | 2014-01-08 | 2015-07-09 | Electronics And Telecommunications Research Institute | Method and apparatus for extracting ionospheric trace |
| CN105116469A (en) * | 2015-08-05 | 2015-12-02 | 中国电子科技集团公司第二十二研究所 | Method for forecasting occurrence probability of ionospheric scintillation in low-latitude areas of China |
| RU2660119C1 (en) * | 2017-06-19 | 2018-07-05 | Федеральное государственное автономное образовательное учреждение высшего образования "Национальный исследовательский Нижегородский государственный университет им. Н.И. Лобачевского" | Method for determining the atomic mass of metal ions in the sporadic layer e (es) |
| CN109490641A (en) * | 2019-01-05 | 2019-03-19 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | A kind of calculation method of middle latitude area Sporadic E layer short wave field strength |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111323807B (en) | 2022-03-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kirincich | Remote sensing of the surface wind field over the coastal ocean via direct calibration of HF radar backscatter power | |
| CN109490641B (en) | Method for calculating field intensity of short wave of sporadic E layer in mid-latitude area | |
| Zhang et al. | Locating narrow bipolar events with single-station measurement of low-frequency magnetic fields | |
| Dymond | Global observations of L band scintillation at solar minimum made by COSMIC | |
| US20110238314A1 (en) | Methodology for Short-term and Impending Earthquake Prediction | |
| CN110031916A (en) | Rainfall intensity measurement method based on satellite-ground link attenuation effect | |
| CN111337549A (en) | GPS multi-satellite fusion soil humidity monitoring method based on fuzzy entropy | |
| Valtr et al. | Estimation of the refractivity structure of the lower troposphere from measurements on a terrestrial multiple-receiver radio link | |
| Chen et al. | Exploration and validation of wave-height measurement using multifrequency HF radar | |
| CN114186484A (en) | Surface soil humidity remote sensing inversion method suitable for high-altitude area | |
| Wang et al. | Operational C-band dual-polarization radar QPE for the subtropical complex terrain of Taiwan | |
| CN106842155B (en) | Wireless fixed emission source positioning method based on spatial interpolation and cluster analysis | |
| CN115754487A (en) | Ultra-long-distance lightning positioning method and system based on very-low-frequency electromagnetic pulse signals | |
| Conroy et al. | Statistical analysis of refractive and diffractive scintillation at high latitudes | |
| CN111323807B (en) | Method for predicting change trend of Es in summer area | |
| CN116953707B (en) | Tidal level monitoring radar device, and monitoring method and system | |
| CN114089443B (en) | UHF frequency band ionosphere scintillation event forecasting method based on TEC integral quantity and seasonal variation coefficient | |
| CN109991564B (en) | Short wave single station positioning result deviation rectifying method based on neural network | |
| CN116029162A (en) | Flood disaster inundation range monitoring method and system by using satellite-borne GNSS-R data | |
| Said et al. | Empirical Parameterization of Broadband VLF Attenuation in the Earth‐Ionosphere Waveguide | |
| Zhang et al. | The seasonal dependence of cycle slip occurrence of GPS data over China low latitude region | |
| Amabayo et al. | Instantaneous ionospheric scintillation mapping over the east African region by use of GPS derived amplitude scintillation proxy | |
| CN117313436B (en) | Method for homogenizing effective wave height and ocean wave spectrum of ocean wave weather forecast | |
| CN117135639B (en) | Wireless communication coverage prediction method, system and equipment based on neural network | |
| Yu et al. | 3 Spatial-Temporal Variation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |