CN114943132B - Method for automatically inverting ionosphere parameters based on inclinometry ionization diagram - Google Patents

Method for automatically inverting ionosphere parameters based on inclinometry ionization diagram Download PDF

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CN114943132B
CN114943132B CN202210215434.8A CN202210215434A CN114943132B CN 114943132 B CN114943132 B CN 114943132B CN 202210215434 A CN202210215434 A CN 202210215434A CN 114943132 B CN114943132 B CN 114943132B
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inclinometry
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CN114943132A (en
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张旭辉
姜春华
刘桐辛
杨国斌
赵正予
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Wuhan University WHU
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Abstract

The invention discloses a method for automatically inverting ionosphere parameters based on an inclinometry ionization diagram. The method comprises the steps of determining initial parameters and enumeration intervals of a QPS model; selecting each group of QPS parameters to construct background electron density and synthesizing a theoretical vertical measurement ionization diagram; converting the theoretical vertical measurement ionization diagram into a theoretical oblique measurement ionization diagram; if the frequency parameter difference and the group path parameter difference of the theoretical inclinometry ionization diagram and the actually measured inclinometry ionization diagram are within the threshold range, performing correlation operation; and after enumeration, taking the QPS parameter corresponding to the maximum correlation value as an ionosphere F2 layer parameter inversion result. The method for directly and automatically inverting the inclinometry ionization map by using the multi-layer quasi-parabolic model disclosed by the invention adopts the multi-layer quasi-parabolic model, converts the vertical measurement ionization map into the inclinometry ionization map for comparison, and is beneficial to improving the accuracy and stability of the inversion result.

Description

Method for automatically inverting ionosphere parameters based on inclinometry ionization diagram
Technical Field
The invention belongs to the technical field of ionosphere electron concentration profile automatic inversion, and particularly relates to a method for automatically inverting ionosphere parameters based on an inclinometry ionization chart.
Background
The ionized layer is a high-level atmospheric region which is partially ionized from about 60km to about 1000km from the ground, and can be divided into 4 different regions according to electron density, namely a layer D, a layer E, a layer F1 and a layer F2. F2 layer is about 200km or more from the ground and is the main area for reflecting radio signals.
The ionosphere oblique detection refers to a process that a transmitter transmits a signal, and the signal reaches a receiving station through ionosphere reflection to obtain an oblique measurement ionization diagram, wherein the transverse axis of the oblique measurement ionization diagram is frequency, the longitudinal axis of the oblique measurement ionization diagram is group path, parameters such as the maximum available frequency, the jump distance and the like of a link can be obtained through oblique detection, the ionosphere of a link relay point can be inverted, ionosphere parameters such as critical frequency, peak height and half thickness of the link relay point are obtained, and then an electron concentration profile at the link relay point can be constructed.
At present, the method for automatically inverting ionosphere parameters according to the inclinometer ionization diagram is roughly divided into two types, wherein one type is to utilize a single-layer quasi-parabolic model to construct inclinometer ionization diagram trace, compare the inclined measurer ionization diagram trace with an actual ionization diagram, search model parameters through an intelligent search algorithm, and directly invert the inclined measurer ionization diagram; the other is to convert the oblique ionization diagram into a vertical ionization diagram, and inversion is carried out by using the existing automatic inversion technology of the vertical ionization diagram which is mature in comparison, so as to obtain the corresponding ionosphere parameters.
Aiming at the current method for automatically inverting the inclinometry ionization map, the method mainly has the following problems:
for the direct automatic inversion of the inclinometry ionization diagram by using a single-layer quasi-parabola, the problem of poor ionosphere model precision exists, because the ionosphere is generally of a multi-layer structure, and a large error exists when the single-layer quasi-parabola model is adopted to represent the ionosphere.
Aiming at the method for converting the actual measurement oblique measurement ionization diagram into the vertical measurement ionization diagram, the actual measurement oblique measurement ionization diagram has poor effect of converting the actual measurement oblique measurement ionization diagram into the vertical measurement ionization diagram and directly influences inversion accuracy due to the fact that the actual measurement ionization diagram has poor echo quality or unstable condition.
Aiming at the problems, the invention provides a method for directly and automatically inverting an inclinometry ionization map by using a multi-layer quasi-parabolic model.
Disclosure of Invention
The invention aims to provide a method for automatically inverting ionosphere parameters based on an inclinometry ionization diagram so as to effectively improve the accuracy and stability of inversion results.
In order to achieve the above purpose, the technical scheme of the invention is a method for automatically inverting ionosphere parameters based on inclinometry ionization diagrams, which is characterized by comprising the following steps:
step 1: generating an initial QPS model parameter vector by utilizing an international reference ionosphere model according to the time of the actual inclinometry ionization diagram and the longitude and latitude information of the actual inclinometry ionization diagram, and further generating a plurality of groups of QPS model parameter vectors according to the initial QPS model parameter vector;
Step 2: generating an ionized layer background electron concentration profile corresponding to each group of QPS model parameter vectors according to the QPS model formula model in sequence, and obtaining theoretical vertical measurement ionization map traces corresponding to each group of QPS model parameter vectors through group refractive index integration by the ionized layer background electron concentration profile corresponding to each group of QPS model parameter vectors;
Step 3: the theoretical vertical measurement ionization diagram trace corresponding to each group of QPS model parameter vectors is obtained by utilizing the equivalent path theorem and the secant theorem;
Step 4: obtaining frequency parameters of an actual measurement inclinometry chart and group path parameters of the actual measurement inclinometry chart through an automatic interpretation algorithm, further obtaining theoretical inclinometry ionization chart trace corresponding to each group of QPS model parameter vectors through an interpretation algorithm, obtaining the frequency parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors and the group path parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, calculating frequency parameter differences between the frequency parameters of the actual measurement inclinometry chart and the frequency parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, calculating group path parameter differences between the group path parameters of the actual measurement inclinometry chart and the group path parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, and if the frequency parameter differences are in a frequency normal threshold range and the group path parameter differences are in a group path normal threshold range, performing correlation calculation on the theoretical inclinometry ionization chart corresponding to the group of QPS model parameter vectors and the actual measurement inclinometry ionization chart, and obtaining correlation values between the theoretical inclinometry ionization chart corresponding to the group of QPS model parameter vectors and the actual measurement inclinometry chart;
Step 5: and obtaining a maximum value of the correlation value between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector through searching in correlation values between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector, and taking the QPS model parameter vector corresponding to the maximum value of the correlation value between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector as an ionosphere parameter inversion result.
Preferably, the initial QPS model parameter vector in step 1 is specifically defined as:
Parameter0＝{foE0,foF10,foF20,hmE0,hmF10,hmF20,ymE0,ymF10,ymF20}
Wherein Parameter 0 represents an initial QPS model Parameter vector, foE 0 represents an E-layer critical frequency of the initial QPS model Parameter vector, foF1 0 represents an F1-layer critical frequency of the initial QPS model Parameter vector, foF2 0 represents an F2-layer critical frequency of the initial QPS model Parameter vector, hmE 0 represents an E-layer electron density peak distance height of the initial QPS model Parameter vector, hmF1 0 represents an F1-layer electron density peak distance height of the initial QPS model Parameter vector, hmF2 0 represents an F2-layer electron density peak distance height of the initial QPS model Parameter vector, ymE 0 represents an E-layer half thickness of the initial QPS model Parameter vector, ymF1 0 represents an F1-layer half thickness of the initial QPS model Parameter vector, ymF2 0 represents an F2-layer half thickness of the initial QPS model Parameter vector,
Step 1, generating a plurality of sets of QPS model parameter vectors according to the initial QPS model parameter vectors, specifically:
Generating the E-layer temporary frequency parameter search interval according to foE 0 is as follows: [ foE 0-ΔfoE,foE0 +Delta foE ] and generating E-layer temporary frequencies of each group of QPS model parameter vectors at equal intervals in the E-layer temporary frequency parameter search interval, wherein Delta foE represents the offset of the E-layer temporary frequencies;
Generating the F1 layer temporary frequency parameter search interval according to foF < 1 > - 0 is as follows: [ foF1 0-ΔfoF1,foF10 +Delta foF1], F1 layer clinical frequencies of each group of QPS model parameter vectors are generated at equal intervals in the F1 layer clinical frequency parameter search interval, and Delta foF1 represents the offset of the F1 layer clinical frequencies;
generating the F2 layer temporary frequency parameter search interval according to foF < 2 > - 0 is as follows: [ foF2 0-ΔfoF2,foF20 +Delta foF2], generating F2 layer temporary frequencies of each group of QPS model parameter vectors at equal intervals in the F2 layer temporary frequency parameter search interval, wherein Delta foF2 represents the offset of the F2 layer temporary frequencies;
Generating an E-layer electron density parameter search interval according to hmE 0 is as follows: [ hmE 0-ΔhmE,hmE0 +Delta hmE ], wherein the E-layer electron density peak distance height of each group of QPS model parameter vectors is generated at equal intervals in the E-layer electron density parameter search interval, and Delta hmE represents the offset of the E-layer electron density;
Generating the F1 layer electron density parameter search interval according to hmF < 1 > - 0 is: [ hmF1 0-ΔhmF1,hmF10 +Delta hmF1], wherein the heights of the F1 layer electron density peak values of each group of QPS model parameter vectors are generated at equal intervals in the F1 layer electron density parameter search interval, and Delta hmF1 represents the offset of the F1 layer electron density;
Generating the F2 layer electron density parameter search interval according to hmF < 2 > - 0 is: [ hmF2 0-ΔhmF2,hmF20 +Delta hmF2], wherein the heights of the F2-layer electron density peak values of each group of QPS model parameter vectors are generated at equal intervals in the F2-layer electron density parameter search interval, and Delta hmF2 represents the offset of the F2-layer electron density;
Generating an E-layer half-thickness parameter search interval according to ymE 0 is as follows: [ ymE 0-ΔymE,ymE0 +Delta ymE ] and generating E-layer half thicknesses of each group of QPS model parameter vectors at equal intervals in the E-layer half thickness parameter search interval, wherein Delta ymE represents the offset of the E-layer half thicknesses;
The F1 layer half thickness parameter search interval generated according to ymF <1 > - 0 is: [ ymF1 0-ΔymF1,ymF10 +Delta ymF1], generating F1 layer half thickness of each group of QPS model parameter vectors at equal intervals in the F1 layer half thickness parameter search interval, wherein Delta ymF1 represents the offset of the F1 layer half thickness;
The F2 layer half thickness parameter search interval generated according to ymF < 2 > - 0 is: [ ymF2 0-ΔymF2,ymF20 +Delta ymF2], generating F2 layer half thicknesses of each group of QPS model parameter vectors at equal intervals in the F2 layer half thickness parameter search interval, wherein Delta ymF2 represents the offset of the F2 layer half thicknesses;
The multiple sets of QPS model parameter vectors in step 1 are:
Parameteri＝{foEi,foF1i,foF2i,hmEi,hmF1i,hmF2i,ymEi,ymF1i,ymF2i}i∈[1,N]
wherein paramter i represents an i-th set of QPS model Parameter vectors, foE i represents an E-layer critical frequency of the i-th set of QPS model Parameter vectors, foF1 i represents an F1-layer critical frequency of the i-th set of QPS model Parameter vectors, foF2 i represents an F2-layer critical frequency of the i-th set of QPS model Parameter vectors, hmE i represents an E-layer electron density peak-to-ground height of the i-th set of QPS model Parameter vectors, hmF1 i represents an F1-layer electron density peak-to-ground height of the i-th set of QPS model Parameter vectors, hmF2 i represents an F2-layer electron density peak-to-ground height of the i-th set of QPS model Parameter vectors, ymE i represents an E-layer half thickness of the i-th set of QPS model Parameter vectors, ymF1 i represents an F1-layer half thickness of the i-th set of QPS model Parameter vectors, ymF2 i represents a number of sets of QPS model Parameter vectors;
Preferably, in the step 4, a frequency parameter difference between the frequency parameter of the actually measured inclinometry graph and the frequency parameter of the theoretical inclinometry ionization graph corresponding to each set of QPS model parameter vectors is calculated as follows:
fxMUF_E0-foMUF_Ei、fxMUF_F10-foMUF_F1i、fxMUF_F20-foMUF_F2i
Wherein fxMUF _e 0 represents the maximum usable frequency of the X-wave of the measured inclinometry graph E layer, fxMUF _f1 0 represents the maximum usable frequency of the X-wave of the measured inclinometry graph F1 layer, fxMUF _f2 0 represents the maximum usable frequency of the X-wave of the F2 layer of the measured inclinometry graph, foMUF _e i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph E layer corresponding to the i-th set of QPS model parameter vectors, foMUF _f1 i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph F1 layer corresponding to the i-th set of QPS model parameter vectors, foMUF _f2 i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph F2 layer corresponding to the i-th set of QPS model parameter vectors;
and step 4, calculating a group path parameter difference between the group path parameters of the actually measured inclinometry graph and the group path parameters of the theoretical inclinometry ionization graph corresponding to each group of QPS model parameter vectors, wherein the group path parameter difference is as follows:
PminE0-PminEi、PminF10-PminF1i、PminF20-PminF2i
Wherein PminE 0 represents the minimum group path of the measured inclinometry graph E layer, pminF1 0 represents the minimum group path of the measured inclinometry graph F1 layer, pminF2 0 represents the minimum group path of the measured inclinometry graph F2 layer, pminE i represents the minimum group path of the theoretical inclinometry graph E layer corresponding to the i-th group QPS model parameter vector, pminF1 i represents the minimum group path of the theoretical inclinometry graph F1 corresponding to the i-th group QPS model parameter vector, pminF2 i represents the minimum group path of the theoretical inclinometry graph F2 layer corresponding to the i-th group QPS model parameter vector;
in step 4, if the frequency parameter difference is within the frequency normal threshold range and the group path parameter difference is within the group path normal threshold range, the method specifically comprises the following steps:
If the F1 layer is not present:
If the F1 layer is present:
Wherein fxMUF _e 0 represents the maximum usable frequency of the X-wave of the layer E of the measured inclinometry graph, fxMUF _f1 0 represents the maximum usable frequency of the X-wave of the layer F1 of the measured inclinometry graph, fxMUF _f2 0 represents the maximum usable frequency of the X-wave of the layer F2 of the measured inclinometry graph, pminE 0 represents the minimum group path of the layer E of the measured inclinometry graph, pminF1 0 represents the minimum group path of the layer F1 of the measured inclinometry graph, pminF2 _f2 0 represents the minimum group path of the layer F2 of the measured inclinometry graph;
foMUF _e i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph E layer corresponding to the i-th group QPS model parameter vector, foMUF _f1 i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph F1 layer corresponding to the i-th group QPS model parameter vector, and foMUF _f2 i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph F2 layer corresponding to the i-th group QPS model parameter vector; pminE i denotes the minimum group path of the theoretical inclinometry map E layer corresponding to the i-th group QPS model parameter vector, pminF1 i denotes the minimum group path of the theoretical inclinometry map F1 layer corresponding to the i-th group QPS model parameter vector, pminF2 i denotes the minimum group path of the theoretical inclinometry map F2 layer corresponding to the i-th group QPS model parameter vector;
Δmuf_e min represents the minimum value of the prescribed range of the difference of the measured inclinometer and the theoretical inclinometer layer E frequency parameters corresponding to each set of QPS model parameter vectors, Δmuf_e max represents the maximum value of the prescribed range of the difference of the measured inclinometer and the theoretical inclinometer layer E frequency parameters corresponding to each set of QPS model parameter vectors, Δmuf_f1 min represents the minimum value of the prescribed range of the difference of the measured inclinometer and the theoretical inclinometer layer F1 frequency parameters corresponding to each set of QPS model parameter vectors, Δmuf_f1 max represents the maximum value of the prescribed range of the difference of the measured inclinometer and the theoretical inclinometer layer F1 frequency parameters corresponding to each set of QPS model parameter vectors, Δmuf_f2 min represents the minimum value of the prescribed range of the difference of the measured inclinometer and the theoretical inclinometer layer F2 frequency parameters corresponding to each set of QPS model parameter vectors, and Δmuf_f2 max represents the prescribed range of the difference of the measured inclinometer and theoretical inclinometer layer F2 parameters corresponding to each set of QPS model parameter vectors;
Δ PminE represents the maximum value of the absolute value prescribed range of the difference between the measured inclinometer and the theoretical inclinometer E layer group path parameter corresponding to each set of QPS model parameter vectors, Δ PminF1 represents the maximum value of the absolute value prescribed range of the difference between the measured inclinometer and the theoretical inclinometer F1 layer group path parameter corresponding to each set of QPS model parameter vectors, and Δ PminF2 represents the maximum value of the absolute value prescribed range of the difference between the measured inclinometer and the theoretical inclinometer F2 layer group path parameter corresponding to each set of QPS model parameter vectors;
Compared with the prior art, the invention has the beneficial effects that: the invention provides a method for automatically inverting F2 layer parameters by using an inclinometry ionization diagram, which is based on a QPS electron density model, converts a theoretically synthesized vertical inclinometry ionization diagram into a theoretical inclinometry ionization diagram by using an equivalent path theorem and a secant theorem, interprets to obtain a measured inclinometry ionization diagram and a theoretical inclinometry ionization diagram to obtain corresponding multi-layer frequency parameters and multi-layer group path parameters, and if the multi-layer frequency parameter differences and the multi-layer group path parameter differences of the theoretical inclinometry ionization diagram and the measured inclinometry ionization diagram are in a threshold range, carries out correlation operation on the theoretical inclinometry ionization diagram and the measured inclinometry ionization diagram, and selects a QPS parameter value corresponding to a maximum correlation value as an inversion result. The multi-layer frequency parameters and the multi-layer group path parameters of the QPS model are beneficial to improving the accuracy and stability of inversion results.
Drawings
Fig. 1: the invention discloses a flow chart of an inversion method of an inclinometry ionization diagram;
fig. 2: a vertical measurement chart synthesized by theory;
fig. 3: converting the vertical ionization diagram into a schematic diagram of an oblique ionization diagram;
fig. 4: converting the vertical measurement map synthesized in theory into an inclined measurement map;
fig. 5: the method comprises the steps of obtaining an actual inclinometry echo diagram and an inclinometry tracing contrast diagram synthesized based on an inversion result;
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In this embodiment, the great circle distance between the transmitting station and the receiving station is about 1026km, and the adopted oblique detection performance parameters are as follows:
detecting the initial frequency: 2MHz;
Step-by-step detection frequency: 50kHz;
detection termination frequency: 20MHz;
Group distance resolution: 7.68km.
Embodiments of the present invention are described below with reference to fig. 1 to 5.
As shown in FIG. 1, a method for automatically inverting ionosphere parameters based on inclinometry ionization diagrams. The method is characterized by comprising the following steps of:
step 1: generating an initial QPS model parameter vector by utilizing an international reference ionosphere model according to the time of the actual inclinometry ionization diagram and the longitude and latitude information of the actual inclinometry ionization diagram, and further generating a plurality of groups of QPS model parameter vectors according to the initial QPS model parameter vector;
The initial QPS model parameter vector in step 1 is specifically defined as:
Parameter0＝{foE0,foF10,foF20,hmE0,hmF10,hmF20,ymE0,ymF10,ymF20}
wherein paramter 0 represents the initial QPS model Parameter vector, foE 0 =3.2 represents the E-layer critical frequency of the initial QPS model Parameter vector, foF1 0 =4.3 represents the F1-layer critical frequency of the initial QPS model Parameter vector, foF2 0 =7.2 represents the F2-layer critical frequency of the initial QPS model Parameter vector, hmE 0 =110 represents the E-layer electron density peak-to-ground height of the initial QPS model Parameter vector, hmF1 0 =170 represents the F1-layer electron density peak-to-ground height of the initial QPS model Parameter vector, hmF2 0 =260 represents the F2-layer electron density peak-to-ground height of the initial QPS model Parameter vector, ymE 0 =20 represents the E-layer half thickness of the initial QPS model Parameter vector, ymF1 0 =50 represents the F1-layer half thickness of the initial QPS model Parameter vector, and ymF2 0 =50 represents the F2-layer half thickness of the initial QPS model Parameter vector.
Step 1, generating a plurality of sets of QPS model parameter vectors according to the initial QPS model parameter vectors, specifically:
generating the E-layer temporary frequency parameter search interval according to foE 0 is as follows: [ foE 0-ΔfoE,foE0 +Delta foE ] generating E-layer clinical frequencies of each group of QPS model parameter vectors at equal intervals in the E-layer clinical frequency parameter search interval, wherein Delta foE =0.2 represents the offset of the E-layer clinical frequencies;
Generating the F1 layer temporary frequency parameter search interval according to foF <1 > - 0 is as follows: [ foF1 0-ΔfoF1,foF10 +Δ foF1] generating F1 layer frequencies of each group of QPS model parameter vectors at equal intervals in the F1 layer frequency parameter search interval, wherein Δ foF1 =0.2 represents the offset of the F1 layer frequencies;
Generating the F2 layer temporary frequency parameter search interval according to foF < 2 > - 0 is as follows: [ foF2 0-ΔfoF2,foF20 +Δ foF2], generating F2-layer temporary frequencies of each group of QPS model parameter vectors at equal intervals in the F2-layer temporary frequency parameter search interval, wherein Δ foF2 =0.1 represents the offset of the F2-layer temporary frequencies;
generating an E-layer electron density parameter search interval according to hmE 0 is as follows: [ hmE 0-ΔhmE,hmE0 +Δ hmE ] generating the E-layer electron density peak-to-ground height of each group of QPS model parameter vectors at equal intervals in the E-layer electron density parameter search interval, wherein Δ hmE =10 represents the offset of the E-layer electron density peak-to-ground height;
Generating the F1 layer electron density parameter search interval according to hmF < 1 > - 0 is: [ hmF1 0-ΔhmF1,hmF10 +Δ hmF1] generating the F1-layer electron density peak-to-ground height of each set of QPS model parameter vectors at equal intervals within the F1-layer electron density parameter search interval, Δ hmF 1=20 representing the offset of the F1-layer electron density peak-to-ground height;
Generating the F2 layer electron density parameter search interval according to hmF < 2 > - 0 is: [ hmF2 0-ΔhmF2,hmF20 +Δ hmF2] generating the F2-layer electron density peak-to-ground height of each set of QPS model parameter vectors at equal intervals within the F2-layer electron density parameter search interval, Δ hmF2 =50 representing the offset of the F2-layer electron density peak-to-ground height;
generating an E-layer half-thickness parameter search interval according to ymE 0 is as follows: [ ymE 0-ΔymE,ymE0 +Delta ymE ] generating E-layer half thicknesses of each group of QPS model parameter vectors at equal intervals in the E-layer half thickness parameter search interval, wherein Delta ymE =10 represents the offset of the E-layer half thicknesses;
The F1 layer half thickness parameter search interval generated according to ymF < 1 > - 0 is: [ ymF1 0-ΔymF1,ymF10 +Δ ymF1] generating an F1 layer half thickness of each set of QPS model parameter vectors at equal intervals in an F1 layer half thickness parameter search interval, Δ ymF 1=20 representing an offset of the F1 layer half thickness;
the F2 layer half thickness parameter search interval generated according to ymF < 2 > - 0 is: [ ymF2 0-ΔymF2,ymF20 +Δ ymF2], generating F2 layer half thicknesses of each set of QPS model parameter vectors at equal intervals in the F2 layer half thickness parameter search interval, Δ ymF 2=50 representing the offset of the F2 layer half thicknesses;
The multiple sets of QPS model parameter vectors in step 1 are:
Parameteri＝{foEi,foF1i,foF2i,hmEi,hmF1i,hmF2i,ymEi,ymF1i,ymF2i}
i∈[1,N]
Wherein paramter i represents an i-th set of QPS model Parameter vectors, foE i represents an E-layer critical frequency of the i-th set of QPS model Parameter vectors, foF1 i represents an F1-layer critical frequency of the i-th set of QPS model Parameter vectors, foF2 i represents an F2-layer critical frequency of the i-th set of QPS model Parameter vectors, hmE i represents an E-layer electron density peak-to-ground height of the i-th set of QPS model Parameter vectors, hmF1 i represents an F1-layer electron density peak-to-ground height of the i-th set of QPS model Parameter vectors, hmF2 i represents an F2-layer electron density peak-to-ground height of the i-th set of QPS model Parameter vectors, ymE i represents an E-layer half thickness of the i-th set of QPS model Parameter vectors, ymF1 i represents an F1-layer half thickness of the i-th set of QPS model Parameter vectors, ymF2 i represents an F2-layer half thickness of the i-th set of QPS model Parameter vectors, and n=10000 represents the number of sets of QPS model Parameter vectors;
Step 2: generating an ionized layer background electron concentration profile corresponding to each group of QPS model parameter vectors according to the QPS model formula model sequentially by each group of QPS model parameter vectors, and obtaining a theoretical vertical measurement ionization map trace corresponding to each group of QPS model parameter vectors by the ionized layer background electron concentration profile corresponding to each group of QPS model parameter vectors through group refractive index integration, wherein the formula is as follows:
Where h 0 is the bottom height of the layer, hr is the top height of the layer, u' is the group refractive index, N (h) represents the electron density at the h height position, and f represents the radio frequency.
The vertical graph is shown in fig. 2, wherein the horizontal axis is frequency, the vertical axis is virtual height, and the graph has echoes of an E layer, an F1 layer and an F2 layer.
Step 3: the theoretical vertical ionization map trace corresponding to each group of QPS model parameter vectors is obtained by utilizing the equivalent path theorem and the secant theorem, the vertical ionization map trace is converted into the oblique ionization map trace according to the following formula, and the schematic diagram is shown in figure 3.
Where T i is the transmitting station, R i is the receiving station,Is the included angle between the wave and the normal line, theta is half of the central angle of the arc line TR, R represents the earth radius,/>Represents the chord length from the transmitting station to the receiving station, c represents the ground-to-chord/>, of the relay pointIn (2), hv represents the virtual high of the vertical map, fv represents the radio frequency corresponding to the virtual high hv, P represents the group path of the converted oblique ionization map, and fo represents the frequency corresponding to the group path P.
The transformed inclinometer is shown in figure 4, wherein the horizontal axis is frequency, the vertical axis is group path, and the inclinometer has inclinometer signals of E layer, F1 layer and F2 layer.
Step 4: obtaining frequency parameters of an actual measurement inclinometry chart and group path parameters of the actual measurement inclinometry chart through an automatic interpretation algorithm, further obtaining theoretical inclinometry ionization chart trace corresponding to each group of QPS model parameter vectors through an interpretation algorithm, obtaining the frequency parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors and the group path parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, calculating frequency parameter differences between the frequency parameters of the actual measurement inclinometry chart and the frequency parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, calculating group path parameter differences between the group path parameters of the actual measurement inclinometry chart and the group path parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, and if the frequency parameter differences are in a frequency normal threshold range and the group path parameter differences are in a group path normal threshold range, performing correlation calculation on the theoretical inclinometry ionization chart corresponding to the group of QPS model parameter vectors and the theoretical inclinometry ionization chart corresponding to the group of QPS model parameter vectors according to the following formula, and obtaining correlation values between the actual measurement inclinometry chart and the actual measurement inclinometry chart;
And step 4, calculating the frequency parameter difference between the frequency parameter of the actually measured inclinometry graph and the frequency parameter of the theoretical inclinometry ionization graph corresponding to each group of QPS model parameter vectors, wherein the frequency parameter difference is as follows:
fxMUF_E0-foMUF_Ei、fxMUF_F10-foMUF_F1i、fxMUF_F20-foMUF_F2i
Wherein fxMUF _e 0 =13.4 represents the maximum usable frequency of the X-wave of the layer E of the measured inclinometry graph, fxMUF _f 0 =10.6 represents the maximum usable frequency of the X-wave of the layer F1 of the measured inclinometry graph, fxMUF _f 0 =13.6 represents the maximum usable frequency of the X-wave of the layer F2 of the measured inclinometry graph, foMUF _e i represents the maximum usable frequency of the O-wave of the layer E of the theoretical inclinometry graph corresponding to the parameter vector of the i-th set QPS model, foMUF _f1 i represents the maximum usable frequency of the O-wave of the layer F1 of the theoretical inclinometry graph corresponding to the parameter vector of the i-th set QPS model, foMUF _f2 i represents the maximum usable frequency of the O-wave of the layer F2 of the theoretical inclinometry graph corresponding to the parameter vector of the i-th set QPS model;
and step 4, calculating a group path parameter difference between the group path parameters of the actually measured inclinometry graph and the group path parameters of the theoretical inclinometry ionization graph corresponding to each group of QPS model parameter vectors, wherein the group path parameter difference is as follows:
PminE0-PminEi、PminF10-PminF1i、PminF20-PminF2i
Wherein PminE 0 =1052 denotes the minimum group path of the measured inclinometry graph E layer, pminF1 0 =1098 denotes the minimum group path of the measured inclinometry graph F1 layer, pminF2 0 =1160 denotes the minimum group path of the measured inclinometry graph F2 layer, pminE i denotes the minimum group path of the theoretical inclinometry graph E layer corresponding to the i-th group QPS model parameter vector, pminF1 i denotes the minimum group path of the theoretical inclinometry graph F1 corresponding to the i-th group QPS model parameter vector, pminF2 i denotes the minimum group path of the theoretical inclinometry graph F2 layer corresponding to the i-th group QPS model parameter vector;
in step 4, if the frequency parameter difference is within the frequency normal threshold range and the group path parameter difference is within the group path normal threshold range, the method specifically comprises the following steps:
If the F1 layer is not present:
If the F1 layer is present:
Wherein fxMUF _e 0 represents the maximum usable frequency of the X-wave of the layer E of the measured inclinometry graph, fxMUF _f1 0 represents the maximum usable frequency of the X-wave of the layer F1 of the measured inclinometry graph, fxMUF _f2 0 represents the maximum usable frequency of the X-wave of the layer F2 of the measured inclinometry graph, pminE 0 represents the minimum group path of the layer E of the measured inclinometry graph, pminF1 0 represents the minimum group path of the layer F1 of the measured inclinometry graph, pminF2 _f2 0 represents the minimum group path of the layer F2 of the measured inclinometry graph;
foMUF _e i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph E layer corresponding to the i-th group QPS model parameter vector, foMUF _f1 i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph F1 layer corresponding to the i-th group QPS model parameter vector, and foMUF _f2 i represents the maximum usable frequency of the O-wave of the theoretical inclinometry graph F2 layer corresponding to the i-th group QPS model parameter vector; pminE i denotes the minimum group path of the theoretical inclinometry map E layer corresponding to the i-th group QPS model parameter vector, pminF1 i denotes the minimum group path of the theoretical inclinometry map F1 layer corresponding to the i-th group QPS model parameter vector, pminF2 i denotes the minimum group path of the theoretical inclinometry map F2 layer corresponding to the i-th group QPS model parameter vector;
Δmuf_e min =0.5 represents the minimum value of the prescribed range of differences in the theoretical inclinometer F1 layer frequency parameters corresponding to the measured inclinometer and each set of QPS model parameter vectors, Δmuf_e max =1.5 represents the maximum value of the prescribed range of differences in the theoretical inclinometer E layer frequency parameters corresponding to the measured inclinometer and each set of QPS model parameter vectors, Δmuf_f min =0.5 represents the minimum value of the prescribed range of differences in the theoretical inclinometer F1 layer frequency parameters corresponding to the measured inclinometer and each set of QPS model parameter vectors, Δmuf_f max =1.5 represents the maximum value of the prescribed range of differences in the theoretical inclinometer F1 layer frequency parameters corresponding to the measured inclinometer and each set of QPS model parameter vectors, Δmuf_f min =0.5 represents the minimum value of the prescribed range of differences in the theoretical inclinometer F2 layer frequency parameters corresponding to the measured inclinometer and each set of QPS model parameter vectors, and Δmuf_f2= 2 max.5 represents the maximum value of differences in the theoretical inclinometer F1 layer frequency parameters corresponding to the measured inclinometer and each set of QPS model parameter vectors;
Δ PminE =10 represents the maximum value of the absolute value prescribed range of the difference between the measured inclinometer and the theoretical inclinometer E layer group path parameter corresponding to each set of QPS model parameter vectors, Δ PminF1 =10 represents the maximum value of the absolute value prescribed range of the difference between the measured inclinometer and the theoretical inclinometer F1 layer group path parameter corresponding to each set of QPS model parameter vectors, and Δ PminF2 =40 represents the maximum value of the absolute value prescribed range of the difference between the measured inclinometer and the theoretical inclinometer F2 layer group path parameter corresponding to each set of QPS model parameter vectors;
Step 5: and obtaining a maximum value of the correlation value between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector through searching in correlation values between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector, and taking the QPS model parameter vector corresponding to the maximum value of the correlation value between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector as an ionosphere parameter inversion result.
The theoretical inclinometry trace synthesized based on the inversion result is shown as a "+" line in fig. 5, so that the synthesized theoretical inclinometry ionization diagram is basically consistent with the actual measurement inclinometry ionization diagram, the accuracy of the ionosphere parameter inversion algorithm is indirectly verified, and the expected effect is achieved.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same: although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (1)

1. The method for automatically inverting ionosphere parameters based on the inclinometry ionization diagram is characterized by comprising the following steps of:
step 1: generating an initial QPS model parameter vector by utilizing an international reference ionosphere model according to the time of the actual inclinometry ionization diagram and the longitude and latitude information of the actual inclinometry ionization diagram, and further generating a plurality of groups of QPS model parameter vectors according to the initial QPS model parameter vector;
Step 2: generating an ionized layer background electron concentration profile corresponding to each group of QPS model parameter vectors according to the QPS model formula model in sequence, and obtaining theoretical vertical measurement ionization map traces corresponding to each group of QPS model parameter vectors through group refractive index integration by the ionized layer background electron concentration profile corresponding to each group of QPS model parameter vectors;
Step 3: the theoretical vertical measurement ionization diagram trace corresponding to each group of QPS model parameter vectors is obtained by utilizing the equivalent path theorem and the secant theorem;
Step 4: obtaining frequency parameters of an actual measurement inclinometry chart and group path parameters of the actual measurement inclinometry chart through an automatic interpretation algorithm, further obtaining theoretical inclinometry ionization chart trace corresponding to each group of QPS model parameter vectors through an interpretation algorithm, obtaining the frequency parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors and the group path parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, calculating frequency parameter differences between the frequency parameters of the actual measurement inclinometry chart and the frequency parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, calculating group path parameter differences between the group path parameters of the actual measurement inclinometry chart and the group path parameters of the theoretical inclinometry ionization chart corresponding to each group of QPS model parameter vectors, and if the frequency parameter differences are in a frequency normal threshold range and the group path parameter differences are in a group path normal threshold range, performing correlation calculation on the theoretical inclinometry ionization chart corresponding to the group of QPS model parameter vectors and the actual measurement inclinometry ionization chart, and obtaining correlation values between the theoretical inclinometry ionization chart corresponding to the group of QPS model parameter vectors and the actual measurement inclinometry chart;
Step 5: and obtaining a maximum value of the correlation value between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector through searching in correlation values between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector, and taking the QPS model parameter vector corresponding to the maximum value of the correlation value between the theoretical inclinometry ionization diagram and the actual measurement inclinometry ionization diagram corresponding to the QPS model parameter vector as an ionosphere parameter inversion result.
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