1. A method for detecting an ionosphere burst abnormal structure by using sky-wave radar is characterized by comprising the following steps: the method comprises the following steps:

step 1: setting ionosphere parameters, and constructing an ionosphere model by combining a multi-quasi-parabolic model according to longitude and latitude information, seasons, weather and time variables in one day of a detection area;

step 2: and according to the characteristics of different abnormal structures, establishing a geographic position, abnormal structure sizes and plasma physical process parameters, and establishing an ionosphere burst abnormal structure model.

And step 3: according to the electromagnetic wave space propagation, combining with the established ionosphere model, obtaining sky wave radar echoes, and obtaining a range-Doppler frequency spectrum of the echoes through Fourier transform;

and 4, step 4: and carrying out frequency domain energy aggregation on the obtained range-Doppler frequency spectrum of the echo in a frequency domain, and classifying and extracting the characteristics of the echo according to different burst abnormal structure characteristics.

2. The method for detecting ionospheric burst anomaly structure by sky-wave radar as claimed in claim 1, wherein: the step 1 specifically comprises the following steps:

the physical process in the ionized layer is divided into a photochemical process and a transportation process, and three physical quantities are determined: the yield q, in cm-3 s-1; the loss rate L (N), as a function of the electron concentration N, in cm-3 s-1; item of transportationV is the net drift velocity, representing the entire course of motion, according toDetecting latitude and longitude information, seasons, weather and time variable in one day of an area, combining a multi-quasi-parabolic model to construct an ionosphere model, and expressing the ionosphere model according to the following formula:

3. the method for detecting ionospheric burst anomaly structure by sky-wave radar as claimed in claim 2, wherein: the step 2 specifically comprises the following steps:

step 2.1: setting up a plasma loss process, wherein the loss process is divided into the following two cases:

when β > α N, then

q＝αN²(Square law loss)

When beta < alpha N, then

q ═ β N (linear loss)

Step 2.2: the electric field is driven by neutral wind, ignoring gravitational fields, pressure gradients and electron-ion collisions, the equation of motion of charged particles in the ionosphere is expressed by:

wherein V is the drift velocity of the charged particles, U is the neutral atmospheric velocity, B is the earth magnetic field strength,is the collision frequency of charged particles with neutral particles;

step 2.3: by the frequency of magnetic rotation of charged particlesThree components of the velocity V in the x, y, z directions are solved, which components are represented by:

wherein the sign of the υ component is for ions and the positive sign is for electrons;

step 2.4: calculating the diffusion speed of the plasma according to the concentration difference between the set sudden abnormal structure and the set normal condition; because the diffusion speed of electrons and ions is the same, and the kinetic energy obtained by the ions and the electrons is equal to the kinetic energy obtained by the ions and the electrons in unit time, under the action of a gravity field, a bipolar diffusion coefficient is deduced by an experimental method to be:

wherein k is Boltzmann constant, q_eFor the electron charge, T and P are the temperature and pressure in the atmosphere, K₀The mobility of the ions in the zero field, here the value of the nitrogen atom is taken to be K₀＝2.5×10^-4m²s^-1V^-1

The inverse relationship of the bipolar diffusion coefficient to the echo decay time is expressed by:

plasma level is defined as:

wherein T is_eIs the electron temperature, T_iIs the ion concentration, m is the ion mass, and g is the acceleration of gravity.

The height in the direction perpendicular to the geocentric is represented by h, an xyz coordinate system is established by taking the pointing direction of the magnetic field B as the z axis, and the height is obtained by the geometrical relationship according to the longitude and latitude of the detection position:

d＝dz sin I

the diffusion speed of the plasma in the vertical direction is represented by the following formula:

diffusion speed in the horizontal direction was obtained:

wherein N is the electron concentration, H is the neutral elevation, and has H_p＝2H。

4. The method for detecting the ionospheric burst anomaly structure by sky-wave radar as claimed in claim 3, wherein: the step 3 specifically comprises the following steps:

step 3.1: calculating the collision frequency of free electrons by setting the electron concentration of different positions in an ionosphere model, wherein multiple particles collide in the plasma, and the collision frequency of electrons and neutral particles is calculated by the following formula:

wherein the content of the first and second substances,is the collision frequency between the electrons and the gas neutrals; t is the gas temperature, n_mDetermining the derived gas particle density according to a gas state equation, wherein the gas neutral particle density is the gas neutral particle density;

the collision frequency of electrons and ions is:

wherein n is_iIs the ion density, T_eIs the electron temperature;

the collision frequency of electrons in the plasma is:

ν＝ν_em+ν_ei

step 3.2: calculating the refractive index of the ionized layer corresponding to the radar emission frequency, and obtaining the relative dielectric constant of the ionized layer according to an electronic motion equation:

wherein m is_eIs the electron mass; epsilon₀Is the dielectric constant of free space; omega is the radio wave angular frequency;

the equation is expressed as the ionospheric medium refractive index n:

step 3.3: calculating the absorption of the ionized layer to electromagnetic wave, and if the relative dielectric constant epsilonr and conductivity sigma of the dielectric medium are known, the attenuation constant alpha is

For short wave propagation, sigma/omega epsilon > 1 is usually satisfied, then

And obtaining an echo signal in an ionized layer by means of the sea clutter, and performing Fourier transform on the echo to obtain a range-Doppler frequency spectrum of the echo signal.

5. The method for detecting the ionospheric burst anomaly structure by sky-wave radar as claimed in claim 4, wherein: the step 4 specifically comprises the following steps:

step 4.1: after the parameters such as the working frequency, the emission pulse width and the like of the antenna over-the-horizon radar are determined, the distance resolution is a fixed value, and after the radar echo is subjected to Fourier transform, a signal spectrum is represented as A (r)_i，d_j) I 1, 2.. the m is the number of range gates, j-N, -N + 1.. the N, N is the doppler frequency point, and in each range gate, the whole doppler frequency spectrum is accumulated to obtain the range frequency domain energy accumulation value at the time tk:

where p is the Doppler frequency range.

Step 4.2: when the background noise is established, a queue with the length of M is established on the time dimension, and the averaging processing is carried out again to obtain t_kBackground noise level estimation at time instant:

will t_kComparing the frequency domain energy value accumulated at the moment with the background noise level estimation of the same range gate, approximating the background noise level estimation to a Schweilin model, obtaining a mean value and a signal fluctuation variance, and determining a signal echo interval according to the fluctuation amount;

when the deviation exceeds an established threshold, the area is listed as a suspected target area for further feature extraction analysis, and the target detection process is shown as the following formula:

wherein H₁Expressed as the presence of a target, H, on the aggregated frequency domain₀The energy of the gathered frequency domain is only background noise, and the rest noise and clutter are represented by Z₀And (4) showing.

In the square law detector, Z is treated as a random variable, the probability density function is normally exponentially distributed, and the background noise level is estimated as being μ ═ ZB (r)_i，t_k)：

When the frequency domain aggregation value contains a target, the function can be expressed as follows, and s is the signal-to-noise ratio of the target and clutter therein:

the threshold value can be selected as follows:

T＝α*Z_B(r_i,t_k)

the parameter α is for controlling the false alarm probability P_faBased on Neyman-Pearson lemma, the false alarm probability P of the optimal detector_faThe target model described as following is Swerling I:

the detection probability is represented by:

step 4.3: after a suspected target is obtained, firstly, coarse classification is carried out from the aggregation amplitude to obtain the frequency domain energy aggregation quantity on the time sequence, and then, the change on the time sequence is further subdivided, so that the discrimination accuracy is improved, and simultaneously, more target parameter characteristics are obtained.

Background

With the rapid development of the times and the continuous progress of science and technology, people have taken the information times, light waves and radio waves become an indispensable part of the lives of people, and the light waves and the radio waves are widely applied to the fields of military use and civil use. Military, modern high-tech wars are the integration of land, sea, air, sound, light and electric information, and how to quickly acquire information is the key to success or failure of modern wars. In the recent gulf war to iraq war, the great role played by modern radio technology in the war with high informatization degree makes people clearly recognize the importance degree of the modern radio technology in the war attack and defense, which forces the world to strive for increasing research and development on the information technology fields of radio, photoelectric reconnaissance and the like. In recent years, with the continuous development and perfection of communication systems, the required detection distance requirement is higher and higher, due to the influence of the curvature of the earth, the detection distance of the conventional ground-based radar cannot meet the reconnaissance early warning function in a large area, if the reconnaissance early warning work is carried out by a space-based early warning satellite system, the ground-based radar is high in manufacturing cost, long in construction period and unchangeable in maintenance, and is difficult to be the best choice, and the over-the-horizon radar (OTHR) can break through the limitation. The sky-wave over-the-horizon radar is a new radar which utilizes the reflection of high-frequency electromagnetic waves between an ionized layer and the ground or the diffraction mechanism along the earth surface to overcome the limitation of the curvature of the earth so as to detect targets below the horizon, the detection distance can reach thousands of kilometers, and the sky-wave over-the-horizon radar has great advantages on the detection and early warning of the targets at a long distance, which is an important reason for people to research the influence of the ionized layer on the propagation of the electric waves.

Because of the interaction between the solar ultraviolet radiation, the cosmic background rays and the like and the high-rise atmosphere, the atmospheric molecules are ionized to form a quasi-neutral plasma gathering area, under the normal condition, the ionized layer is located in the earth space with the height of 60-2000km, but the ionized layer is different from a magnetic layer in nature, and the magnetic field can completely control the movement of charged particles in the magnetic layer, so that the charged particles in a certain energy range can be captured by the geomagnetic field to form an earth radiation band at a certain position; the ionosphere is different, and the charged particles and the neutral particles collide relatively frequently, so that the magnetic field cannot completely control the movement of electrons. Under 110km, neutral wind controls the movement of the charged particles; in the range of 110km to 160km, the gyromagnetic frequency of electrons is far higher than the collision frequency of the electrons and neutral particles, and the ions are still mainly influenced by collision; above 200km, electrons and ions are gradually magnetized, and the influence of a magnetic field on charged particles becomes more and more remarkable, and the influence depends on local time, latitude and the like. Generally, in the equatorial region, the geomagnetic field is horizontal, and the lorentz force formed by the electric field and the magnetic field in the east-west direction pushes the plasma to drift upward during the day and to spread along the magnetic line to both sides of the magnetic equator at a height of about 300-. In the middle latitude area, an irregular burst E layer (Es layer) is also frequently generated, and because Es burst is formed, many characteristics of Es layer are not clear, so that the current conclusion can be reached: the Es layer is an aggregate of 'electronic cloud blocks', the electron concentration is high, different 'electronic cloud blocks' are separated by weak ionized gas, a net-shaped electric thin layer is formed, the height is within a range of 90-140km, the thickness is 1-2km, and the horizontal coverage range can reach dozens of kilometers to hundreds of kilometers. The caused ion concentration change may cause the reflection or scattering phenomenon of the ray, resulting in the change of the normal high-frequency electromagnetic wave detection range and the echo intensity. Therefore, in order to avoid the influence of the Es layer on the sky wave over-the-horizon radar detection, the occurrence of the Es layer needs to be effectively judged, and the rule and the characteristic of the Es layer need to be researched.

Normally, the dielectric constant and refractive index of the ionosphere are affected by the nonuniformity of the electron density of the ionosphere to generate random fluctuation, and when radio waves propagate in such a random environment, the propagation path and the propagation time are changed, so that the amplitude, the phase, the arrival angle and the like of signals are rapidly fluctuated, that is, ionosphere flicker is generated. Ionospheric scintillation usually reduces the resolution of radio wave systems such as radars, and in addition, ionospheric scintillation is directly related to the statistical characteristics of signal fading, channel design, ranging, accuracy of speed and angle measurement, and resolution of radar images, and from the application perspective, if the ionospheric layer generates an abnormal burst structure, the detection capability of the sky-wave radar is seriously affected, but if the abnormal burst structure is modeled, the influence caused by the abnormal burst structure is researched, so that the ionospheric scintillation is not only beneficial to human recognition, but also beneficial to solving the detection problem of the sky-wave radar, and an external invader can be detected to pass through the ionospheric layer, the ionization concentration change caused by the ionospheric layer, and then the external invader is judged and early warned.

Disclosure of Invention

The invention provides a method for detecting an ionospheric burst anomaly structure by using sky-wave radar, which is used for detecting different burst anomaly structures and comprises the following technical scheme:

a method for detecting an ionospheric burst abnormal structure by using sky-wave radar comprises the following steps:

step 1: setting ionosphere parameters, and constructing an ionosphere model by combining a multi-quasi-parabolic model according to longitude and latitude information, seasons, weather and time variables in one day of a detection area;

step 2: and according to the characteristics of different abnormal structures, establishing a geographic position, abnormal structure sizes and plasma physical process parameters, and establishing an ionosphere burst abnormal structure model.

And step 3: according to the electromagnetic wave space propagation, combining with the established ionosphere model, obtaining sky wave radar echoes, and obtaining a range-Doppler frequency spectrum of the echoes through Fourier transform;

and 4, step 4: and carrying out frequency domain energy aggregation on the obtained range-Doppler frequency spectrum of the echo in a frequency domain, and classifying and extracting the characteristics of the echo according to different burst abnormal structure characteristics.

Preferably, the step 1 specifically comprises:

the physical process in the ionized layer is divided into a photochemical process and a transportation process, and three physical quantities are determined: the yield q, in cm-3 s-1; the loss rate L (N), as a function of the electron concentration N, in cm-3 s-1; item of transportationV is net drift velocity, represents the whole movement process, and is calculated according to longitude and latitude information, season, weather and time variable in one day of the detection areaAnd (3) constructing an ionosphere model by combining a multi-quasi-parabolic model, and representing the ionosphere model by the following formula:

preferably, the step 2 specifically comprises:

step 2.1: setting up a plasma loss process, wherein the loss process is divided into the following two cases:

when β > α N, then

q＝αN²(Square law loss)

When beta < alpha N, then

q ═ β N (linear loss)

Step 2.2: the electric field is driven by neutral wind, ignoring gravitational fields, pressure gradients and electron-ion collisions, the equation of motion of charged particles in the ionosphere is expressed by:

wherein V is the drift velocity of the charged particles, U is the neutral atmospheric velocity, B is the intensity of the earth magnetic field, and V is the collision frequency of the charged particles and the neutral particles;

step 2.3: by the frequency of magnetic rotation of charged particlesThree components of the velocity V in the x, y, z directions are solved, which components are represented by:

wherein the sign of the υ component is for ions and the positive sign is for electrons;

step 2.4: calculating the diffusion speed of the plasma according to the concentration difference between the set sudden abnormal structure and the set normal condition; because the diffusion speed of electrons and ions is the same, and the kinetic energy obtained by the ions and the electrons is equal to the kinetic energy obtained by the ions and the electrons in unit time, under the action of a gravity field, a bipolar diffusion coefficient is deduced by an experimental method to be:

wherein k is Boltzmann constant, q_eFor the electron charge, T and P are the temperature and pressure in the atmosphere, K₀The mobility of the ions in the zero field, here the value of the nitrogen atom is taken to be K₀＝2.5×10^-4m²s^-1V^-1

The inverse relationship of the bipolar diffusion coefficient to the echo decay time is expressed by:

plasma level is defined as:

wherein T is_eIs the electron temperature, T_iIs the ion concentration, m is the ion mass, and g is the acceleration of gravity.

The height in the direction perpendicular to the geocentric is represented by h, an xyz coordinate system is established by taking the pointing direction of the magnetic field B as the z axis, and the height is obtained by the geometrical relationship according to the longitude and latitude of the detection position:

d＝dz sin I

the diffusion speed of the plasma in the vertical direction is represented by the following formula:

diffusion speed in the horizontal direction was obtained:

wherein N is the electron concentration, H is the neutral elevation, and has H_p＝2H。

Preferably, the step 3 specifically comprises:

step 3.1: calculating the collision frequency of free electrons by setting the electron concentration of different positions in an ionosphere model, wherein multiple particles collide in the plasma, and the collision frequency of electrons and neutral particles is calculated by the following formula:

wherein v is_emIs the collision frequency between the electrons and the gas neutrals; t is the gas temperature, n_mDetermining the derived gas particle density according to a gas state equation, wherein the gas neutral particle density is the gas neutral particle density;

the collision frequency of electrons and ions is:

wherein n is_iIs the ion density, T_eIs the electron temperature;

the collision frequency of electrons in the plasma is:

ν＝ν_em+ν_ei

step 3.2: calculating the refractive index of the ionized layer corresponding to the radar emission frequency, and obtaining the relative dielectric constant of the ionized layer according to an electronic motion equation:

wherein m is_eIs the electron mass; epsilon₀Is the dielectric constant of free space; omega is the radio wave angular frequency; will be provided with

The equation is expressed in terms of the dielectric refractive index n of the ionosphere as:

step 3.3: calculating the absorption of the ionized layer to electromagnetic wave, and if the relative dielectric constant epsilonr and conductivity sigma of the dielectric medium are known, the attenuation constant alpha is

For short wave propagation, sigma/omega epsilon > 1 is usually satisfied, then

And obtaining an echo signal in an ionized layer by means of the sea clutter, and performing Fourier transform on the echo to obtain a range-Doppler frequency spectrum of the echo signal.

Preferably, the step 4 specifically includes:

step 4.1: after the parameters such as the working frequency, the emission pulse width and the like of the antenna over-the-horizon radar are determined, the distance resolution is a fixed value, and after the radar echo is subjected to Fourier transform, a signal spectrum is represented as A (r)_i,d_j) I 1, 2.. the m is the number of range gates, j-N, -N + 1.. the N, N is the doppler frequency point, and in each range gate, the whole doppler frequency spectrum is accumulated to obtain the range frequency domain energy accumulation value at the time tk:

where p is the Doppler frequency range.

Step 4.2: in establishing the backgroundWhen noise occurs, a queue with the length of M is established in the time dimension, and the averaging processing is carried out again to obtain t_kBackground noise level estimation at time instant:

will t_kComparing the frequency domain energy value accumulated at the moment with the background noise level estimation of the same range gate, approximating the background noise level estimation to a Schweilin model, obtaining a mean value and a signal fluctuation variance, and determining a signal echo interval according to the fluctuation amount;

when the deviation exceeds an established threshold, the area is listed as a suspected target area for further feature extraction analysis, and the target detection process is shown as the following formula:

wherein H₁Expressed as the presence of a target, H, on the aggregated frequency domain₀The energy of the gathered frequency domain is only background noise, and the rest noise and clutter are represented by Z₀And (4) showing.

In the square law detector, Z is treated as a random variable, the probability density function is normally exponentially distributed, and the background noise level is estimated as being μ ═ ZB (r)_i,t_k):

When the frequency domain aggregation value contains a target, the function can be expressed as follows, and s is the signal-to-noise ratio of the target and clutter therein:

the threshold value can be selected as follows:

T＝α*Z_B(r_i,t_k)

the parameter α is for controlling the false alarm probability P_faBased on Neyman-Pearson lemma, the false alarm probability P of the optimal detector_faThe target model described as following is Swerling I:

the detection probability is represented by:

step 4.3: after a suspected target is obtained, firstly, coarse classification is carried out from the aggregation amplitude to obtain the frequency domain energy aggregation quantity on the time sequence, and then, the change on the time sequence is further subdivided, so that the discrimination accuracy is improved, and simultaneously, more target parameter characteristics are obtained.

The invention has the following beneficial effects:

the invention aims to analyze the influence of the burst abnormal structure in the ionosphere on the detection capability of the sky wave radar, so that when the burst abnormal structure occurs, the abnormal structure can be rapidly classified, and the working state of the sky wave over-the-horizon radar is adjusted or an external invader is warned according to the characteristics of different burst abnormal structures. The method mainly utilizes physical processes of various plasmas in an ionized layer to model different burst abnormal structures, and utilizes radar echoes to simulate and analyze, so that the influence of the different burst abnormal structures on the echoes is compared.

For the change of the electron concentration in the ionized layer, a model is established for the loss, drift and diffusion model of the plasma according to the real natural environment data, when the micro-element scale is divided to be small enough, the process of the change of the electron concentration in the real ionized layer can be reflected to a certain extent, when the longitude and latitude are changed, the data of the geomagnetic field, the wind speed and the like under the longitude and latitude are selected to obtain the change model of the ionized layer in the area, and the method has certain popularization.

In order to improve the accuracy of the echo in judging the change in the ionosphere, a frequency domain energy aggregation-based algorithm is provided, the obtained echo distance-Doppler frequency spectrum is subjected to weighted aggregation in each range gate and a certain time sequence, the background noise level estimation obtained by aggregation and the aggregation value at each moment are judged in a probability model, a suspected target signal is screened out, the analysis time and the complexity of the echo signal are reduced, and the false-missing probability and the detection probability are improved to a certain extent.

Two roughly classified large classes of burst abnormal structures (including an inhomogeneous type represented by a burst E layer and an external invader type represented by a rocket) are obtained by transversely comparing results in different models by combining a suspected target result obtained by gathering frequency domain energy with a burst abnormal structure model in an ionosphere. And further, longitudinal comparison is carried out on the time sequence through tracking, so that the obtained burst abnormal structure parameters are more definite.

Drawings

FIG. 1 is a diagram of a five-layer multi-quasi-parabolic model;

FIG. 2 is a diagram of a burst E-layer quasi-parabolic model;

FIG. 3 is a schematic diagram of a model of different frequencies of electromagnetic waves traversing the ionosphere;

FIG. 4 is a range-Doppler frequency spectrum of the signal processing output;

figure 5 is a doppler spectrum energy condensation graph.

Detailed Description

The present invention will be described in detail with reference to specific examples.

The first embodiment is as follows:

referring to fig. 1 to 5, the present invention provides a method for detecting an ionospheric burst anomaly structure by using sky-wave radar, comprising the following steps:

step 1: setting ionosphere parameters, and constructing an ionosphere model by combining a multi-quasi-parabolic model according to the longitude and latitude information, the season, the weather, the time in one day and other variables of a detection area.

In the ionosphereThe physical process is divided into a photochemical process and a transportation process, and can be represented by three physical quantities: rate of production q (in cm-3s-1), rate of loss L (N) (function of electron concentration N, in cm-3s-1), transport terms(V is net drift velocity) represents the entire course of motion. The equation for continuity by ionization can be expressed as:

a plasma loss process is established, and the loss process can be roughly divided into the following two cases:

1. if β > α N, then

q＝αN²(Square law loss) (2)

2. If β < α N, then

q ═ β N (linear loss) (3)

The coefficient α may be temperature dependent but may be considered highly independent. On the other hand, β varies with molecular concentration, and at larger heights, the condition β < α N can be expected to hold. For an abnormal structure, when the height of the abnormal structure is lower, the concentration of particles in the atmosphere is higher, the change of the electron concentration of the abnormal structure is mainly dominated by a loss process, and other physical processes are assisted.

Drift velocity in each direction is calculated from drift caused by electric field, neutral wind drive in the ionosphere.

Considering only the electric field and neutral wind drive, neglecting the gravitational field, pressure gradient and electron-ion collisions, the equation of motion of charged particles in the ionosphere can be simplified to the following form:

where V is the drift velocity of the charged particles, U is the neutral atmospheric velocity, B is the earth magnetic field strength, and V is the collision frequency of the charged particles with the neutral particles.

By the frequency of magnetic rotation of charged particlesThree components of the velocity V in the x, y, z directions can be solved

The sign of the υ component is for ions and the positive sign for electrons.

Mobility is mainly influenced byThe effect is that its size varies with height in the ionosphere. The motion state of the particles also differs according to the stress condition of the charged particles. The wind speed tends to increase along with the increase of the height, when the magnetic rotation frequency in the sudden abnormal structure is higher, a higher migration speed is obtained in the longitudinal direction, so that the longitudinal size of the sudden abnormal structure is changed, but in most cases, the horizontal migration speed is higher than the longitudinal migration speed, so that the sudden abnormal structure is mostly formed by flat block-shaped floccules or gathered into a plate.

And calculating the diffusion speed of the plasma according to the concentration difference between the set sudden abnormal structure and the set normal condition.

Because the diffusion speed of electrons and ions is the same, and the kinetic energy obtained by the ions and the electrons is equal to the kinetic energy obtained by the ions and the electrons in unit time, under the action of a gravity field, a bipolar diffusion coefficient is deduced by an experimental method to be:

where k is Boltzmann's constant, q_eFor the electron charge, T and P are the temperature and pressure in the atmosphere, K₀The mobility of the ions in the zero field, here the value of the nitrogen atom is taken to be K₀＝2.5×10^-4m²s^-1V^-1。

The bipolar diffusion coefficient is inversely related to the echo decay time:

plasma level is defined as:

in the formula T_eIs the electron temperature, T_iIs the ion concentration, m is the ion mass, and g is the acceleration of gravity.

The plasma is diffused in the ionized layer and is influenced by the electric field and the magnetic field, but the diffusion speed V is perpendicular to the direction of the magnetic field_⊥Much less than the diffusion velocity V parallel to the magnetic field direction_//Diffusion therefore only takes into account the projection in the direction of the magnetic field. The height in the direction perpendicular to the earth's center is expressed by (positive downward), an xyz coordinate system is established with the direction of the magnetic field B as the z-axis, d-dz sin I is obtained from the geometric relationship according to the longitude and latitude of the detection position, and

the diffusion velocity of the plasma in the vertical direction can be expressed as:

the same can be said for the diffusion velocity in the horizontal direction:

in which N is the electron concentration and H is at neutral elevation, andH_p＝2H。

when the diffusion is caused mainly by the change in electron concentration as in the case of the occurrence of sudden inhomogeneity, and in the case of the occurrence of foreign invaders, the temperature change occurs due to friction with the atmosphere, and it is also necessary to consider the influence of the temperature change. After the sudden abnormal structure occurs, a concentration difference value of one to two orders of magnitude is generated between the abnormal structure and the normal ionized layer electron concentration under the general condition, the larger the concentration difference is, the abnormal structure with different sizes can be generated along with the time diffusion, and when the abnormal structure is positioned in the atmosphere with different heights, the longitudinal size can be changed to a certain extent due to the change of the atmospheric temperature. This is also the predominant form of ionospheric interlayer to higher layer motion.

And step 3: and calculating the collision frequency of free electrons by setting the electron concentration of different positions in the ionosphere model. There are many particle collisions in the plasma, among which collisions between electrons and neutral particles, and between electrons and particles, dominate. The calculated formula for the collision frequency of electrons and neutral particles is:

in the formula, v_emIs the collision frequency (Hz) between electrons and gas neutrals; t is the gas temperature (K); n is_mIs gas neutral particle density (1/cm)³) The gas particle density can be derived from the gas equation of state.

The collision frequency of electrons and ions is:

in the formula, n_iIs the ion density, T_eIs the electron temperature.

The collision frequency of electrons in the plasma is:

ν＝ν_em+ν_ei (14)

calculating the refractive index of the ionized layer corresponding to the radar transmitting frequency, and obtaining the relative dielectric constant of the ionized layer according to an electronic motion equation:

in the formula m_eIs the electron mass; epsilon₀Is the dielectric constant of free space; ω is the radio wave angular frequency. The equation is expressed as the ionospheric medium refractive index n:

the absorption of the ionized layer to electromagnetic wave is calculated, and the calculation of non-offset absorption can be carried out according to a calculation formula related to plane wave attenuation in a lossy medium in an electromagnetic field theory. Given that the relative permittivity er and the conductivity σ of the lossy medium are known, the attenuation constant α is

For short wave propagation, sigma/omega epsilon > 1 is usually satisfied, then

By means of the sea clutter, an echo signal of the ionosphere is obtained in this case, and the echo is subjected to a fourier transformation, resulting in a range-doppler frequency spectrum of the echo signal.

And 4, step 4: after the parameters such as the working frequency, the emission pulse width and the like of the antenna over-the-horizon radar are determined, the distance resolution is also a fixed value. After Fourier transform for radar echo, the signal spectrum can be represented as A (r)_i,d_j) I is 1, 2.. times, m (m is the number of range gates), j is-N, -N + 1.. times, N (N is the doppler frequency point). And accumulating the whole Doppler frequency spectrum in each range gate to obtain a range frequency domain energy accumulation value at the time tk.

p is the Doppler frequency range.

In order to increase the robustness of the algorithm, the ionosphere is a model which changes along with time, and can be used as a fixed parameter in short-time detection, but the estimation of the background noise also needs to change along with the time in the long-time detection process. So as to eliminate the fluctuation caused by weather, time change or special extreme condition to the establishment of background noise, when the background noise is established, the queue with the length of M is established on the time dimension, and the averaging processing is carried out again to obtain t_kBackground noise level estimation of time instants.

Will t_kComparing the frequency domain energy value accumulated at the moment with the background noise level estimation of the same range gate, approximating the background noise level estimation to a Schweilin model, obtaining the mean value and the signal fluctuation variance, and determining the signal echo interval according to the fluctuation quantity. Since the change of the electron concentration in the ionosphere causes the change of the detection distance, the increase or decrease of the energy accumulation value occurs at a certain distance gate, and even the change of the detection distance occurs. When the deviation exceeds an established threshold, the area is classified as a suspected target area for further feature extraction analysis.

The target detection process is shown as follows:

H₁expressed as the presence of a target, H, on the aggregated frequency domain₀The energy of the gathered frequency domain is only background noise, and the rest noise and clutter are represented by Z₀And (4) showing.

Detection at square lawIn this case, Z can be treated as a random variable, normally with an exponential probability density function, and the background noise level is estimated as μ ═ ZB (r)_i,t_k):

If the frequency domain aggregation value contains a target, the function can be expressed as follows, and s is the signal-to-noise ratio of the target and clutter therein:

the threshold value can be selected as follows:

T＝α*Z_B(r_i,t_k) (24)

the parameter α is for controlling the false alarm probability P_faThe scaling factor of (c). False alarm probability P of optimal detector based on Neyman-Pearson lemma_faThe target model that can be described as following is Swerling I:

the detection probability is:

after a suspected target is obtained, the aggregation amplitude can be roughly classified once, but target information characteristics are difficult to obtain from the suspected target through classification judgment once, so that after the suspected target is found, the sky-wave beyond visual range radar can continuously monitor and track the area to obtain frequency domain energy aggregation quantity on a time sequence, and then the change on the time sequence is further subdivided, so that the judgment accuracy is improved, and meanwhile, more target parameter characteristics are obtained.

The above description is only a preferred embodiment of the method for detecting the ionospheric burst anomaly structure by using the sky-wave radar, and the protection range of the method for detecting the ionospheric burst anomaly structure by using the sky-wave radar is not limited to the above embodiments, and all technical solutions belonging to the idea belong to the protection range of the present invention. It should be noted that modifications and variations which do not depart from the gist of the invention will be those skilled in the art to which the invention pertains and which are intended to be within the scope of the invention.