CN107302387A - A kind of high-speed aircraft relays dual polarization mimo channel modeling method - Google Patents

Abstract

The invention belongs to TTC＆T Technology field, a kind of high-speed aircraft relaying dual polarization mimo channel modeling method is disclosed, including：Loo channel parameters are determined using plasma sheath Markov state metastasis model；The large scale fading model and multipath fading model for the repeater satellite subchannel set up using Loo models under every plasma sheath, subchannel produce polarization dependence by dual polarization MIMO model；Large scale decline and multipath fading part of the joint per subchannel obtain the polarization mimo channel model under plasma sheath.The present invention, which is adopted, greatly reduces space and launch cost；Consider influence of the dual polarization asymmetry to channel model under plasma sheath.

Description

A high-speed aircraft relay dual-polarization MIMO channel modeling method

technical field

The invention belongs to the technical field of measurement and control communication, and in particular relates to a high-speed aircraft relay dual-polarization MIMO channel modeling method.

Background technique

With the rapid development of aerospace technology, the development and utilization of hypersonic vehicles has become a research hotspot in the aerospace field at home and abroad. When a high-speed aircraft flies at a speed greater than Mach 10, the plasma sheath around the aircraft will seriously attenuate and distort the signal, which will greatly reduce the channel capacity and cause communication interruption (black barrier), which greatly threatens the flight safety of the aircraft. In order to overcome or alleviate the problem of black barrier communication interruption, researchers have proposed many physical and chemical plasma suppression methods to improve the possibility of communication. These measures can theoretically reduce the attenuation to a certain extent, but they are almost impossible to apply in practical situations. For communication, the current communication research on high-speed aircraft is all about downlink "end-to-end" communication, which is a single-input and single-output transmission channel, and the channel capacity is relatively small. Using uplink relay and diversity transmission is an important means to increase channel capacity and improve communication quality. In fact, the use of polarization diversity can generate two independent orthogonal sub-channels in the polarization direction. It only needs a single relay satellite and a single aircraft to form a MIMO system, which can greatly reduce the system complexity. Satellite application of dual-polarized MIMO technology is relatively mature, document "Konstantinos P.Liolis, Jesús Gómez-Vilardebó, Enrico Casini, Ana I.Pérez-Neira. Statistical Modeling of Dual-Polarized MIMO Land Mobile Satellite Channels[J].IEEE Transactions on Communications,2010,58(11):3077-3083"gives a dual-polarization MIMO channel model for land mobile satellites, but there is a special plasma sheath environment in high-speed aircraft, which leads to the application of dual-polarization under the plasma sheath The polarization MIMO technology has the following problems: (1) In the satellite dual-polarization MIMO system, the polarization is generally considered to be symmetric, but the polarization asymmetry needs to be considered in the design of the dual-polarization MIMO channel model under the plasma sheath, so that the The large-scale and small-scale effects of MIMO subchannels are different. (2) The plasma sheath will affect the large-scale fading and small-scale fading characteristics of the channel, and the plasma sheath environment will affect the independence of the polarization transmission channel, that is, it will change the correlation between the dual-polarization MIMO sub-channels The independence of the sub-channels is destroyed, which needs to be considered in the modeling process. Aiming at the reliability problem of black barrier communication of high-speed aircraft, oriented to the research of uplink relay dual-polarization transmission method, a high-speed aircraft relay dual-polarization MIMO channel modeling method is proposed, which can provide reference for relay diversity communication evaluation and system design.

To sum up, the problems existing in the existing technology are: the current MIMO channel model has dual-polarization MIMO channel model design under the plasma sheath. It is necessary to consider polarization asymmetry, which affects the large-scale fading and small-scale fading characteristics of the channel. .

Contents of the invention

Aiming at the problems existing in the prior art, the present invention provides a high-speed aircraft relay dual-polarization MIMO channel modeling method.

The present invention is achieved in this way, a high-speed aircraft relay dual-polarization MIMO channel modeling method, the high-speed aircraft relay dual-polarization MIMO channel modeling method includes the following steps:

Step 1, using the plasma sheath Markov state transition model to determine Loo channel parameters;

Step 2, using the Loo model to establish a large-scale fading model and a small-scale fading model of the sub-channel of the relay satellite under each plasma sheath, and the sub-channel generates polarization correlation through a dual-polarization MIMO model;

Step three, combine the large-scale fading and small-scale fading parts of each sub-channel to obtain the polarization MIMO channel model under the plasma sheath.

Further, the high-speed aircraft relay dual-polarization MIMO channel modeling method includes the following steps:

The first step is to obtain the transition sequence of the Markov channel model according to the land mobile satellite Markov channel state transition matrix P; determine the corresponding Loo model channel parameters of the state sequence according to the land mobile satellite channel test results;

In the second step, according to the electron density and collision frequency of the plasma sheath of the high-speed aircraft, calculate and obtain the left-handed circularly polarized plasma environment polarization coupling degree parameter XPC _env,L and the right-handed circularly polarized plasma environment polarization coupling degree parameter and xpc _env,R ;

The third step is to use the Loo model channel parameters and parameters XPC _env,L and XPC _env,R to realize large-scale channel model simulation;

The fourth step is to realize small-scale channel model simulation by using the channel parameters and the parameters XPC _env,L and XPC _env,R of step S2;

In the fifth step, the polarization MIMO channel model under the plasma sheath is obtained by combining the large-scale fading component and the small-scale fading component.

Further, the first step specifically includes:

(1) Input the plasma sheath Markov state transition matrix P, the element P(i,j) in the state transition matrix P represents the probability of jumping from state i to state j, 0≤P(i,j)≤1 and n means that the model simulates n states.

(2) Input the state frame L _Frame , and L _Frame represents the minimum distance that a certain state lasts. Given the current state S _t , generate the next state S _t+1 every L _Frame meters

The first step is to generate a (0, 1) uniformly distributed random number U, and set k=1;

The second step, test conditions If the test condition is met, then the next state S _t+1 =k; if the test condition is not met, then k=k+1 and repeat the second step until the condition is met;

(3) The aircraft moves along its path, and judges the state of the terminal every L _Frame meters, and finds the Loo model parameters Loo(α,ψ,MP) in the corresponding state, and the Loo model parameters corresponding to the good state (-1.1045 ,1.3149,-16.8763), Loo model parameters corresponding to the bad state (-13.6829,5.0213,-22.3256); α, ψ and MP are expressed in dB, where α, ψ represent the mean and variance of the magnitude of large-scale fading, respectively, MP represents the average energy of the magnitude of small-scale fading.

Further, the second step specifically includes:

1) According to the electron density and collision frequency of the high-speed aircraft, for the plasma sheath at the antenna window of the aircraft, the electron density distribution curve is approximated by a double Gaussian model:

Among them, a ₁ and a ₂ respectively represent the rising and falling coefficients of the electron density distribution curve, Ne _peak and z ₀ represent the maximum value of the electron density and the distance from the surface of the aircraft, respectively;

2) Calculate the transmitted wave after the circularly polarized wave obliquely incident on the plasma according to the equivalent wave impedance method:

in, with denote the parallel-polarized and vertical-polarized unit direction vectors, respectively. with are the parallel and vertical polarization components decomposed into the incident wave, respectively, with are the parallel and vertical polarization components decomposed into the transmitted wave, respectively; with are the transmission coefficients of parallel polarized waves and vertical polarized waves, respectively;

3) Decompose the transmitted wave after the circularly polarized wave enters the plasma into right-handed circular transmitted waves and the transmitted wave of the left-handed circle

where _E0 is the normalized field strength, with are the transmission coefficients of the transmitted co-polarized and cross-polarized waves, respectively, after the right-handed wave is incident, with are the transmission coefficients of the transmitted co-polarized and cross-polarized waves after the incident left-handed wave, respectively;

4) Put the transmission coefficients of the co-polarized and cross-polarized waves of the transmitted waves after the left/right-handed waves are incident into the following formula to obtain the parameters XPC _env,L and XPC _env,R :

Further, the third step specifically includes:

Step 1, for each state, generate a 2×2 statistically independent Gaussian random sequence sample matrix with mean 0 and variance 1 The sampling interval of the samples is T. After sample matrix Each element is passed through a low-pass IIR filter to realize the time correlation of the signal, and a 2×2 matrix with time correlation is obtained

Step 2, input the correlation matrix of the large-scale fading component and will into the following formula, using the correlation matrix Generate polarization correlation between MIMO sub-channels, and obtain a polarization-related 2×2 channel matrix

vec() means to take column vector operation.

Step 3, according to the lognormal distribution of the amplitude of large-scale fading, input the channel parameters α and ψ of the Loo model, and set Substituting into the following formula, the channel characteristic matrix of polarization-related log-normal distribution is generated

Step 4: According to the influence of polarization on channel sequence power, input the polarization discrimination degree XPD _ant,r of the polarized antenna located on the high-speed aircraft, and use the following formula to adjust the large-scale fading matrix

where β _ant is a factor of XPD _ant,r ,

Further, the fourth step specifically includes:

1) For each state, generate a 2×2 statistically independent complex Gaussian random sequence sample matrix with a mean of 0 and a variance of 1

2) In order to introduce the Doppler frequency shift effect, the 2×2 complex Gaussian random sequence matrix Each element is implemented through a Butterworth filter, resulting in a complex Gaussian random sequence matrix with Doppler effect The Butterworth filter is expressed as:

Wherein, A=exp(-vT/r _c ), v is the flight speed of the aircraft, T is the sampling interval, r _c is the coherent distance, and f _c is the cut-off frequency of the k-order filter;

3) According to the fact that the magnitude of small-scale fading obeys the Rayleigh distribution, in order to generate a 2×2 complex Rayleigh sequence, input the Loo model channel parameter MP, and the complex Gaussian sequence matrix multiply each element by to generate the Rayleigh 2×2 matrix in

4) Input the correlation matrix of the small-scale fading component and will into the following formula, using the correlation matrix Generate the polarization correlation between MIMO sub-channels, and obtain the polarization-related channel characteristic 2×2 matrix

in, Represents the Kronecker product, the superscript T represents the matrix transpose, with Represent the 2×2 covariance matrix of the sending end and the receiving end respectively;

in, with Denote the cross-correlation of left-handed circular polarization and right-handed circular polarization of the transmitting terminal, respectively; with Denote the cross-correlation of left-handed circular polarization and right-handed circular polarization at the receiving end, respectively;

5) According to the influence of polarization on channel sequence power, input the environmental coupling degree XPC _env,L , XPC _env,R and the polarization discrimination degree XPD _ant,r of the polarized antenna located on the high-speed aircraft, and use the following formula to adjust the large-scale fading matrix

in with

Another object of the present invention is to provide a high-speed aircraft using the high-speed aircraft relay dual-polarization MIMO channel modeling method.

The advantages and positive effects of the present invention are: adopting the multi-state Markov chain to model the channel can better describe the actual channel, avoiding the limitation that a single random process cannot accurately describe the channel characteristics. Based on the uplink dual-polarization transmission of relay satellites and high-speed aircraft, compared with the existing "end-to-end" aircraft wireless transmission channel research, only one relay satellite and high-speed aircraft can realize the MIMO system. Compared with the multi-satellite MIMO system, the antenna system can greatly reduce the complexity of system implementation;

The polarization MIMO channel model modeling method under the plasma sheath provided by the present invention, compared with the polarization symmetry of the existing land mobile satellite dual-polarization MIMO channel model, considers the dual polarization under the plasma sheath The influence of asymmetry on the channel model can accurately describe the large-scale and small-scale fading characteristics in the high-speed aircraft plasma sheath environment, as well as the correlation between polarimetric sub-channels.

The present invention is applicable to the dual-polarization MIMO channel modeling of the high-speed aircraft relay satellite near space, and also applicable to the dual-polarization MIMO channel modeling of the aerospace re-entry aircraft relay satellite. The established channel model can be used for the design of the high-speed aircraft communication system , Adaptive method research provides channel simulation foundation and platform, which can be used for algorithm design and performance evaluation of communication physical layer transmission technologies such as modulation/demodulation, channel coding, channel estimation and equalization.

Description of drawings

Fig. 1 is a flowchart of a high-speed aircraft relay dual-polarization MIMO channel modeling method provided by an embodiment of the present invention.

Fig. 2 is a flow chart of a specific implementation of a method for modeling and simulating a high-speed aircraft relay dual-polarization MIMO channel provided by an embodiment of the present invention.

Fig. 3 is a flowchart for realizing large-scale fading under a plasma sheath provided by an embodiment of the present invention.

Fig. 4 is a flow chart of implementing small-scale fading under a plasma sheath provided by an embodiment of the present invention.

Fig. 5 is a schematic diagram comparing the influence of the dual-polarization MIMO technology under the plasma sheath and that without the dual-polarization MIMO technology on the channel capacity under certain conditions provided by the embodiment of the present invention.

Fig. 6 is a schematic diagram comparing the effects on the bit error rate of using the dual-polarization MIMO technology and not using the dual-polarization MIMO technology under the plasma sheath under certain conditions provided by the embodiment of the present invention.

detailed description

In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

The application principle of the present invention will be described in detail below in conjunction with the accompanying drawings.

As shown in Figure 1, the high-speed aircraft relay dual-polarization MIMO channel modeling method provided by the embodiment of the present invention includes the following steps:

S101: Using the plasma sheath Markov state transition model to determine Loo channel parameters;

S102: Using the Loo model to establish a large-scale fading model and a small-scale fading model of the sub-channels of the relay satellite under each plasma sheath, these sub-channels undergo a dual-polarization MIMO model to generate polarization correlation;

S103: Combine the large-scale fading and small-scale fading parts of each sub-channel to obtain a polarization MIMO channel model under the plasma sheath.

The application principle of the present invention will be further described below in conjunction with the accompanying drawings.

As shown in Figure 2, the high-speed aircraft relay dual-polarization MIMO channel modeling method of the embodiment of the present invention includes the following steps:

S1 obtains the transition sequence of the Markov channel model according to the land mobile satellite Markov channel state transition matrix P; determines the corresponding Loo model channel parameters of the state sequence according to the land mobile satellite channel test results.

S1.1: Input plasma sheath Markov state transition matrix The element P(i,j) in the state transition matrix P represents the probability of jumping from state i to state j, 0≤P(i,j)≤1 and n means that the model simulates n states. According to the measured data of MiLADY, the integrated channel environment in the near space can be modeled as a two-state Markov process, which is a good state and a bad state, so n=2;

S1.2: Input transition frame L _Frame =5, L _Frame represents the minimum distance for a certain state to last. Given the current state S _t , generate the next state S _t+1 every L _Frame :

The first step is to generate a (0, 1) uniformly distributed random number U, and set k=1;

The second step, test conditions If the test condition is met, then the next state S _t+1 =k; if the test condition is not met, then k=k+1 and repeat the second step until the condition is met;

S1.3: The aircraft moves along its path, judge the state of the terminal every L _Frame meters, and find the Loo model parameters Loo(α,ψ,MP) in the corresponding state, and the Loo model parameters corresponding to the good state (- 1.1045,1.3149,-16.8763), Loo model parameters corresponding to the bad state (-13.6829,5.0213,-22.3256); α, ψ and MP are expressed in dB, where α, ψ represent the mean and variance of the amplitude of large-scale fading respectively , MP represents the average energy of the magnitude of the small-scale fading.

S2 According to the high-speed aircraft plasma sheath electron density and collision frequency, calculate and obtain the left-handed circularly polarized plasma environment polarization coupling degree parameter XPC _env,L and the right-handed circularly polarized plasma environment polarization coupling degree parameter XPC _env ,L _R.

S2.1: According to the electron density and collision frequency of the high-speed aircraft, for the plasma sheath at the antenna window of the aircraft, the electron density distribution curve can be approximated by a double Gaussian model:

Among them, a ₁ and a ₂ represent the rising and falling coefficients of the electron density distribution curve, Ne _peak and z ₀ represent the maximum value of the electron density and the distance from the surface of the aircraft, respectively.

S2.2: Calculate the transmitted wave after the circularly polarized wave obliquely incident on the plasma according to the equivalent wave impedance method:

in, with denote the parallel-polarized and vertical-polarized unit direction vectors, respectively. with are the parallel and vertical polarization components decomposed into the incident wave, respectively, with are the parallel and vertical polarization components decomposed into the transmitted wave, respectively. with are the transmission coefficients of parallel polarized waves and vertical polarized waves, respectively;

S2.3: According to the circularly polarized wave incident on the plasma, the transmitted wave can be decomposed into the transmitted wave of the right-handed circle (RHCP) and the transmitted wave of the left-handed circle (LHCP)

where _E0 is the normalized field strength, with are the transmission coefficients of the transmitted co-polarized and cross-polarized waves, respectively, after the right-handed wave is incident, with are the transmission coefficients of the co-polarized and cross-polarized waves after the incident left-handed wave, respectively

S2.4: Put the transmission coefficients of the co-polarized and cross-polarized waves of the transmitted waves after the incident left/right-handed waves into the following formula to obtain the parameters XPC _env,L and XPC _env,R :

S3 uses the channel parameters of the Loo model in step S1 and the parameters XPC _env,L and XPC _env,R in step S2 to realize large-scale channel model simulation, as shown in FIG. 3 .

S3.1: For each state, generate a 2×2 statistically independent Gaussian random sequence sample matrix with mean 0 and variance 1 The sampling interval of the samples is T=1.2273×10 ^-3 . After sample matrix Each element is passed through a low-pass IIR filter to realize the time correlation of the signal, and a 2×2 matrix with time correlation is obtained

S3.2: Enter the correlation matrix of the large-scale fading component and will into the following formula, using the correlation matrix Generate the polarization correlation between MIMO sub-channels, and obtain the polarization-related channel characteristic 2×2 matrix

S3.3: According to the lognormal distribution of the magnitude of large-scale fading, input the channel parameters α and ψ of the Loo model, and set Substituting into the following formula, the channel characteristic matrix of polarization-related log-normal distribution is generated

S3.4: According to the influence of polarization on channel sequence power, input the polarization discrimination degree XPD _ant,r = 15dB of the polarized antenna located on the high-speed aircraft, and use the following formula to adjust the large-scale fading matrix

where β _ant is a factor of XPD _ant,r ,

S4 utilizes the channel parameters in step S1 and the parameters XPC _env,L and XPC _env,R in step S2 to realize small-scale channel model simulation, as shown in FIG. 4 .

S4.1: For each state, generate a 2×2 statistically independent complex Gaussian random sequence sample matrix with mean 0 and variance 1

S4.2: In order to introduce the Doppler shift effect, the 2×2 complex Gaussian random sequence matrix Each element is implemented through a Butterworth filter, resulting in a complex Gaussian random sequence matrix with Doppler effect Butterworth filter can be expressed as:

Among them, A=exp(-vT/r _c ), the flight speed of the aircraft v=4080m/s, the sampling interval T=1.2273×10- ³ , the coherent distance r _c =2m, and f _c is the cut-off of the k-order filter Frequency, Butterworth filter: attenuation 3dB: 0.9×ν/λ, attenuation 100dB: 3×ν/λ;

S4.3: According to the fact that the magnitude of small-scale fading obeys the Rayleigh distribution, in order to generate a 2×2 complex Rayleigh sequence, input the Loo model channel parameter MP, and the complex Gaussian sequence matrix multiply each element by to generate the Rayleigh 2×2 matrix in

S4.4: Input correlation matrix of small-scale fading components and will into the following formula, using the correlation matrix Generate the polarization correlation between MIMO sub-channels, and obtain the polarization-related channel characteristic 2×2 matrix

S4.5: According to the influence of polarization on the channel sequence power, input the environmental coupling degree XPC _env,L , XPC _env,R and the polarization discrimination degree XPD _ant,r of the polarized antenna located on the high-speed aircraft, and use the following formula to adjust the large scale fading matrix

in with

It should be further noted that in step S4.4, the correlation matrix of small-scale components needs to be obtained

in, Represents the Kronecker product, the superscript T represents the matrix transpose, with Represent the 2×2 covariance matrix of the sending end and the receiving end respectively:

in, with Denote the cross-correlation of left-handed circular polarization and right-handed circular polarization of the transmitting terminal, respectively; with Denote the cross-correlation of left-handed circular polarization and right-handed circular polarization at the receiving end, respectively;

The concrete implementation of step S5 is as follows:

The large-scale fading component of step S3 and the small-scale fading component of step S4 are combined to obtain a polarized MIMO channel model under the plasma sheath.

It can be seen from Figure 5 that the channel capacity of the near-space high-speed vehicle relay satellite dual-polarization MIMO system and the SISO system increases with the increase of the signal-to-noise ratio, but the channel capacity of the near-space high-speed vehicle relay satellite dual-polarization MIMO system The capacity is significantly higher than that of the SISO system. For example, when the signal-to-noise ratio is 20dB, the channel capacity of the near-space high-speed aircraft relay satellite dual-polarization MIMO system is 5.708bps/Hz, while the channel capacity of the near-space high-speed aircraft relay satellite SISO system is 2.517bps/Hz. It can be seen from Fig. 6 that the BER of the near-space high-speed aircraft relay satellite dual-polarization MIMO system and the SISO system decrease with the increase of SNR, but the near-space high-speed aircraft relay satellite dual-polarization MIMO The bit error rate of the system is obviously lower than that of the SISO system. For example, when the signal-to-noise ratio is 14dB, the bit error rate of the near-space high-speed aircraft relay satellite dual-polarization MIMO system is 0.0257, while that of the near-space high-speed aircraft relay satellite SISO system is 0.2319. Therefore, adopting the dual-polarization MIMO technology on the near-space high-speed aircraft and the relay satellite can greatly increase the channel capacity and improve the bit error rate, which illustrates the effectiveness of the present invention.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention should be included in the protection of the present invention. within range.

Claims (7)

1. A high-speed aircraft relay dual-polarization MIMO channel modeling method is characterized in that, the high-speed aircraft relay dual-polarization MIMO channel modeling method comprises the following steps: Step 1, using the plasma sheath Markov state transition model to determine Loo channel parameters; Step 2, using the Loo model to establish a large-scale fading model and a small-scale fading model of the sub-channel of the relay satellite under each plasma sheath, and the sub-channel generates polarization correlation through a dual-polarization MIMO model; Step 3, combine the large-scale fading and small-scale fading parts of each sub-channel to obtain the polarization MIMO channel model under the plasma sheath. 2. the high-speed aircraft relay dual-polarization MIMO channel modeling method as claimed in claim 1, is characterized in that, described high-speed aircraft relay dual-polarization MIMO channel modeling method comprises the following steps: The first step is to obtain the transition sequence of the Markov channel model according to the land mobile satellite Markov channel state transition matrix P; determine the corresponding Loo model channel parameters of the state sequence according to the land mobile satellite channel test results; In the second step, according to the electron density and collision frequency of the plasma sheath of the high-speed aircraft, calculate and obtain the left-handed circularly polarized plasma environment polarization coupling degree parameter XPC _env,L and the right-handed circularly polarized plasma environment polarization coupling degree parameter and xpc _env,R ; The third step is to use the Loo model channel parameters and parameters XPC _env,L and XPC _env,R to realize large-scale channel model simulation; The fourth step is to realize small-scale channel model simulation by using the channel parameters and the parameters XPC _env,L and XPC _env,R of step S2; In the fifth step, the polarization MIMO channel model under the plasma sheath is obtained by combining the large-scale fading component and the small-scale fading component. 3. the high-speed aircraft relay dual-polarization MIMO channel modeling method as claimed in claim 2, is characterized in that, described first step specifically comprises: (1) Input the plasma sheath Markov state transition matrix P, the element P(i,j) in the state transition matrix P represents the probability of jumping from state i to state j, 0≤P(i,j)≤1 and n indicates that the model simulates n states; (2) Input the state frame L _Frame , L _Frame represents the minimum distance for a certain state; given the current state S _t , generate the next state S _t+1 every L _Frame meter The first step is to generate a (0, 1) uniformly distributed random number U, and set k=1; The second step, test conditions If the test condition is met, then the next state S _t+1 =k; if the test condition is not met, then k=k+1 and repeat the second step until the condition is met; (3) The aircraft moves along its path, judge the state of the terminal every L _Frame meters, and find the Loo model parameters Loo(α,ψ,MP) in the corresponding state; α, ψ and MP are expressed in dB, Among them, α and ψ represent the mean and variance of the magnitude of the large-scale fading, respectively, and MP represents the average energy of the magnitude of the small-scale fading. 4. the high-speed aircraft relay dual-polarization MIMO channel modeling method as claimed in claim 2, is characterized in that, described second step specifically comprises: 1) According to the electron density and collision frequency of the high-speed aircraft, for the plasma sheath at the antenna window of the aircraft, the electron density distribution curve is approximated by a double Gaussian model: <mrow><mi>N</mi><mi>e</mi><mrow><mo>(</mo><mi>z</mi><mo>)</mo></mrow><mo>=</mo><mfenced open = "{" close = ""><mtable><mtr><mtd><mrow><msub><mi>Ne</mi><mrow><mi>p</mi><mi>e</mi><mi>a</mi><mi>k</mi></mrow></msub><mi>exp</mi><mo>&amp;lsqb;</mo><mo>-</mo><msub><mi>a</mi><mn>1</mn></msub><msup><mrow><mo>(</mo><mi>z</mi><mo>-</mo><msub><mi>z</mi><mn>0</mn></msub><mo>)</mo></mrow><mn>2</mn></msup><mo>&amp;rsqb;</mo></mrow></mtd><mtd><mrow><mo>(</mo><mn>0</mn><mo>&amp;le;</mo><mi>z</mi><mo>&lt;</mo><msub><mi>z</mi><mn>0</mn></msub><mo>)</mo></mrow></mtd></mtr><mtr><mtd><mrow><msub><mi>Ne</mi><mrow><mi>p</mi><mi>e</mi><mi>a</mi><mi>k</mi></mrow></msub><mi>exp</mi><mo>&amp;lsqb;</mo><mo>-</mo><msub><mi>a</mi><mn>2</mn></msub><msup><mrow><mo>(</mo><mi>z</mi><mo>-</mo><msub><mi>z</mi><mn>0</mn></msub><mo>)</mo></mrow><mn>2</mn></msup><mo>&amp;rsqb;</mo></mrow></mtd><mtd><mrow><mo>(</mo><mi>z</mi><mo>&amp;GreaterEqual;</mo><msub><mi>z</mi><mn>0</mn></msub><mo>)</mo></mrow></mtd></mtr></mtable></mfenced><mo>;</mo></mrow> Among them, a ₁ and a ₂ respectively represent the rising and falling coefficients of the electron density distribution curve, Ne _peak and z ₀ represent the maximum value of the electron density and the distance from the surface of the aircraft, respectively; 2) Calculate the transmitted wave after the circularly polarized wave obliquely incident on the plasma according to the equivalent wave impedance method: <mrow><msup><mover><mi>E</mi><mo>&amp;RightArrow;</mo></mover><mi>t</mi></msup><mo>=</mo><msubsup><mi>E</mi><mrow><mo>|</mo><mo>|</mo></mrow><mi>t</mi></msubsup><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><mo>+</mo><msubsup><mi>E</mi><mo>&amp;perp;</mo><mi>t</mi></msubsup><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>=</mo><msubsup><mi>E</mi><mrow><mo>|</mo><mo>|</mo></mrow><mi>i</mi></msubsup><msub><mover><mi>T</mi><mo>~</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><mo>+</mo><msubsup><mi>E</mi><mo>&amp;perp;</mo><mi>i</mi></msubsup><msub><mover><mi>T</mi><mo>~</mo></mover><mo>&amp;perp;</mo></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>;</mo></mrow> in, with denote the parallel polarization and vertical polarization unit direction vectors, respectively; with are the parallel and vertical polarization components decomposed into the incident wave, respectively, with are the parallel and vertical polarization components decomposed into the transmitted wave, respectively; with are the transmission coefficients of parallel polarized waves and vertical polarized waves, respectively; 3) Decompose the transmitted wave after the circularly polarized wave enters the plasma into right-handed circular transmitted waves and the transmitted wave of the left-handed circle <mrow><msubsup><mover><mi>E</mi><mo>&amp;RightArrow;</mo></mover><mi>R</mi><mi>t</mi></msubsup><mo>=</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>T</mi><mo>~</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><mo>+</mo><msub><mi>jE</mi><mn>0</mn></msub><msub><mover><mi>T</mi><mo>~</mo></mover><mo>&amp;perp;</mo></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>=</mo><msubsup><mi>T</mi><mi>R</mi><mrow><mi>c</mi><mi>o</mi></mrow></msubsup><mrow><mo>(</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>+</mo><mi>j</mi><mo>&amp;CenterDot;</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><mo>)</mo></mrow><mo>+</mo><msubsup><mi>T</mi><mi>R</mi><mrow><mi>c</mi><mi>r</mi><mi>o</mi><mi>s</mi><mi>s</mi></mrow></msubsup><mrow><mo>(</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>-</mo><mi>j</mi><mo>&amp;CenterDot;</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><mo>)</mo></mrow><mo>;</mo></mrow> <mrow><msubsup><mover><mi>E</mi><mo>&amp;RightArrow;</mo></mover><mi>L</mi><mi>t</mi></msubsup><mo>=</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>T</mi><mo>~</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><mo>-</mo><msub><mi>jE</mi><mn>0</mn></msub><msub><mover><mi>T</mi><mo>~</mo></mover><mo>&amp;perp;</mo></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>=</mo><msubsup><mi>T</mi><mi>L</mi><mrow><mi>c</mi><mi>r</mi><mi>o</mi><mi>s</mi><mi>s</mi></mrow></msubsup><mrow><mo>(</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>+</mo><mi>j</mi><mo>&amp;CenterDot;</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</mo></mrow></msub><mo>)</mo></mrow><mo>+</mo><msubsup><mi>T</mi><mi>L</mi><mrow><mi>c</mi><mi>o</mi></mrow></msubsup><mrow><mo>(</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mo>&amp;perp;</mo></msub><mo>-</mo><mi>j</mi><mo>&amp;CenterDot;</mo><msub><mi>E</mi><mn>0</mn></msub><msub><mover><mi>v</mi><mo>&amp;RightArrow;</mo></mover><mrow><mo>|</mo><mo>|</msubmo></mrow></msub><mo>)</mo></mrow><mo>;</mo></mrow> where _E0 is the normalized field strength, with are the transmission coefficients of the transmitted co-polarized and cross-polarized waves, respectively, after the right-handed wave is incident, with are the transmission coefficients of the transmitted co-polarized and cross-polarized waves after the incident left-handed wave, respectively; 4) Put the transmission coefficients of the co-polarized and cross-polarized waves of the transmitted waves after the left/right-handed waves are incident into the following formula to obtain the parameters XPC _env,L and XPC _env,R : <mrow><msub><mi>XPC</mi><mrow><mi>e</mi><mi>n</mi><mi>v</mi><mo>,</mo><mi>L</mi></mrow></msub><mo>=</mo><msubsup><mi>T</mi><mi>L</mi><mrow><mi>c</mi><mi>o</mi></mrow></msubsup><mo>/</mo><msubsup><mi>T</mi><mi>L</mi><mrow><mi>c</mi><mi>r</mi><mi>o</mi><mi>s</mi><mi>s</mi></mrow></msubsup><mo>;</mo></mrow> <mrow><msub><mi>XPC</mi><mrow><mi>e</mi><mi>n</mi><mi>v</mi><mo>,</mo><mi>R</mi></mrow></msub><mo>=</mo><msubsup><mi>T</mi><mi>R</mi><mrow><mi>c</mi><mi>o</mi></mrow></msubsup><mo>/</mo><msubsup><mi>T</mi><mi>R</mi><mrow><mi>c</mi><mi>r</mi><mi>o</mi><mi>s</mi><mi>s</mi></mrow></msubsup><mo>.</mo></mrow> 5. the high-speed aircraft relay dual-polarization MIMO channel modeling method as claimed in claim 2, is characterized in that, described 3rd step specifically comprises: Step 1, for each state, generate a 2×2 statistically independent Gaussian random sequence sample matrix with mean 0 and variance 1 The sampling interval of the sample is T; after that, the sample matrix Each element is passed through a low-pass IIR filter to realize the time correlation of the signal, and a 2×2 matrix with time correlation is obtained Step 2, input the correlation matrix of the large-scale fading component and will into the following formula, using the correlation matrix Generate polarization correlation between MIMO sub-channels, and obtain a polarization-related 2×2 channel matrix <mrow><mi>v</mi><mi>e</mi><mi>c</mi><mrow><mo>(</mo><msub><mover><mi>H</mi><mo>&amp;OverBar;</mo></mover><mrow><mi>c</mi><mi>o</mi><mi>r</mi><mi>r</mi></mrow></msub><mo>)</mo></mrow><mo>=</mo><msup><mover><mi>C</mi><mo>&amp;OverBar;</mo></mover><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msup><mo>&amp;CenterDot;</mo><mi>v</mi><mi>e</mi><mi>c</mi><mrow><mo>(</mo><msub><mover><mi>H</mi><mo>&amp;OverBar;</mo></mover><mrow><mi>u</mi><mi>n</mi><mi>c</mi><mi>o</mi><mi>r</mi><mi>r</mi></mrow></msub><mo>)</mo></mrow></mrow> vec() means to take column vector operation; Step 3, according to the lognormal distribution of the amplitude of large-scale fading, input the channel parameters α and ψ of the Loo model, and set Substituting into the following formula, the channel characteristic matrix of polarization-related log-normal distribution is generated <mrow><mi>v</mi><mi>e</mi><mi>c</mi><mrow><mo>(</mo><mover><mi>H</mi><mo>&amp;OverBar;</mo></mover><mo>)</mo></mrow><mo>=</mo><msup><mn>10</mn><mrow><mo>&amp;lsqb;</mo><mi>v</mi><mi>e</mi><mi>c</mi><mrow><mo>(</mo><msub><mover><mi>H</mi><mo>&amp;OverBar;</mo></mover><mrow><mi>c</mi><mi>o</mi><mi>r</mi><mi>r</mi></mrow></msub><mo>)</mo></mrow><mrow><mo>(</mo><mi>&amp;psi;</mi><mo>/</mo><mn>20</mn><mo>)</mo></mrow><mo>+</mo><mrow><mo>(</mo><mi>&amp;alpha;</mi><mo>/</mo><mn>20</mn><mo>)</mo></mrow><mo>&amp;rsqb;</mo></mrow></msup><mo>;</mo></mrow> Step 4: According to the influence of polarization on channel sequence power, input the polarization discrimination degree XPD _ant,r of the polarized antenna located on the high-speed aircraft, and use the following formula to adjust the large-scale fading matrix <mrow><mover><mi>H</mi><mo>&amp;OverBar;</mo></mover><mo>=</mo><mo>&amp;lsqb;</mo><msub><mover><mi>h</mi><mo>&amp;OverBar;</mo></mover><mrow><mi>i</mi><mi>j</mi></mrow></msub><mo>&amp;rsqb;</mo><mo>=</mo><mfenced open = "[" close = "]"><mtable><mtr><mtd><mrow><msqrt><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>&amp;beta;</mi><mrow><mi>a</mi><mi>n</mi><mi>t</mi></mrow></msub><mo>)</mo></mrow></msqrt><mo>&amp;CenterDot;</mo><msub><mover><mi>h</mi><mo>&amp;OverBar;</mo></mover><mn>11</mn></msub></mrow></mtd><mtd><mrow><msqrt><msub><mi>&amp;beta;</mi><mrow><mi>a</mi><mi>n</mi><mi>t</mi></mrow></msub></msqrt><mo>&amp;CenterDot;</mo><msub><mover><mi>h</mi><mo>&amp;OverBar;</mo></mover><mn>12</mn></msub></mrow></mtd></mtr><mtr><mtd><mrow><msqrt><msub><mi>&amp;beta;</mi><mrow><mi>a</mi><mi>n</mi><mi>t</mi></mrow></msub></msqrt><mo>&amp;CenterDot;</mo><msub><mover><mi>h</mi><mo>&amp;OverBar;</mo></mover><mn>21</mn></msub></mrow></mtd><mtd><mrow><msqrt><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>&amp;beta;</mi><mrow><mi>a</mi><mi>n</mi><mi>t</mi></mrow></msub><mo>)</mo></mrow></msqrt><mo>&amp;CenterDot;</mo><msub><mover><mi>h</mi><mo>&amp;OverBar;</mo></mover><mn>22</mn></msub></mrow></mtd></mtr></mtable></mfenced><mo>;</mo></mrow> where β _ant is a factor of XPD _ant,r , 6. the high-speed aircraft relay dual-polarization MIMO channel modeling method as claimed in claim 2, is characterized in that, described 4th step specifically comprises: 1) For each state, generate a 2×2 statistically independent complex Gaussian random sequence sample matrix with a mean of 0 and a variance of 1 2) In order to introduce the Doppler frequency shift effect, the 2×2 complex Gaussian random sequence matrix Each element is implemented through a Butterworth filter, resulting in a complex Gaussian random sequence matrix with Doppler effect The Butterworth filter is expressed as: <mrow><mo>|</mo><msub><mi>H</mi><mrow><mi>B</mi><mi>u</mi><mi>t</mi><mi>t</mi></mrow></msub><mrow><mo>(</mo><mi>f</mi><mo>)</mo></mrow><msup><mo>|</mo><mn>2</mn></msup><mo>=</mo><mfrac><mi>A</mi><mrow><mn>1</mn><mo>+</mo><msup><mrow><mo>(</mo><mi>f</mi><mo>/</mo><msub><mi>f</mi><mi>c</mi></msub><mo>)</mo></mrow><mrow><mn>2</mn><mi>k</mi></mrow></msup></mrow></mfrac><mo>;</mo></mrow> Wherein, A=exp(-vT/r _c ), v is the flight speed of the aircraft, T is the sampling interval, r _c is the coherent distance, and f _c is the cut-off frequency of the k-order filter; 3) According to the fact that the magnitude of small-scale fading obeys the Rayleigh distribution, in order to generate a 2×2 complex Rayleigh sequence, input the Loo model channel parameter MP, and the complex Gaussian sequence matrix multiply each element by to generate the Rayleigh 2×2 matrix in 4) Input the correlation matrix of the small-scale fading component and will into the following formula, using the correlation matrix Generate the polarization correlation between MIMO sub-channels, and obtain the polarization-related channel characteristic 2×2 matrix <mrow><mi>v</mi><mi>e</mi><mi>c</mi><mrow><mo>(</mo><mover><mi>H</mi><mo>~</mo></mover><mo>)</mo></mrow><mo>=</mo><msup><mover><mi>C</mi><mo>~</mo></mover><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msup><mo>&amp;CenterDot;</mo><mi>v</mi><mi>e</mi><mi>c</mi><mrow><mo>(</mo><msub><mover><mi>H</mi><mo>~</mo></mover><mrow><mi>r</mi><mi>a</mi><mi>y</mi><mi>l</mi><mi>e</mi><mi>i</mi><mi>g</mi><mi>h</mi></mrow></msub><mo>)</mo></mrow><mo>;</mo></mrow> <mrow><mover><mi>C</mi><mo>~</mo></mover><mo>=</mo><msubsup><mover><mi>R</mi><mo>~</mo></mover><mrow><mi>t</mi><mi>x</mi></mrow><mi>T</mi></msubsup><mo>&amp;CircleTimes;</mo><msub><mover><mi>R</mi><mo>~</mo></mover><mrow><mi>r</mi><mi>x</mi></mrow></msub><mo>;</mo></mrow> in, Represents the Kronecker product, the superscript T represents the matrix transpose, with Represent the 2×2 covariance matrix of the sending end and the receiving end respectively; <mrow><mtable><mtr><mtd><mrow><msub><mover><mi>R</mi><mo>~</mo></mover><mrow><mi>t</mi><mi>x</mi></mrow></msub><mo>=</mo><mfenced open = "[" close = "]"><mtable><mtr><mtd><mn>1</mn></mtd><mtd><msub><mi>&amp;rho;</mi><mrow><mi>t</mi><mo>,</mo><mi>L</mi></mrow></msub></mtd></mtr><mtr><mtd><msub><mi>&amp;rho;</mi><mrow><mi>t</mi><mo>,</mo><mi>R</mi></mrow></msub></mtd><mtd><mn>1</mn></mtd></mtr></mtable></mfenced></mrow></mtd></mtr><mtr><mtd><mrow><msub><mover><mi>R</mi><mo>~</mo></mover><mrow><mi>r</mi><mi>x</mi></mrow></msub><mo>=</mo><mfenced open = "[" close = "]"><mtable><mtr><mtd><mn>1</mn></mtd><mtd><msub><mi>&amp;rho;</mi><mrow><mi>r</mi><mo>,</mo><mi>L</mi></mrow></msub></mtd></mtr><mtr><mtd><msub><mi>&amp;rho;</mi><mrow><mi>r</mi><mo>,</mo><mi>R</mi></mrow></msub></mtd><mtd><mn>1</mn></mtd></mtr></mtable></mfenced></mrow></mtd></mtr></mtable><mo>;</mo></mrow> in, with Denote the cross-correlation of left-handed circular polarization and right-handed circular polarization of the transmitting terminal, respectively; with Denote the cross-correlation of left-handed circular polarization and right-handed circular polarization at the receiving end, respectively; 5) According to the influence of polarization on the channel sequence power, input the environmental coupling degree XPC _env,L , XPC _env,R and the polarization discrimination degree XPD _ant,r of the polarized antenna located on the high-speed aircraft, and use the following formula to adjust the large-scale fading matrix <mrow><mover><mi>H</mi><mo>~</mo></mover><mo>=</mo><mo>&amp;lsqb;</mo><msub><mover><mi>h</mi><mo>~</mo></mover><mrow><mi>i</mi><mi>j</mi></mrow></msub><mo>&amp;rsqb;</mo><mo>=</mo><mfenced open = "[" close = "]"><mtable><mtr><mtd><mrow><msqrt><mrow><mn>1</mn><mo>-</mo><msub><mi>&amp;chi;</mi><mi>L</mi></msub></mrow></msqrt><msub><mover><mi>h</mi><mo>~</mo></mover><mn>11</mn></msub></mrow></mtd><mtd><mrow><msqrt><msub><mi>&amp;chi;</mi><mi>L</mi></msub></msqrt><msub><mover><mi>h</mi><mo>~</mo></mover><mn>12</mn></msub></mrow></mtd></mtr><mtr><mtd><mrow><msqrt><msub><mi>&amp;chi;</mi><mi>R</mi></msub></msqrt><msub><mover><mi>h</mi><mo>~</mo></mover><mn>21</mn></msub></mrow></mtd><mtd><mrow><msqrt><mrow><mn>1</mn><mo>-</mo><msub><mi>&amp;chi;</mi><mi>R</mi></msub></mrow></msqrt><msub><mover><mi>h</mi><mo>~</mo></mover><mn>22</mn></msub></mrow></mtd></mtr></mtable></mfenced><mo>;</mo>< /m row> in with 7. A high-speed aircraft using the high-speed aircraft relay dual-polarization MIMO channel modeling method according to any one of claims 1-6.