A Shortwave MIMO Channel Modeling Method Based on Multi-Domain Coordination of Time-Space-Frequency-Polarization-Angle

Abstract

This invention relates to shortwave communication technology, and particularly to a shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle. The method includes: constructing a nonlinear array of transceiver antennas; determining the geometric relationships of element spacing, element velocity, distance from the reflector cluster to the antenna, and reflector cluster velocity based on three-dimensional vectors; establishing a path transmission delay characterization mechanism jointly determined by propagation distance, the number of inseparable multipath paths, and time-difference statistical characteristics; decomposing the distance from the element to the reflector cluster into time-space stationary and non-stationary terms; establishing a polarization matrix and performing amplitude-phase weighting on multipath components with different arrival and departure angles; obtaining the existence and disappearance states of the path over time based on the reflector cluster probability model combined with Markov processes; incorporating the influence of antenna polarization on channel amplitude into the channel expression; and generating impulse response and corresponding scattering functions using the obtained angular power spectrum, delay domain model, and time-varying path state model. This invention improves the polarization adaptability of large-scale arrays to actual arrays.

Description

Technical Field

[0001] This invention relates to shortwave communication technology, and in particular to a shortwave MIMO channel modeling method based on time-space-frequency-polarization-angle multi-domain coordination. Background Technology

[0002] In existing technologies, the Watterson channel model is generally used in shortwave statistical models, but it is only applicable to channels with a bandwidth of around 3 kHz. This is mainly because it discretizes each path and fixes it as a delay. While this delay can be ignored for longer inter-symbol lengths, it easily leads to inter-symbol interference (ISI) for broadband signals with long ISI lengths. Therefore, most models use the ITS model because it describes the power distribution spectrum within the path, which is beneficial for the signal transmission design of broadband signals. However, it only provides a mathematical expression for the delay power spectrum, without mentioning the physical meaning of signal transmission or explaining the underlying principles that cause this phenomenon. The entire model also has a large computational load. Because it does not consider the time-varying relationship of the delay path, neither model can describe the channel in a large-scale transmission environment. Non-stationary channel models for MIMO have formed a relatively mature system, such as the random channel model (GSCM / GBSM) system, but they are only applicable to cellular or microwave communication fields.

[0003] The above statistical modeling of path delay changes over time is insufficient. Current models focus on the time domain changes of time delay, while the survival and disappearance of transmit path delay are also important reasons for changes in path power. However, traditional shortwave channels lack relevant research. In addition to time-related changes, polarization also affects signal transmission. It not only affects the power of the received signal but also leads to changes in the correlation between different array elements.

[0004] Therefore, a shortwave MIMO channel model that takes into account the impact of polarization on spatial correlation is needed in the context of large-size array applications. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention relates to a shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle, specifically including the following steps:

[0006] S1. Construct the transceiver antenna as a nonlinear array, and determine the geometric relationships of the element spacing, element movement speed, distance from the reflector cluster to the antenna, and movement speed of the reflector cluster based on three-dimensional vectors.

[0007] S2. Establish a path transmission delay characterization mechanism determined by the propagation distance, the number of inseparable multipaths, and the time difference statistical characteristics, and obtain the delay power spectrum based on this mechanism.

[0008] S3. Decompose the distance from the array element to the reflection cluster into time-space stationary and non-stationary terms to describe the application scenarios of delay depending on the path in stationary and non-stationary environments.

[0009] S4. Establish the polarization matrix and perform amplitude and phase weighting on the multipath components with different arrival and departure angles;

[0010] S5. Based on the probability model of the reflection cluster and the Markov process, obtain the existence and disappearance states of the path over time, and simulate the influence of ionospheric fluctuations on the reflection path.

[0011] S6. Introduce the effect of antenna polarization on the channel, and incorporate the effect of antenna polarization on the channel amplitude into the channel expression;

[0012] S7. Using the obtained angular power spectrum, delay domain model and time-varying path state model, generate impulse response and corresponding scattering function to obtain shortwave MIMO channel representation.

[0013] Compared with the prior art, the present invention has at least the following beneficial effects:

[0014] (1) It can simultaneously characterize the time nonstationarity, frequency nonstationarity and spatial nonstationarity of shortwave channels, and is suitable for shortwave MIMO scenarios with large element spacing and large array size.

[0015] (2) Modeling path delay as a spatiotemporal dependent variable and introducing exponential statistical perturbation can more realistically reflect the delay and Doppler variation caused by the random motion of ionospheric reflector clusters.

[0016] (3) Explicitly introducing a polarization matching matrix can improve the consistency between simulated received power and angle characteristics. Attached Figure Description

[0017] Figure 1 This is a diagram of the shortwave MIMO non-stationary model of the present invention;

[0018] Figure 2 This is the spatial vector diagram of the transmitting array elements of the present invention;

[0019] Figure 3 This is a flowchart of the reflection cluster modeling process of the present invention;

[0020] Figure 4 This is a flowchart of the spatial correlation modeling process of the present invention;

[0021] Figure 5 This is a time-nonstationary plot of the present invention;

[0022] Figure 6 This is a non-stationary frequency plot of the present invention;

[0023] Figure 7 This is the wavenumber power spectrum of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] This invention relates to a shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle, specifically including the following steps:

[0026] S1. Construct the transceiver antenna as a nonlinear array, and determine the geometric relationships of the element spacing, element movement speed, distance from the reflector cluster to the antenna, and movement speed of the reflector cluster based on three-dimensional vectors.

[0027] S2. Establish a path transmission delay characterization mechanism determined by the propagation distance, the number of inseparable multipaths, and the time difference statistical characteristics, and obtain the delay power spectrum based on this mechanism.

[0028] S3. Decompose the distance from the array element to the reflection cluster into time-space stationary and non-stationary terms to describe the application scenarios of delay depending on the path in stationary and non-stationary environments.

[0029] S4. Establish the polarization matrix and perform amplitude and phase weighting on the multipath components with different arrival and departure angles;

[0030] S5. Based on the probability model of the reflection cluster and the Markov process, obtain the existence and disappearance states of the path over time, and simulate the influence of ionospheric fluctuations on the reflection path.

[0031] S6. Introduce the effect of antenna polarization on the channel, and incorporate the effect of antenna polarization on the channel amplitude into the channel expression;

[0032] S7. Using the obtained angular power spectrum, delay domain model and time-varying path state model, generate impulse response and corresponding scattering function to obtain shortwave MIMO channel representation.

[0033] In this embodiment, as Figure 1 A triangular array structure with transmitter and receiver is adopted to establish a three-dimensional coordinate model of array elements and the spacing between array elements. Specifically, the coordinates and spacing are the input values ​​of the model. The latitude, longitude and altitude of the input antenna are the three-dimensional coordinates of the array elements, and the distance between the transmitting points of different antennas is the element spacing. In the attached figure, the superscript R represents the receiver and T represents the transmitter. In this application, in order to avoid confusion between the superscript T and the superscript indicating transpose, Re is used to represent the receiver and Tr to represent the transmitter.

[0034] In this embodiment, a reflection cluster formed by ionospheric reflection / scattering is used as the propagation unit. A multi-cluster multipath propagation relationship is established, and each cluster is assigned an azimuth / elevation angle and an equivalent velocity. Specifically, the starting point coordinates of the reflection cluster are set, the azimuth and elevation angles are set, one of the selected array elements is used as the reference array element, the angle between the vector formed by these two elements and the plane is the elevation angle, the angle between its projection on the plane and the direction of the Earth's North Pole is the azimuth angle, and the velocity is the cluster movement velocity.

[0035] This embodiment derives the propagation distance from array elements to reflection clusters based on geometric vector relationships, dividing the distance into stationary and non-stationary components: the stationary component consists of the linear motion of the array and the fixed distance between array elements, while the non-stationary component consists of the non-linear motion of the array elements and the different signal transmission distances caused by the varying distances between reflection clusters at greater distances; the stationary component is further divided into time-stationary and space-stationary components, while the non-stationary component is divided into time-non-stationary and space-non-stationary components. The specific principles are as follows:

[0036] The distance from the array element to the reflection cluster is decomposed into time-space stationary and non-stationary terms, where the total transmission distance from the i-th array element at the transmitter to the reflection cluster is expressed as:

[0037]

[0038]

[0039]

[0040]

[0041]

[0042]

[0043]

[0044] in, Indicates time-stationary components; The angle between the total velocity vector of the transmitter reflector cluster moving to transmitter element i and the distance vector formed by the initial transmitter reflector cluster and the reference transmitter element; This indicates the moving speed of the reflector cluster at the transmitting end; This represents the moving speed of the i-th array element at the transmitting end; Represents the spatial stability component at the transmitting end; The angle between the distance vector from the reference element to the i-th element of the transmitter and the distance vector formed by the reflector cluster at the transmitter to the reference element; This represents the distance from the reference element at the transmitter to the i-th element at the transmitter. This represents the non-stationary time component at the transmitting end; This indicates the distance from the transmitting reference element to the transmitting end reflection cluster; Indicates the modulo value; This represents the spatial non-stationary component at the transmitting end; It represents the azimuth angle of the distance vector between the i-th element of the transmitter and the transmitting reference element; The azimuth angle represents the distance vector between the transmitting reference element and the transmitting reflector cluster; The elevation angle represents the distance vector from the transmitting reference element to the transmitting end reflection cluster. The elevation angle represents the distance vector between the i-th element of the transmitter and the transmitting reference element. This represents the total transmission distance of the signal emitted by array element i to the reflection cluster.

[0045] To describe ionospheric uncertainty, this embodiment introduces an exponentially distributed random variable as a random delay perturbation term, obtaining the time-varying delay for each path:

[0046]

[0047] in, , These represent the distances from the receiver and transmitter array elements to the reflector cluster, respectively. The distance from the first reflection cluster to the last reflection cluster. is a random jitter term with a composite exponential distribution; c is the speed of light.

[0048] A polarization matrix is ​​established, and the multipath components with different arrival / departure angles are weighted by amplitude and phase. Circular polarization matching is preferred to improve stability in the reflection environment. The polarization matrix is ​​as follows:

[0049]

[0050]

[0051] in, The polarization matrix, Indicates transpose. For the transmitter polarization mode, Indicates the level factor, Indicates the vertical factor; For receiver polarization; This represents the time-varying amplitude value of the horizontal component of the transmitted or received signal at terminal k. , Indicates the sending end. Indicates the receiving end; The signal angular frequency; The initial phases of the horizontal and vertical components; This represents the time-varying amplitude value of the vertical component of the transmitted or received signal at end k; This represents the phase difference between the vertical and horizontal components.

[0052] This embodiment uses a reflection cluster probability model combined with a Markov process to obtain the existence and disappearance states of a path over time, such as... Figure 3 Specifically, it includes:

[0053] Based on the state preservation probability density function of array element i at the transmitting end and the state preservation probability density function of array element j at the receiving end, calculate the state preservation probability density function under the current transmission time difference.

[0054] Generate a random number and determine the relationship between the state preservation probability density function and the random number under the current transmission time difference;

[0055] If the state preservation probability density function is greater than or equal to the random number, then the current state is maintained; otherwise, the current state is changed.

[0056] The current state value is 1 or 0. When the state value is 1, it indicates that the channel between the transmitting element i and the receiving element j is active. When the state value is 0, it indicates that the channel is in sleep mode.

[0057] In this embodiment, the state preservation probability density function is expressed as:

[0058]

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065] in, Indicates signal transmission After a certain time, the state between transmitter element i and receiver element j retains the probability density function; Indicates signal transmission After a certain time, the state of transmitter element i retains the probability density function; Indicates signal transmission After a certain time, the state of the receiver element j retains the probability density function; Indicates the wavelength of the signal; This represents the time difference factor of the transmitting array element i during signal transmission; This represents the spatial difference factor of the transmitting array element i during signal transmission; This represents the azimuth angle between the transmitting element i and the total moving velocity vector of the reflector cluster; The azimuth angle represents the distance vector between the reference element of the transmitter and element i of the transmitter array. The elevation angle represents the distance vector between the transmitter reference element and transmitter element i. This represents the velocity vector of the transmitter array element i and the total velocity vector of the transmitter reflector cluster; It represents the time difference between when the signal was emitted and the current time, that is, the time difference calculated from when the signal was emitted; This represents the coherent distance between array elements, typically taken as 10m. This represents the coherent distance of the movement, typically taken as 20m. This represents the spatial difference factor of array element j at the receiving end during signal transmission; This represents the spatial difference factor of array element j at the receiving end during signal transmission; This represents the azimuth angle between receiver element j and the total moving velocity vector of the receiver reflection cluster; This represents the azimuth angle between receiver element j and the total moving velocity vector of the receiver reflection cluster; This represents the velocity vector of the receiver array element j and the total velocity vector of the receiver reflection cluster.

[0066] Combining the previous delay model and path state model, the MIMO channel impulse response and scattering function matrix are generated. The impulse response expression is as follows:

[0067]

[0068] in, Indicates the delay-time impulse response; Indicates the number of major diameters; Indicates an inseparable multipath; This represents the status value. The current status value is 1 or 0. When the status value is 1, it indicates that the channel between the transmitting array element i and the receiving array element j is active. When the status value is 0, it indicates that the channel is in sleep mode. Indicates the signal amplitude of each indivisible multipath; The impulse response represents the different delays of each signal. This represents the delay for each indivisible multipath.

[0069] In addition, it is necessary to determine the correlation between array elements. The calculation method is as follows:

[0070]

[0071]

[0072]

[0073] in, This represents the correlation coefficient between any two array elements m and n in the transmitting or receiving end. This represents the distance between any two array elements m and n at the transmitting end; This represents the elevation angle between any two array elements m and n in the transmitting or receiving end; It represents the azimuth angle between any two array elements m and n in the transmitting or receiving end; Indicates the wavelength of the transmitted signal; Represents a two-dimensional angular power spectrum; , These are two array element coordinate vectors (representing the coordinates of the m-th and n-th array elements, with coordinates in three dimensions including longitude, latitude, and altitude). It is a unit vector.

[0074] This embodiment takes an example where the transmitting end includes c transmitting array elements and the receiving end includes d receiving array elements. Figure 4 The process of obtaining the space-correlated impulse response includes:

[0075] 1. At the receiving end and the transmitting end, calculate the receiving correlation matrix and the transmitting correlation matrix respectively. The transmitting correlation matrix is: :

[0076]

[0077] in, This represents the correlation coefficient between the first transmitting element and the second transmitting element. This represents the correlation coefficient between the first transmitting element and the c-th transmitting element; This represents the correlation coefficient between the c-th transmitting element and the 1st transmitting element; This represents the correlation coefficient between the c-th transmitting element and the c-th transmitting element.

[0078] Receiver correlation matrix Represented as:

[0079]

[0080] in, This represents the correlation coefficient between the first receiving array element and the second receiving array element. This represents the correlation coefficient between the first receiving element and the d-th receiving element; This represents the correlation coefficient between the d-th receiving element and the 1st receiving element; Let represent the correlation coefficient between the d-th receiving array element and the d-th receiving array element.

[0081] 2. The mapping matrix is ​​calculated based on the Kronecker product of the received correlation matrix and the transmitted correlation matrix, and is expressed as:

[0082]

[0083] in, For the mapping matrix, For Kronecker product.

[0084] 3. Based on the delay-time impulse response mentioned above The delay-time impulse response from each transmitting element to the receiving element is obtained, and is expressed as:

[0085]

[0086] in, Let be the pulse response from the a-th transmitting element to the b-th receiving element. Let be the polarization matrix from the a-th transmitting element to the b-th receiving element. Let j be the time-varying state factor of the j-th inseparable multipath of the i-th main path from the a-th transmitting element to the b-th receiving element. The time-varying delay is the j-th inseparable multipath of the i-th main path from the a-th transmitting element to the b-th receiving element.

[0087] 4. Finally, the delay-time impulse response matrix is ​​obtained, expressed as:

[0088] in, This is the impulse response matrix; It is represented as the delay-time impulse response from the first transmitting element to the first receiving element; The time-delay pulse response is from the first transmitting element to the c-th receiving element; The time-delay impulse response from the d-th transmitting element to the 1st receiving element; Let be the time-delay impulse response from the d-th transmitting element to the c-th receiving element.

[0089] Convert the impulse response matrix into a row vector, represented as:

[0090] in, To expand into row phasors by column, This is the delay-time impulse response vector.

[0091] 5. Multiply with the mapping matrix:

[0092]

[0093] in, This is the spatially correlated impulse response vector, which, when expanded column-wise, yields the spatially correlated impulse response matrix. 6. Assuming there are c transmitting elements and d receiving elements, the spatial correlation impulse response from the a-th transmitting element to the b-th receiving element is:

[0094]

[0095] in The spatial correlation impulse response from the a-th transmitting element to the b-th receiving element is given. The time-delay impulse response from transmitting element c to receiving element d. Let be the correlation coefficient between the a-th transmitting element and the c-th transmitting element. Let be the correlation coefficient from the b-th receiving element to the d-th receiving element. 7. After obtaining the correlation matrix, obtain the mapping matrix through the Kronecker product. Take the square root and multiply it by the impulse response vector to obtain the spatial correlation impulse response, i.e.:

[0096]

[0097]

[0098] in, Expressing expectations; For conjugate, For space-dependent impulse response, To delay, For the time difference, It is the autocorrelation function of the impulse response with respect to time; Doppler frequency.

[0099] The time correlation can be observed by taking the autocorrelation of the impulse response with respect to time, specifically as follows: Figure 5 As shown, the impulse response of this channel can characterize a time-non-stationary channel.

[0100] Taking the Fourier transform of the impulse response over the time delay domain yields the transfer function. Calculating the autocorrelation with respect to frequency reveals its frequency correlation. Specifically, as shown below... Figure 6 As shown, the impulse response of this channel can characterize a non-stationary frequency channel.

[0101] Impulse response in the time-delay domain The transfer function obtained by delaying the Fourier transform is: The spatial correlation function is then...

[0102]

[0103] in When the time is 0, the antenna spacing is Antenna distance, For transfer functions, , It is the distance of an inseparable multipath.

[0104]

[0105] in For the wavenumber domain, For the spacing between array elements, This is the spatial correlation function. The result is as follows: Figure 7 As shown, the wavenumber variation is visible, therefore this impulse response can characterize a spatially non-stationary channel.

[0106] Compared with existing technologies, this invention can clearly characterize the specific relationship between path delay and spatiotemporal characteristics, as well as the impact of different polarizations on spatial features. It improves the polarization adaptability of large-scale arrays and actual arrays, forms a parameter closed loop that can extract parameters and verify them in reverse phase, and improves the feasibility and accuracy of shortwave MIMO system simulation in engineering design.

[0107] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle, characterized in that, Specifically, the following steps are included: S1. Construct the transceiver antenna as a nonlinear array, and determine the geometric relationships of the element spacing, element movement speed, distance from the reflector cluster to the antenna, and movement speed of the reflector cluster based on three-dimensional vectors. S2. Establish a path transmission delay characterization mechanism determined by the propagation distance, the number of inseparable multipaths, and the time difference statistical characteristics, and obtain the delay power spectrum based on this mechanism. S3. Decompose the distance from the array element to the reflection cluster into time-space stationary and non-stationary terms to describe the application scenarios of delay following the path in stationary and non-stationary environments. S4. Establish the polarization matrix and perform amplitude and phase weighting on the multipath components with different arrival and departure angles; S5. Based on the probability model of the reflection cluster and the Markov process, obtain the existence and disappearance states of the path over time, and simulate the influence of ionospheric fluctuations on the reflection path. S6. Introduce the effect of antenna polarization on the channel, and incorporate the effect of antenna polarization on the channel amplitude into the channel expression; S7. Using the obtained angular power spectrum, delay domain model and time-varying path state model, generate impulse response and corresponding scattering function to obtain shortwave MIMO channel representation.

2. The shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle as described in claim 1, characterized in that, The distance from the array element to the reflection cluster is decomposed into time-space stationary and non-stationary terms, where the total transmission distance from the i-th array element at the transmitter to the reflection cluster is expressed as: in, Indicates time-stationary components; The angle between the total velocity vector of the transmitter reflector cluster moving to transmitter element i and the distance vector formed by the initial transmitter reflector cluster and the reference transmitter element; This indicates the moving speed of the reflector cluster at the transmitting end; This represents the moving speed of the i-th array element at the transmitting end; Represents the spatial stability component at the transmitting end; The angle between the distance vector from the reference element to the i-th element of the transmitter and the distance vector formed by the reflector cluster at the transmitter to the reference element; This represents the distance from the reference element at the transmitter to the i-th element at the transmitter. This represents the non-stationary time component at the transmitting end; This indicates the distance from the transmitting reference element to the transmitting end reflection cluster; Indicates the modulo value; Represents the spatial non-stationary components at the transmitting end; It represents the azimuth angle of the distance vector between the i-th element of the transmitter and the transmitting reference element; The azimuth angle represents the distance vector between the transmitting reference element and the transmitting reflector cluster; The elevation angle represents the distance vector from the transmitting reference element to the transmitting end reflection cluster. The elevation angle represents the distance vector between the i-th element of the transmitter and the transmitting reference element. This represents the total transmission distance of the signal emitted by array element i to the reflection cluster.

3. The shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle as described in claim 1, characterized in that, To describe ionospheric uncertainty, an exponentially distributed random variable is introduced as a random delay perturbation term, and the time-varying delay for each path is expressed as: in, The distance between the receiving array element and the reflection cluster; The distance between the transmitting element and the reflecting cluster; The distance from the first reflection cluster to the last reflection cluster; is the random fluctuation term; c is the speed of light.

4. The shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle as described in claim 1, characterized in that, Amplitude and phase weighting of multipath components with different angles of arrival and exit includes: in, The polarization matrix, Indicates transpose. For the transmitter polarization mode, Indicates the level factor, Indicates the vertical factor; For receiver polarization; This represents the time-varying amplitude value of the horizontal component of the transmitted or received signal at terminal k. , Indicates the sending end. Indicates the receiving end; The signal angular frequency; The initial phases of the horizontal and vertical components; This represents the time-varying amplitude value of the vertical component of the transmitted or received signal at terminal k; This represents the phase difference between the vertical and horizontal components.

5. A shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle as described in claim 1, characterized in that, Based on the reflection cluster probability model combined with Markov processes, the existence and disappearance states of the path over time are obtained, specifically including: Based on the state preservation probability density function of array element i at the transmitting end and the state preservation probability density function of array element j at the receiving end, calculate the state preservation probability density function under the current transmission time difference. Generate a random number and determine the relationship between the state preservation probability density function and the random number under the current transmission time difference; If the state preservation probability density function is greater than or equal to the random number, then the current state is maintained; otherwise, the current state is changed. The current state value is 1 or 0. When the state value is 1, it indicates that the channel between transmitter element i and receiver element j is active. When the state value is 0, it indicates that the channel is in sleep mode.

6. A shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle as described in claim 5, characterized in that, The state-preservation probability density function is expressed as: in, Indicates signal transmission After a certain time, the state between transmitter element i and receiver element j retains the probability density function; Indicates signal transmission After a certain time, the state of transmitter element i retains the probability density function; Indicates signal transmission After a certain time, the state of the receiver element j retains the probability density function; Indicates the wavelength of the signal; This represents the time difference factor of the transmitting array element i during signal transmission; This represents the spatial difference factor of the transmitting array element i during signal transmission; This represents the azimuth angle between the transmitting element i and the total moving velocity vector of the reflector cluster; The azimuth angle represents the distance vector between the reference element of the transmitter and element i of the transmitter array. The elevation angle represents the distance vector between the transmitter reference element and transmitter element i. This represents the velocity vector of the transmitter array element i and the total velocity vector of the transmitter reflector cluster; It represents the difference between the time the signal was sent and the current time. Indicates the coherent distance between array elements. Indicates the distance traveled and the coherence distance; This represents the spatial difference factor of array element j at the receiving end during signal transmission; This represents the spatial difference factor of array element j at the receiving end during signal transmission; This represents the azimuth angle between receiver element j and the total moving velocity vector of the receiver reflection cluster; This represents the azimuth angle between receiver element j and the total moving velocity vector of the receiver reflection cluster; This represents the velocity vector of the receiver array element j and the total velocity vector of the receiver reflection cluster.

7. A shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle as described in claim 1, characterized in that, The impulse response is generated using the obtained angular power spectrum, time-delay domain model, and time-varying path state model, and is expressed as follows: in, Indicates the delay-time impulse response; Indicates the number of major diameters; Indicates the number of indivisible multipaths; The polarization matrix; Indicates the state value; Indicates the signal amplitude of each indivisible multipath; The impulse response represents the different delays of each signal. This represents the delay for each indivisible multipath.

8. A shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle as described in claim 7, characterized in that, The corresponding scattering function is generated using the obtained angular power spectrum, time-delay domain model, and time-varying path state model, and is expressed as follows: ； ； in, This represents a delay-time dependent function. Indicates a delay. Indicates time difference; This represents the spatiotemporal correlated impulse response obtained after considering the spatial domain; Represents the spatiotemporal correlation scattering function. Indicates the Doppler frequency; Expressing expectations; For conjugate.

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