A method for modeling a multipath scattering channel for unmanned aerial vehicle-to-vehicle communication

Abstract

This invention relates to the field of wireless information transmission and discloses a multipath scattering channel modeling method for UAV-to-vehicle communication. The method includes: calculating the line-of-sight path delay, phase, and received power based on the configuration parameters of the UAV-to-vehicle communication, and determining the line-of-sight path coefficient; calculating the ground reflection path delay, phase, and received power based on the configuration parameters of the UAV-to-vehicle communication, and determining the ground reflection path coefficient; determining the existence of a building wall reflection path based on the configuration parameters of the UAV-to-vehicle communication, calculating the building wall reflection path delay, phase, and received power, and determining the building wall reflection path coefficient; calculating the scattering path delay, phase, and normalized power allocation coefficient based on the configuration parameters of the UAV-to-vehicle communication, and determining the scattering path coefficient; and constructing a U2V communication channel model based on the determined line-of-sight path coefficient, ground reflection path coefficient, building wall reflection path coefficient, and scattering path coefficient.

Description

Technical Field

[0001] This invention belongs to the field of wireless information transmission technology, specifically, it relates to a multipath scattering channel modeling method for UAV-to-vehicle communication. Background Technology

[0002] In recent years, unmanned aerial vehicles (UAVs) have been widely used in military and civilian communications due to their advantages such as low cost, high mobility, and flexible deployment. In air-to-ground communication systems, UAVs can significantly increase the probability of line-of-sight (LoS) links, achieving wider coverage and higher communication capacity. UAV-to-vehicle (U2V) communication plays a crucial role in intelligent transportation systems, especially in critical scenarios such as road emergency rescue and traffic congestion management.

[0003] In complex U2V communication scenarios, existing channel models still suffer from the following technical shortcomings: First, traditional U2V communication models typically consider ground reflection as the most significant non-line-of-sight component. However, in urban scenarios, the exterior walls of tall buildings easily generate strong specular reflections. Ignoring this component will severely underestimate multipath energy, leading to serious distortion in the channel model and an inability to accurately reproduce the multipath dispersion characteristics in urban canyons. Consequently, communication systems designed based on this model cannot effectively cope with long-delay interference during actual deployment, ultimately resulting in biased channel capacity assessments and a significant increase in the system's bit error rate. Second, most existing U2V communication models only consider the six-dimensional motion of the UAV, neglecting the influence of ground vehicles. The attitude changes caused by terrain undulations and turning, i.e., the three-dimensional rotation of the vehicle, prevent the U2V communication model from accurately capturing the real-time deflection of the vehicle-end antenna attitude and the micro-Doppler frequency shift. As a result, it cannot truly reflect the high spatial non-stationary characteristics of the air-to-ground channel, which misleads the design of high-speed receiver algorithms. Finally, when dealing with the phase evolution caused by motion, previous work often calculated the Doppler phases generated by translation and rotation separately and then performed a simple scalar superposition. This fragmented calculation method not only deviates from the unified rigid body kinematics foundation, but also requires tracking and processing a large number of redundant intermediate variables, making the calculation of model parameters extremely cumbersome and severely restricting the real-time performance and execution efficiency of high-dynamic U2V channel simulation. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a multipath scattering channel modeling method for UAV-to-vehicle communication. This method can achieve channel modeling when both the UAV and the ground vehicle are in six-dimensional motion. It also comprehensively considers the influence of multipath components such as building wall reflections, thereby effectively improving the accuracy of UAV-to-ground vehicle communication channel modeling.

[0005] To achieve the above technical objectives, the present invention adopts the following technical solution:

[0006] A multipath scattering channel modeling method for UAV-to-vehicle communication includes the following steps: Obtain the configuration parameters for drone-to-vehicle communication; Calculate the line-of-sight path delay, phase, and received power based on the configuration parameters of the UAV's vehicle-to-vehicle communication, and determine the line-of-sight path coefficient; The ground reflection path delay, phase, and received power are calculated based on the configuration parameters of the UAV's vehicle-to-vehicle communication, and the ground reflection path coefficient is determined. The existence of a building wall reflection path is determined based on the configuration parameters of the UAV's vehicle-to-vehicle communication. The time delay, phase, and received power of the building wall reflection path are calculated to determine the building wall reflection path coefficient. The scattering path coefficients are determined by calculating the time delay, phase, and normalized power allocation coefficient of the scattering path based on the configuration parameters of the UAV's vehicle-to-vehicle communication. A U2V communication channel model is constructed based on the determined line-of-sight path coefficient, ground reflection path coefficient, building wall reflection path coefficient, and scattering path coefficient.

[0007] Furthermore, the configuration parameters for the UAV-to-vehicle communication include: carrier frequency, scene type including building statistical characteristics and environmental material electromagnetic properties, position vector, translational velocity vector, three-dimensional attitude angle and three-dimensional rotational angular velocity vector of the UAV and the ground vehicle, relative position coordinates of the transmitting antenna in the UAV body coordinate system and relative position coordinates of the receiving antenna in the ground vehicle body coordinate system.

[0008] Furthermore, the specific process for determining the line-of-sight path coefficient is as follows: The real-time position vectors of the transmitting and receiving antennas are determined based on the position vectors of the UAV and the ground vehicle, the three-dimensional attitude angles, the relative position vector of the transmitting antenna in the UAV's body coordinate system, and the relative position vector of the receiving antenna in the ground vehicle's body coordinate system. The relative distance vector and unit direction vector between the transmitting and receiving antennas on the line-of-sight path are determined based on the real-time position vectors of the transmitting and receiving antennas. Calculate the propagation delay and signal reception power between the transmitting and receiving antennas on the line-of-sight path based on the relative distance vectors between them. The real-time velocity vector of the transmitting antenna is calculated based on the three-dimensional attitude angle, translational velocity vector, three-dimensional rotational angular velocity vector of the UAV, and the relative position vector of the transmitting antenna in the UAV body coordinate system. The real-time velocity vector of the receiving antenna is calculated based on the three-dimensional attitude angle, translational velocity vector, three-dimensional rotational angular velocity vector of the ground vehicle, and the relative position vector of the receiving antenna in the ground vehicle body coordinate system. The total phase of the transmitting and receiving antennas on the line-of-sight path is calculated by combining the relative distance vector and unit direction vector of the transmitting antenna and the real-time velocity vector of the receiving antenna. The line-of-sight path coefficient is determined based on the propagation delay between the transmitting and receiving antennas, the received signal power, and the total phase along the line-of-sight path.

[0009] Furthermore: The calculation process for the real-time velocity vector of the transmitting antenna is as follows:

[0010] in, express At this moment Real-time velocity vector of each transmitting antenna, express The translational velocity vector of the drone at that moment. express At this moment The relative position vectors of the transmitting antennas in the UAV's fuselage coordinate system Represents the velocity matrix of the drone. , This indicates an antisymmetric operation on matrices. Indicates passage The UAV attitude matrix is ​​calculated from the UAV's three-dimensional attitude angles at a given time. This represents the three-dimensional rotational angular velocity vector of the UAV; The calculation process for the real-time velocity vector of the receiving antenna is as follows:

[0011] in, express At this moment Real-time velocity vector of each receiving antenna express The translational velocity vector of the ground vehicle at time t. express At this moment The relative position vector of each receiving antenna in the ground vehicle body coordinate system. Represents the velocity matrix of ground vehicles. , Indicates passage The ground vehicle attitude matrix is ​​calculated from the three-dimensional attitude angles of the ground vehicle at a given time. This represents the three-dimensional rotational angular velocity vector of a ground vehicle.

[0012] Furthermore, the specific process for determining the ground reflection path coefficient is as follows: The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. The coordinates of the reflection point on the ground reflection path are determined based on the global position coordinates of the transmitting and receiving antennas. : ,

[0013] in, express At this moment The global position coordinates of each transmitting antenna. express At this moment The global position coordinates of each receiving antenna; The position vector of the reflection point is determined based on the coordinates of the reflection point along the ground reflection path. The transmission distance along the ground reflection path is then determined by combining this vector with the real-time position vectors of the transmitting and receiving antennas. ,in, express The position vector of the reflection point at time t. express At this moment Real-time position vector of each transmitting antenna, express At this moment Real-time position vector of each receiving antenna; The transmission delay of the ground reflection path is determined based on the transmission distance of the ground reflection path. ,in, Indicates the speed of propagation of electromagnetic waves; The reflection angle of the ground reflection path is determined by combining the reflection point position vector with the global and real-time position coordinates of the transmitting antenna. ; The reflection coefficient of the ground reflection path is determined based on the reflection angle of the ground reflection path. ,in, This represents the complex relative permittivity of the ground-reflecting material; Combining the reflection coefficient and transmission distance of the ground reflection path with the carrier frequency Determine the signal received power of the ground reflection path ; Based on the real-time position vectors of the transmitting and receiving antennas and the position vector of the reflection point on the ground reflection path, determine the unit direction vectors of the transmitting antenna and the ground reflection point on the ground reflection path, as well as the unit direction vectors of the receiving antenna and the ground reflection point. Combine the real-time velocity vectors of the transmitting and receiving antennas and the transmission distance of the ground reflection path to calculate the total phase of the transmitting and receiving antennas on the ground reflection path. The ground reflection path coefficient is calculated based on the propagation delay of the ground reflection path, the signal received power, and the total phase.

[0014] Furthermore, the specific process for determining the reflection path coefficient of the building wall is as follows: Based on the scene type, obtain the percentage of building area and building density, determine the average street width, and combine the position coordinates of the transmitting antenna in the drone and the position coordinates of the receiving antenna in the ground vehicle to determine the coordinates of the building wall reflection point and the position vector of the building wall reflection point; The building height is generated using statistical methods. If the generated building height is greater than the z-axis coordinate of the building wall reflection point, it indicates that a building wall reflection path exists; otherwise, no building wall reflection path exists. In the presence of a building wall reflection path, the transmission distance and transmission delay of the building wall reflection path are determined by combining the real-time position vectors of the transmitting and receiving antennas. The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. In the case of a building wall reflection path, the reflection angle of the building wall reflection path is determined by the location of the building wall reflection point and the global position coordinates of the transmitting antenna, and the reflection coefficient of the building wall reflection path is obtained. The signal receiving power of the building wall reflection path is determined by combining the reflection coefficient and transmission distance with the carrier frequency. Based on the real-time position vectors of the transmitting and receiving antennas and the position vector of the reflection point on the building wall, determine the unit direction vectors of the transmitting antenna and the reflection point on the building wall and the unit direction vectors of the receiving antenna and the reflection point on the building wall on the reflection path. Combine the real-time velocity vectors of the transmitting antenna and the receiving antenna with the transmission distance of the reflection path on the building wall to calculate the total phase of the transmitting antenna and the receiving antenna on the reflection path on the building wall. The building wall reflection path coefficient is calculated based on the propagation delay of the reflection path, the signal received power, and the total phase.

[0015] Furthermore: The coordinates of the reflection point on the building wall The calculation process is as follows:

[0016]

[0017]

[0018] in, Indicates the average street width. express At this moment The position coordinates of each transmitting antenna express At this moment The position coordinates of each receiving antenna; The transmission distance of the reflection path of the building wall ,in, express The position vector of the reflection point on the building wall at time t. express At this moment Real-time position vector of each transmitting antenna, express At this moment Real-time position vector of each receiving antenna; The transmission delay of the reflection path of the building wall ,in, Indicates the speed of propagation of electromagnetic waves; The reflection coefficient of the building wall reflection path ,in, This represents the complex relative permittivity of the reflective material in building walls. express The angle of reflection along the reflection path of the building wall at a given time. ; The signal receiving power of the building wall reflection path ,in, Indicates the carrier frequency.

[0019] Furthermore, the specific process for determining the scattering path coefficient is as follows: Determine the radial distance, azimuth angle, and pitch angle of the center of the scattering cluster relative to the geometric center of the ground vehicle based on the scene type, and determine the position vector of the scattering cluster center by combining the position vector of the ground vehicle. The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. The average angle of arrival of the scattering cluster is determined by combining the position coordinates and position vector of the center of the scattering cluster with the global position coordinates of the receiving antenna in the ground vehicle. The angle of arrival of each sub-path in the scattering cluster is determined based on the average angle of arrival of the scattering cluster, and the unit direction vector of the signal arriving at each sub-path in the scattering cluster is calculated. The position vector of the scattering point corresponding to each sub-path in the scattering cluster is determined by combining the unit direction vector of the signal arriving at each sub-path in the scattering cluster with the position vector of the scattering cluster center and the position vector of the receiving antenna. The transmission distance and transmission delay of each sub-path in the scattering cluster are determined by combining the position vector of the scattering point corresponding to each sub-path with the real-time position vectors of the transmitting and receiving antennas. The normalized power allocation coefficient of each sub-path in the scattering cluster is determined based on the additional time delay of each sub-path relative to the line-of-sight path. Based on the real-time position vectors of the transmitting and receiving antennas and the position vector of the scattering point corresponding to each sub-path in the scattering cluster, the unit direction vectors of the transmitting antenna and the scattering point on each sub-path in the scattering cluster and the unit direction vectors of the receiving antenna and the scattering point are determined. The total phase of the transmitting and receiving antennas on each sub-path in the scattering cluster is calculated by combining the real-time velocity vector of the transmitting antenna, the real-time velocity vector of the receiving antenna, and the transmission distance of the scattering path. The scattering path coefficients are obtained by calculating the propagation delay of all sub-paths of all scattering clusters, the normalized power distribution coefficients, and the total phase.

[0020] Furthermore, the calculation process for the position vector of the scattering cluster center is as follows:

[0021] in, express At this moment The position vector of the center of each scattering cluster express The position vector of the ground vehicle at that moment. , and They represent the first The radial distance, azimuth, and pitch angle of the center of each scattering cluster relative to the geometric center of the ground vehicle.

[0022] Furthermore, the construction process of the U2V communication channel model is as follows:

[0023] in, express At this moment, no one is in charge. The first transmitting antenna and the ground vehicle Multipath scattering channel coefficients between receiving antennas Indicates time delay. Represents Rice factor, Indicates the reflection path power coefficient. Indicates the scattering path power coefficient. express The first time on the drone The first transmitting antenna and the ground vehicle Line-of-sight path coefficients between receiving antennas express The first time on the drone The first transmitting antenna and the ground vehicle Ground reflection path coefficient between receiving antennas express The first time on the drone The first transmitting antenna and the ground vehicle The building wall reflection path coefficient between each receiving antenna express At this moment, no one is in charge. The first transmitting antenna and the ground vehicle The scattering path coefficient between each receiving antenna.

[0024] Compared with the prior art, the present invention has the following beneficial effects: (1) The multipath scattering channel modeling method for UAV-to-vehicle communication of the present invention adopts a geometry-based random channel modeling method. Under the condition of six-dimensional motion of the UAV-to-ground vehicle communication transceiver, the determination process of line-of-sight path coefficient, ground reflection path coefficient, building wall reflection path coefficient and scattering path coefficient is given, realizing efficient and accurate reproduction of U2V communication channel. (2) The multipath scattering channel modeling method for UAV-to-vehicle communication in this invention introduces the reflection path of building walls in urban high-rise scenarios and adopts a hybrid method of "deterministic geometry and statistical environment" for modeling. Compared with traditional models, this invention can more accurately characterize the strong reflection multipath propagation mechanism in urban canyon environments, make up for the limitations of current models in characterizing specific geometric environment features, and avoid underestimating multipath energy. This invention can achieve accurate simulation and reproduction of the large-scale and small-scale fading characteristics of U2V communication channels in high-rise building scenarios; (3) The multipath scattering channel modeling method for UAV-to-vehicle communication of this invention comprehensively considers the three-dimensional translational motion and three-dimensional attitude changes of the UAV and the ground vehicle. By introducing attitude matrix and velocity matrix, the real-time position and instantaneous velocity of the transmitting and receiving ends are accurately calculated. Compared with the traditional model, this invention can more accurately characterize the spatial position offset and Doppler frequency shift caused by six-dimensional motion, further improving the accuracy of channel modeling, and can realize the real and accurate reconstruction and simulation reproduction of high dynamic U2V communication scenarios.

[0025] In summary, in the face of complex multipath effects caused by dense buildings in urban scenarios, establishing an accurate and realistic U2V communication channel model through this invention is crucial for achieving reliable air-to-ground interconnection. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the multipath scattering channel modeling for UAV-to-vehicle communication according to the present invention; Figure 2 This is a diagram showing the angle of arrival distribution of the receiver in the U2V channel model of this invention; Figure 3 This is the normalized power delay spectrum of the non-line-of-sight components of the U2V channel model in this invention; Figure 4 This is a comparison of the line-of-sight path Doppler frequencies of the U2V channel model in different motion scenarios in this invention; Figure 5 This is a comparison chart of the normalized time autocorrelation function of the U2V channel model in different motion scenarios in this invention; Figure 6 This is a comparison of the Doppler power spectral density of the U2V channel model in different motion scenarios in this invention. Detailed Implementation

[0027] The technical solution of the present invention will be further explained and described below with reference to the accompanying drawings.

[0028] Figure 1 This is a schematic diagram of multipath scattering channel modeling for UAV-to-vehicle communication according to the present invention. The multipath scattering channel modeling method includes the following steps: The configuration parameters for UAV-to-vehicle communication are obtained, including: carrier frequency, scene type including building statistical characteristics and environmental material electromagnetic properties, position vector, translational velocity vector, three-dimensional attitude angle and three-dimensional rotational angular velocity vector of the UAV and ground vehicle, relative position coordinates of the transmitting antenna in the UAV body coordinate system and relative position coordinates of the receiving antenna in the ground vehicle body coordinate system.

[0029] Based on the configuration parameters of the UAV's communication with the vehicle, the line-of-sight path delay, phase, and received power are calculated to determine the line-of-sight path coefficient; specifically: The real-time position vectors of the transmitting and receiving antennas are determined based on the position vectors of the UAV and the ground vehicle, the three-dimensional attitude angles, the relative position vector of the transmitting antenna in the UAV's fuselage coordinate system, and the relative position vector of the receiving antenna in the ground vehicle's body coordinate system. ; ; in, express The first drone at present Real-time position vector of each transmitting antenna, express At this moment, the first among ground vehicles Real-time position vector of each transmitting antenna, express The position vector of the drone at that moment, express The position vector of the ground vehicle at that moment. Indicates the first The relative position vectors of each transmitting antenna element in the UAV's fuselage coordinate system Indicates the first The relative position vectors of each receiving antenna element in the ground vehicle body coordinate system; express The attitude matrix of the drone at that moment. express The attitude matrix of the ground vehicle at time t is used to calculate the position offset of the corresponding antenna caused by the three-dimensional rotation of the UAV and the ground vehicle, respectively, and can be expressed as:

[0030] in, , and These represent pitch angle, roll angle, and yaw angle, respectively.

[0031] The relative distance vector between the transmitting and receiving antennas on the line-of-sight path is determined based on their real-time position vectors. and unit direction vector .

[0032] Calculate the propagation delay between the transmitting and receiving antennas along the line-of-sight path based on the relative distance vectors between them. and signal receiving power : , ; in, The speed of electromagnetic wave propagation. Indicates the carrier frequency.

[0033] The real-time velocity vector of the transmitting antenna is calculated based on the UAV's three-dimensional attitude angles, translational velocity vector, three-dimensional rotational angular velocity vector, and the relative position vector of the transmitting antenna in the UAV's body coordinate system.

[0034] in, express At this moment Real-time velocity vector of each transmitting antenna, express The translational velocity vector of the drone at that moment. express At this moment The relative position vectors of the transmitting antennas in the UAV's fuselage coordinate system Represents the velocity matrix of the drone. , This indicates an antisymmetric operation on matrices. Indicates passage The UAV attitude matrix is ​​calculated from the UAV's three-dimensional attitude angles at a given time. This represents the three-dimensional rotational angular velocity vector of the UAV; The real-time velocity vector of the receiving antenna is calculated based on the three-dimensional attitude angle, translational velocity vector, three-dimensional rotational angular velocity vector of the ground vehicle, and the relative position vector of the receiving antenna in the ground vehicle's body coordinate system.

[0035] in, express At this moment Real-time velocity vector of each receiving antenna express The translational velocity vector of the ground vehicle at time t. express At this moment The relative position vector of each receiving antenna in the ground vehicle body coordinate system. Represents the velocity matrix of ground vehicles. , Indicates passage The ground vehicle attitude matrix is ​​calculated from the three-dimensional attitude angles of the ground vehicle at a given time. This represents the three-dimensional rotational angular velocity vector of a ground vehicle.

[0036] The total phase of the transmitting and receiving antennas along the line-of-sight path is calculated by combining the relative distance vector and unit direction vector between the transmitting and receiving antennas with the real-time velocity vectors of the transmitting and receiving antennas.

[0037] in, Indicates wave number, express At any given moment, the Doppler phase of the line-of-sight path is... .

[0038] The line-of-sight path coefficient is determined based on the propagation delay between the transmitting and receiving antennas, the received signal power, and the total phase along the line-of-sight path. ,in, Indicates time delay. Represents the impulse function. Represents the imaginary number symbol.

[0039] Based on the configuration parameters of the UAV's vehicle-to-vehicle communication, the ground reflection path delay, phase, and received power are calculated to determine the ground reflection path coefficient; specifically: The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. The coordinates of the reflection point on the ground reflection path are determined based on the global position coordinates of the transmitting and receiving antennas. : ,

[0040] in, express At this moment The global position coordinates of each transmitting antenna. express At this moment The global position coordinates of each receiving antenna.

[0041] The position vector of the reflection point is determined based on the coordinates of the reflection point along the ground reflection path. The transmission distance along the ground reflection path is then determined by combining this vector with the real-time position vectors of the transmitting and receiving antennas. ,in, express The position vector of the reflection point at time t. express At this moment Real-time position vector of each transmitting antenna, express At this moment Real-time position vector of each receiving antenna.

[0042] The transmission delay of the ground reflection path is determined based on the transmission distance of the ground reflection path. ; The reflection angle of the ground reflection path is determined by combining the reflection point position vector with the global and real-time position coordinates of the transmitting antenna. .

[0043] The reflection coefficient of the ground reflection path is determined based on the reflection angle of the ground reflection path. ,in, This represents the complex relative permittivity of the ground-reflecting material. , This represents the relative permittivity of the ground-reflecting material. This indicates the electrical conductivity of the ground reflective material. It represents the wavelength of electromagnetic waves.

[0044] The signal reception power of the ground reflection path is determined by combining the reflection coefficient and transmission distance of the ground reflection path with the carrier frequency. .

[0045] The unit direction vectors of the transmitting and receiving antennas and the reflection point position vector on the ground reflection path are determined based on the real-time position vectors of the transmitting antenna and the receiving antenna, as well as the reflection point position vector on the ground reflection path. and the unit direction vector between the receiving antenna and the ground reflection point : ; ; The total phase of the transmitting and receiving antennas along the ground reflection path is calculated by combining the real-time velocity vectors of the transmitting and receiving antennas and the transmission distance along the ground reflection path.

[0046] in, express At that moment, the Doppler phase of the ground reflection path .

[0047] The ground reflection path coefficient is calculated based on the propagation delay of the ground reflection path, the received signal power, and the total phase. .

[0048] This invention addresses urban high-rise building scenarios by introducing building wall reflection paths and employing a hybrid approach combining deterministic geometry and statistical environment analysis to model them. The existence of building wall reflection paths is determined based on the configuration parameters of UAV-to-vehicle communication. The time delay, phase, and received power of these reflection paths are calculated to determine the building wall reflection path coefficients. This accurately characterizes the strong reflection multipath propagation mechanism in urban canyon environments, overcoming the limitations of current models in representing specific geometric features and avoiding underestimation of multipath energy. Specifically: Obtain the percentage of building footprint based on scene type. and building density The average street width is determined, and the coordinates of the building wall reflection points and the position vector of the building wall reflection points are determined by combining the position coordinates of the transmitting antenna in the UAV and the position coordinates of the receiving antenna in the ground vehicle. Coordinates of the reflection point on the building wall The calculation process is as follows:

[0049]

[0050]

[0051] in, Indicates the average street width. ; express At this moment The position coordinates of each transmitting antenna express At this moment The position coordinates of each receiving antenna; The building height is generated using statistical methods, and its probability density function is: ; in, This represents the statistically generated building height. The average building height under the Rayleigh distribution; If the height of the generated building is greater than the z-axis coordinate of the building wall reflection point, it indicates that a building wall reflection path exists; otherwise, no building wall reflection path exists. In the presence of a reflection path through a building wall, the transmission distance of the reflection path is determined by combining the real-time position vectors of the transmitting and receiving antennas. and transmission delay : , ; in, express The position vector of the reflection point on the building wall at a given time.

[0052] The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. In the case of a building wall reflection path, the reflection angle of the building wall reflection path is determined by using the location of the reflection point on the building wall and the global position coordinates of the transmitting antenna, thus obtaining the reflection coefficient of the building wall reflection path: , in, This represents the complex relative permittivity of the reflective material in building walls. , This represents the relative permittivity of the reflective material in a building wall. This indicates the conductivity of the reflective material on the building wall. express The angle of reflection along the reflection path of the building wall at a given time. .

[0053] The signal receiving power of the building wall reflection path is determined by combining the reflection coefficient and transmission distance with the carrier frequency. .

[0054] The unit direction vectors of the transmitting and receiving antennas and the reflection point on the building wall are determined based on the real-time position vectors of the transmitting antenna and the reflection point on the building wall. and the unit direction vector of the receiving antenna and the reflection point on the building wall. : , ; The total phase of the transmitting and receiving antennas along the building wall reflection path is calculated by combining the real-time velocity vectors of the transmitting and receiving antennas and the transmission distance along the reflection path of the building wall: , in, express The Doppler phase of the reflection path of the wall surface at that moment. .

[0055] The building wall reflection path coefficient is calculated based on the propagation delay, signal received power, and total phase of the reflection path. .

[0056] The scattering path coefficients are determined by calculating the scattering path delay, phase, and normalized power allocation coefficient based on the configuration parameters of the UAV's vehicle-to-vehicle communication; specifically: Based on the scene type, determine the radial distance, azimuth angle, and elevation angle of the center of the scattering cluster relative to the geometric center of the ground vehicle. Combine this with the position vector of the ground vehicle to determine the position vector of the scattering cluster center.

[0057] in, express At this moment The position vector of the center of each scattering cluster express The position vector of the ground vehicle at that moment. , and They represent the first The radial distance, azimuth angle, and pitch angle of each scattering cluster center relative to the geometric center of the ground vehicle, respectively, follow the rules... , and Uniform distribution This represents the maximum radial distance, which is determined by the configured scene type.

[0058] The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. The average angle of arrival (AOA) of the scattering cluster is determined by combining the position coordinates and position vector of the center of the scattering cluster with the global position coordinates of the receiving antenna in the ground vehicle. and average pitch angle : , ; in, express At this moment The coordinates of the center of each scattering cluster.

[0059] The angle of arrival of each sub-path in the scattering cluster is determined based on the average angle of arrival of the scattering cluster, including: the first... In the scattering cluster, the th azimuth of arrival of the stripe and the In the scattering cluster, the th The pitch angle of the strip path : , ; in, Indicates the first In the scattering cluster, the th The azimuth offset of the stripe's trajectory follows a Von Mise distribution. , This represents the angular extension of the Von Mise distribution. This represents the zeroth-order modified Bessel function of the first kind. Indicates the first In the scattering cluster, the th The arrival pitch angle offset of the stripe follows a Laplacian distribution. , This represents the angular extension of the Laplacian distribution; Calculate the unit direction vector of the arriving signal of each sub-path in the scattering cluster based on the angle of arrival of each sub-path in the scattering cluster. .

[0060] By combining the unit direction vector of the signal arriving at each sub-path in the scattering cluster with the position vector of the scattering cluster center and the position vector of the receiving antenna, the position vector of the scattering point corresponding to each sub-path in the scattering cluster is determined. ; The transmission distance of each sub-path in the scattering cluster is determined by combining the position vector of the scattering point corresponding to each sub-path with the real-time position vectors of the transmitting and receiving antennas. and transmission delay : , .

[0061] The normalized power allocation coefficient of each sub-path in the scattering cluster is determined based on the additional time delay of each sub-path relative to the line-of-sight path. ,in, express The number of scattering clusters at time t represents At this moment The number of sub-diameters in each scattering cluster Indicates the first In the scattering cluster, the th Power distribution factor of strip diameter, , Represents the delay scalar. Indicates delay spread, express The additional time delay relative to the line-of-sight path at any given time. It is inter-cluster shading fading that follows a Gaussian distribution.

[0062] Based on the real-time position vectors of the transmitting and receiving antennas and the position vector of the scattering point corresponding to each sub-path in the scattering cluster, determine the unit direction vector between the transmitting antenna and the scattering point on each sub-path of the scattering cluster. and the unit direction vector of the receiving antenna and the scattering point : , ; The total phase between the transmitting and receiving antennas on each sub-path of the scattering cluster is calculated by combining the real-time velocity vectors of the transmitting and receiving antennas and the transmission distance of the scattering path.

[0063] in, This represents the Doppler phase of each sub-path in the scattering cluster. .

[0064] The scattering path coefficients are obtained by calculating the propagation delays, normalized power distribution coefficients, and total phase of all sub-paths of all scattering clusters. .

[0065] A U2V communication channel model is constructed based on the determined line-of-sight path coefficient, ground reflection path coefficient, building wall reflection path coefficient, and scattering path coefficient:

[0066] in, express At this moment, no one is in charge. The first transmitting antenna and the ground vehicle Multipath scattering channel coefficients between receiving antennas Represents Rice factor, Indicates the reflection path power coefficient. Indicates the scattering path power coefficient. express The first time on the drone The first transmitting antenna and the ground vehicle Line-of-sight path coefficients between receiving antennas express The first time on the drone The first transmitting antenna and the ground vehicle Ground reflection path coefficient between receiving antennas express The first time on the drone The first transmitting antenna and the ground vehicle The building wall reflection path coefficient between each receiving antenna express At this moment, no one is in charge. The first transmitting antenna and the ground vehicle The scattering path coefficient between each receiving antenna.

[0067] This invention presents a multipath scattering channel modeling method for UAV-to-vehicle communication, comprehensively considering the three-dimensional translational motion and three-dimensional attitude changes of both the UAV and the ground vehicle. By introducing attitude and velocity matrices, it accurately calculates the real-time position and instantaneous velocity of both the transmitting and receiving ends. Compared to traditional models, this invention can more accurately characterize the spatial position shift and Doppler frequency shift caused by six-dimensional motion, further improving the accuracy of channel modeling. It can achieve realistic and accurate reconstruction and simulation reproduction of highly dynamic U2V communication scenarios, and is applicable to various complex scenarios such as urban and suburban areas. It can achieve channel modeling when both the UAV and the ground vehicle are in six-dimensional motion, and comprehensively considers the influence of multipath components such as building wall reflections, thereby effectively improving the accuracy of UAV-to-vehicle communication channel simulation and providing reliable channel model support for subsequent communication system performance optimization.

[0068] To verify the effectiveness of the multipath scattering channel modeling method for UAV-to-vehicle communication proposed in this invention, the configuration parameters for UAV-to-vehicle communication are configured as follows: carrier frequency. Building footprint percentage Building density Average building height under Rayleigh distribution Scene types related to the electromagnetic properties of environmental materials, including the relative permittivity of ground materials. Electrical conductivity of ground material The relative permittivity of building wall materials Electrical conductivity of building wall materials UAV initial position vector Translational velocity vector 3D attitude angle and three-dimensional rotational angular velocity vector ; Initial position vector of ground vehicle Translational velocity vector 3D attitude angle and three-dimensional rotational angular velocity vector The relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle body coordinate system. .

[0069] Figure 2This diagram shows the angle of arrival (AHA) distribution at the receiver in the U2V channel model of this invention. The blue triangles and squares precisely mark the AHAs of the ground reflection point GR (-94.83°, 26.08°) and the wall reflection point WR (-90.00°, -26.85°), respectively. The hollow circles represent six scattering clusters with a total of 120 sub-paths, exhibiting an azimuth extension of up to 292.91°, providing wide coverage. 3GPP standard channel models typically use pure statistical probability to generate multipath angles, lacking spatial geometric constraints. This results in strong reflection paths deviating significantly from the actual physical environment, leading to substantial random errors. This invention employs a "quasi-deterministic" geometric analytical method, improving the AHA prediction accuracy of the ground reflection point GR and the wall reflection point WR from "probabilistic guessing" to "physically-level absolute accuracy." Through real coordinate derivation, the spatial location error of the dominant path is completely eliminated; simultaneously, the 292.91° azimuth extension perfectly reproduces the complex omnidirectional scattering characteristics of urban canyons. This hybrid generation mechanism, which "determines the geometric direction of the reflection path and distributes the scattering path according to probability," not only restores the multipath distribution characteristics of real three-dimensional space but also avoids the enormous computational burden of full ray tracing.

[0070] Figure 3 The normalized power delay spectrum of the non-line-of-sight component of the U2V channel model in this invention is shown. The reflection path delays of the deterministic ground reflection point GR and the wall reflection point WR are extremely short, at 1.01 μs and 1.02 μs respectively, and their power is significant, at -7.24 dB and -5.45 dB respectively. The random scattering clusters are distributed in the long delay region of 1.13 to 1.53 μs, and their power exhibits an exponential decay tail up to -28.18 dB. The 3GPP standard channel model cannot distinguish the impact of specific geometric environments on multipath propagation, resulting in huge random errors in the time delay and power allocation of strong reflection paths. This invention adopts a "quasi-deterministic" architecture, using geometric optics and Fresnel equations to improve the time delay calculation accuracy of ground reflection point GR and wall reflection point WR to "nanosecond-level precision", and truly reflects the power loss caused by materials. It perfectly reproduces the real physical fading law of "strong reflection dominance and weak scattering tail" in urban canyons, fundamentally eliminating the scene mismatch bias of statistical models. This "determined main path and statistical multipath" processing architecture ensures the high reliability of time delay power spectrum generation and low computational complexity.

[0071] Figure 4This diagram compares the line-of-sight path Doppler frequencies of the U2V channel model in this invention under different motion scenarios. The blue curve represents the state of the UAV only translating; the red and green curves show the states when superimposed with π / 2 rad / s and π rad / s yaw rotation, respectively, with the overall highest frequency shift reaching 143 Hz. Due to the micro-Doppler effect caused by rotation, the red and green curves exhibit periodic fluctuations, producing frequency shift deviations of 6.1 Hz and 12.4 Hz respectively compared to the pure translation motion scenario. The 3GPP standard channel model treats the terminal as a point mass, completely ignoring attitude rotation, and its prediction results, as shown by the blue curve, have significant blind spots during high-maneuverability UAVs. This invention, by introducing velocity matrix theory, accurately corrects the 12.4 Hz absolute error in Doppler calculation in the 3GPP standard channel model. Compared to traditional approximate estimation, this invention utilizes the velocity matrix to achieve strict coupling of translation and rotation effects, avoiding error accumulation and enabling high-fidelity reproduction of the true phase evolution.

[0072] Figure 5 This diagram compares the normalized time autocorrelation function (TCF) of the U2V channel model in this invention under different motion scenarios. The blue and red curves represent the motion states of both the proposed and 3GPP standard channel models when the WR path at the wall reflection point is stable, both exhibiting double-ended translational motion, with a maximum TCF difference of 0.46. The green and purple curves represent the single-ended and double-ended yaw motions introduced in this invention, respectively, with maximum deviation reductions of 0.14 and 0.19 compared to the 3GPP standard channel model. Because the traditional 3GPP standard channel model treats the terminal as a point mass and lacks specific geometric constraints, it severely underestimates channel coherence in steady-state scenarios and fails to capture the micro-Doppler decorrelation effect caused by attitude rotation in highly maneuverable scenarios. This invention, by introducing a deterministic WR path and velocity matrix, eliminates the absolute coherence prediction error by up to 0.46. The multipath scattering channel modeling method for U2V channels in this invention perfectly reproduces the real physical interweaving process of "strong reflection stable channel" and "attitude rotation accelerated fading" in urban canyons, and realizes high-fidelity simulation of the actual channel evolution characteristics, providing accurate theoretical feasibility support for the evaluation of high dynamic receiver algorithms.

[0073] Figure 6The image shows a comparison of the Doppler power spectral density of the U2V channel model in this invention under different motion scenarios. The main peak of all three models is at -116Hz, while the secondary peak of the 3GPP standard channel model is at -78Hz, i.e., the ground reflection point; while the secondary peak of this invention is located at -40Hz, i.e., the wall reflection point. After introducing single-ended and double-ended yaw motion, the main peak of this invention is significantly broadened by 50Hz and 75Hz respectively compared to the 3GPP standard channel model, and the peak power decreases by 8dB and 15dB respectively. This is because the 3GPP standard channel model simplifies the terminal as a static point mass and completely ignores rigid body rotation, resulting in severe frequency domain narrowing and energy overestimation distortion in its spectrum prediction. This invention, by introducing a velocity matrix, accurately corrects the lack of micro-Doppler broadening up to 75Hz in the 3GPP standard channel model, as well as the 15dB absolute error of peak power overestimation; at the same time, it geometrically corrects the strong secondary peak from -78Hz to -40Hz, perfectly restoring the Doppler projection of real wall reflection in urban canyons. The multipath scattering channel modeling method for U2V channels proposed in this invention can accurately capture the micro-Doppler effect caused by attitude changes, providing a practical and feasible technical solution for accurate prediction of high dynamic channel states.

[0074] In one technical solution of the present invention, a computer-readable storage medium is also provided, storing a computer program that enables a computer to execute the multipath scattering channel modeling method for UAV-to-vehicle communication of the present invention.

[0075] In one technical solution of the present invention, an electronic device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the multipath scattering channel modeling method for UAV-to-vehicle communication of the present invention.

[0076] In the embodiments disclosed in this application, a computer storage medium may be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, and portable compact disc read-only memory (CD). ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0077] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0078] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A multipath scattering channel modeling method for UAV-to-vehicle communication, characterized in that, Includes the following steps: Obtain the configuration parameters for drone-to-vehicle communication; Calculate the line-of-sight path delay, phase, and received power based on the configuration parameters of the UAV's vehicle-to-vehicle communication, and determine the line-of-sight path coefficient; The ground reflection path delay, phase, and received power are calculated based on the configuration parameters of the UAV's vehicle-to-vehicle communication, and the ground reflection path coefficient is determined. The existence of a building wall reflection path is determined based on the configuration parameters of the UAV's vehicle-to-vehicle communication. The time delay, phase, and received power of the building wall reflection path are calculated to determine the building wall reflection path coefficient. The scattering path coefficients are determined by calculating the time delay, phase, and normalized power allocation coefficient of the scattering path based on the configuration parameters of the UAV's vehicle-to-vehicle communication. A U2V communication channel model is constructed based on the determined line-of-sight path coefficient, ground reflection path coefficient, building wall reflection path coefficient, and scattering path coefficient.

2. The multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 1, characterized in that, The configuration parameters for UAV-to-vehicle communication include: carrier frequency, scene type including building statistical characteristics and environmental material electromagnetic properties, position vector, translational velocity vector, three-dimensional attitude angle and three-dimensional rotational angular velocity vector of the UAV and ground vehicle, relative position coordinates of the transmitting antenna in the UAV body coordinate system and relative position coordinates of the receiving antenna in the ground vehicle body coordinate system.

3. A multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 2, characterized in that, The specific process for determining the line-of-sight path coefficient is as follows: The real-time position vectors of the transmitting and receiving antennas are determined based on the position vectors of the UAV and the ground vehicle, the three-dimensional attitude angles, the relative position vector of the transmitting antenna in the UAV's body coordinate system, and the relative position vector of the receiving antenna in the ground vehicle's body coordinate system. The relative distance vector and unit direction vector between the transmitting and receiving antennas on the line-of-sight path are determined based on the real-time position vectors of the transmitting and receiving antennas. Calculate the propagation delay and signal reception power between the transmitting and receiving antennas on the line-of-sight path based on the relative distance vectors between them. The real-time velocity vector of the transmitting antenna is calculated based on the three-dimensional attitude angle, translational velocity vector, three-dimensional rotational angular velocity vector of the UAV, and the relative position vector of the transmitting antenna in the UAV body coordinate system. The real-time velocity vector of the receiving antenna is calculated based on the three-dimensional attitude angle, translational velocity vector, three-dimensional rotational angular velocity vector of the ground vehicle, and the relative position vector of the receiving antenna in the ground vehicle body coordinate system. The total phase of the transmitting and receiving antennas on the line-of-sight path is calculated by combining the relative distance vector and unit direction vector of the transmitting antenna and the real-time velocity vector of the receiving antenna. The line-of-sight path coefficient is determined based on the propagation delay between the transmitting and receiving antennas, the received signal power, and the total phase along the line-of-sight path.

4. The multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 3, characterized in that: The calculation process for the real-time velocity vector of the transmitting antenna is as follows: in, express At this moment Real-time velocity vector of each transmitting antenna, express The translational velocity vector of the drone at that moment. express At this moment The relative position vectors of the transmitting antennas in the UAV's fuselage coordinate system Represents the velocity matrix of the drone. , This indicates an antisymmetric operation on matrices. Indicates passage The UAV attitude matrix is ​​calculated from the UAV's three-dimensional attitude angles at a given time. This represents the three-dimensional rotational angular velocity vector of the UAV; The calculation process for the real-time velocity vector of the receiving antenna is as follows: in, express At this moment Real-time velocity vector of each receiving antenna express The translational velocity vector of the ground vehicle at time t. express At this moment The relative position vector of each receiving antenna in the ground vehicle body coordinate system. Represents the velocity matrix of ground vehicles. , Indicates passage The ground vehicle attitude matrix is ​​calculated from the three-dimensional attitude angles of the ground vehicle at a given time. This represents the three-dimensional rotational angular velocity vector of a ground vehicle.

5. A multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 3, characterized in that, The specific process for determining the ground reflection path coefficient is as follows: The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. The coordinates of the reflection point on the ground reflection path are determined based on the global position coordinates of the transmitting and receiving antennas. : ， in, express At this moment The global position coordinates of each transmitting antenna. express At this moment The global position coordinates of each receiving antenna; The position vector of the reflection point is determined based on the coordinates of the reflection point along the ground reflection path. The transmission distance along the ground reflection path is then determined by combining this vector with the real-time position vectors of the transmitting and receiving antennas. ,in, express The position vector of the reflection point at time t. express At this moment Real-time position vector of each transmitting antenna, express At this moment Real-time position vector of each receiving antenna; The transmission delay of the ground reflection path is determined based on the transmission distance of the ground reflection path. ,in, Indicates the speed of propagation of electromagnetic waves; The reflection angle of the ground reflection path is determined by combining the reflection point position vector with the global and real-time position coordinates of the transmitting antenna. ; The reflection coefficient of the ground reflection path is determined based on the reflection angle of the ground reflection path. ,in, This represents the complex relative permittivity of the ground-reflecting material; Combining the reflection coefficient and transmission distance of the ground reflection path with the carrier frequency Determine the signal received power of the ground reflection path ; Based on the real-time position vectors of the transmitting and receiving antennas and the position vector of the reflection point on the ground reflection path, determine the unit direction vectors of the transmitting antenna and the ground reflection point on the ground reflection path, as well as the unit direction vectors of the receiving antenna and the ground reflection point. Combine the real-time velocity vectors of the transmitting and receiving antennas and the transmission distance of the ground reflection path to calculate the total phase of the transmitting and receiving antennas on the ground reflection path. The ground reflection path coefficient is calculated based on the propagation delay of the ground reflection path, the signal received power, and the total phase.

6. A multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 3, characterized in that, The specific process for determining the reflection path coefficient of the building wall is as follows: Based on the scene type, obtain the percentage of building area and building density, determine the average street width, and combine the position coordinates of the transmitting antenna in the drone and the position coordinates of the receiving antenna in the ground vehicle to determine the coordinates of the building wall reflection point and the position vector of the building wall reflection point; The building height is generated using statistical methods. If the generated building height is greater than the z-axis coordinate of the building wall reflection point, it indicates that a building wall reflection path exists; otherwise, no building wall reflection path exists. In the presence of a building wall reflection path, the transmission distance and transmission delay of the building wall reflection path are determined by combining the real-time position vectors of the transmitting and receiving antennas. The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. In the case of a building wall reflection path, the reflection angle of the building wall reflection path is determined by the location of the building wall reflection point and the global position coordinates of the transmitting antenna, and the reflection coefficient of the building wall reflection path is obtained. The signal receiving power of the building wall reflection path is determined by combining the reflection coefficient and transmission distance with the carrier frequency. Based on the real-time position vectors of the transmitting and receiving antennas and the position vector of the reflection point on the building wall, determine the unit direction vectors of the transmitting antenna and the reflection point on the building wall and the unit direction vectors of the receiving antenna and the reflection point on the building wall on the reflection path. Combine the real-time velocity vectors of the transmitting antenna and the receiving antenna with the transmission distance of the reflection path on the building wall to calculate the total phase of the transmitting antenna and the receiving antenna on the reflection path on the building wall. The building wall reflection path coefficient is calculated based on the propagation delay of the reflection path, the signal received power, and the total phase.

7. A multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 6, characterized in that: The coordinates of the reflection point on the building wall The calculation process is as follows: in, Indicates the average street width. express At this moment The position coordinates of each transmitting antenna express At this moment The position coordinates of each receiving antenna; The transmission distance of the reflection path of the building wall ,in, express The position vector of the reflection point on the building wall at time t. express At this moment Real-time position vector of each transmitting antenna, express At this moment Real-time position vector of each receiving antenna; The transmission delay of the reflection path of the building wall ,in, Indicates the speed of propagation of electromagnetic waves; The reflection coefficient of the building wall reflection path ,in, This represents the complex relative permittivity of the reflective material in building walls. express The angle of reflection along the reflection path of the building wall at a given time. ; The signal receiving power of the building wall reflection path ,in, Indicates the carrier frequency.

8. A multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 2, characterized in that, The specific process for determining the scattering path coefficient is as follows: Determine the radial distance, azimuth angle, and pitch angle of the center of the scattering cluster relative to the geometric center of the ground vehicle based on the scene type, and determine the position vector of the scattering cluster center by combining the position vector of the ground vehicle. The global position coordinates of the transmitting antenna and the receiving antenna are determined based on the relative position coordinates of the transmitting antenna in the UAV's fuselage coordinate system and the relative position coordinates of the receiving antenna in the ground vehicle's body coordinate system. The average angle of arrival of the scattering cluster is determined by combining the position coordinates and position vector of the center of the scattering cluster with the global position coordinates of the receiving antenna in the ground vehicle. The angle of arrival of each sub-path in the scattering cluster is determined based on the average angle of arrival of the scattering cluster, and the unit direction vector of the signal arriving at each sub-path in the scattering cluster is calculated. The position vector of the scattering point corresponding to each sub-path in the scattering cluster is determined by combining the unit direction vector of the signal arriving at each sub-path in the scattering cluster with the position vector of the scattering cluster center and the position vector of the receiving antenna. The transmission distance and transmission delay of each sub-path in the scattering cluster are determined by combining the position vector of the scattering point corresponding to each sub-path with the real-time position vectors of the transmitting and receiving antennas. The normalized power allocation coefficient of each sub-path in the scattering cluster is determined based on the additional time delay of each sub-path relative to the line-of-sight path. Based on the real-time position vectors of the transmitting and receiving antennas and the position vector of the scattering point corresponding to each sub-path in the scattering cluster, the unit direction vectors of the transmitting antenna and the scattering point on each sub-path in the scattering cluster and the unit direction vectors of the receiving antenna and the scattering point are determined. The total phase of the transmitting and receiving antennas on each sub-path in the scattering cluster is calculated by combining the real-time velocity vector of the transmitting antenna, the real-time velocity vector of the receiving antenna, and the transmission distance of the scattering path. The scattering path coefficients are obtained by calculating the propagation delay of all sub-paths of all scattering clusters, the normalized power distribution coefficients, and the total phase.

9. A multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 8, characterized in that, The calculation process for the position vector of the scattering cluster center is as follows: in, express At this moment The position vector of the center of each scattering cluster express The position vector of the ground vehicle at that moment. , and They represent the first The radial distance, azimuth, and pitch angle of the center of each scattering cluster relative to the geometric center of the ground vehicle.

10. A multipath scattering channel modeling method for UAV-to-vehicle communication according to claim 1, characterized in that, The construction process of the U2V communication channel model is as follows: in, express At this moment, no one is in charge. The first transmitting antenna and the ground vehicle Multipath scattering channel coefficients between receiving antennas Indicates time delay. Represents Rice factor, Indicates the reflection path power coefficient. Indicates the scattering path power coefficient. express The first time on the drone The first transmitting antenna and the ground vehicle Line-of-sight path coefficients between receiving antennas express The first time on the drone The first transmitting antenna and the ground vehicle Ground reflection path coefficient between receiving antennas express The first time on the drone The first transmitting antenna and the ground vehicle The building wall reflection path coefficient between each receiving antenna express At this moment, no one is in charge. The first transmitting antenna and the ground vehicle The scattering path coefficient between each receiving antenna.

Images