An active ris-assisted jitter uav air-ground safety communication method and system

Abstract

This invention provides an active RIS-assisted jitter-based UAV air-to-ground secure communication method and system, relating to the field of UAV communication technology. The active RIS-assisted jitter-based UAV air-to-ground secure communication method of this invention constructs the coordinates of each communication node in the communication system and utilizes a preset free-space path loss model to construct the UAV onboard base station channel and the active RIS channel. Simultaneously, based on the vibration characteristics of the UAV onboard base station, and using a pre-constructed set of uncertainties in azimuth and elevation angles, it considers the jitter characteristics under the influence of random airflow and airframe vibration for secure communication, determines the UAV onboard base station channel error and the active RIS channel error, and iteratively solves the constructed optimization problem to obtain the communication decision of the active RIS-assisted UAV communication system, thereby achieving the goal of reducing the impact of jitter characteristics under the influence of random airflow and airframe vibration on the safe communication of the UAV.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) communication technology, specifically to an active RIS-assisted jitter UAV air-to-ground secure communication method and system. Background Technology

[0002] The low-altitude economy is a comprehensive economic form driven by various low-altitude flight activities of manned or unmanned aircraft, radiating and promoting the integrated development of related fields. It is characterized by a long industrial chain, wide reach, strong growth potential, and significant driving force, primarily encompassing low-altitude manufacturing, low-altitude flight, low-altitude support, and low-altitude operation services. Among these, the low-altitude flight industry is the core industry of the low-altitude economy, while the drone industry represents the cutting edge of this sector. Drones are flexible and rapid mobile platforms that can be widely used in various smart city applications, such as surveying, aerial photography, evidence collection, and logistics. This involves a large amount of data processing, and the electronic components carried by drones, such as photography, environmental perception, recording, and GPS sensors, enable them to collect and store data more conveniently and over a wider area, thus posing higher requirements for data security protection.

[0003] Existing technologies have proposed using Reconfigurable Intelligence Surface (RIS) technology to improve the secure communication performance of Unmanned Aerial Vehicles (UAVs). However, most current work overlooks an unavoidable problem in RIS-assisted UAV communication: while RIS introduces a new reliable reflection link for signal transmission in addition to the direct link, a "double fading" effect always exists in this reflection link, meaning the signal received via this link suffers two large-scale fadings. When the fading coefficient is large, the signal from the longer reflection link loses more power than the signal from the shorter direct link, resulting in limited security performance gains compared to links without RIS. On the other hand, the jitter characteristics caused by random airflow and the UAV's own fuselage vibration have a significant impact on establishing robust and secure communication links. Unlike terrestrial cellular networks with fixed and stable infrastructure, UAVs are susceptible to airflow and fuselage vibration, leading to random vibrations such as yaw jitter in the horizontal direction or pitch jitter in the vertical direction. Therefore, vibration introduces non-negligible channel estimation errors, which lead to deviations in directional signal beams and further result in severe performance degradation. Summary of the Invention

[0004] To address the issue of unmanned aerial vehicle (UAV) jitter characteristics affecting safe communication under the influence of random airflow and airframe vibration in existing technologies, this invention proposes an active RIS-assisted jitter UAV air-to-ground safe communication method and system. The method involves constructing the coordinates of each communication node in the communication system and using a pre-defined free-space path loss model to build the UAV's onboard base station channel and active RIS channel. Simultaneously, based on the vibration characteristics of the UAV's onboard base station, and utilizing a pre-constructed set of uncertainties in azimuth and elevation angles, the method considers the jitter characteristics under the influence of random airflow and airframe vibration to determine the UAV's onboard base station channel error and active RIS channel error for safe communication. The constructed optimization problem is then iteratively solved to obtain the communication decision of the active RIS-assisted UAV communication system, thereby reducing the impact of jitter characteristics under random airflow and airframe vibration on the safe communication of UAVs.

[0005] On one hand, the present invention provides an active RIS-assisted jitter UAV air-to-ground secure communication method, comprising:

[0006] Based on the communication nodes in the pre-defined active RIS-assisted UAV communication system, the coordinates of each communication node in the communication system are obtained using a three-dimensional coordinate system. The communication nodes include UAV airborne base stations, active RIS, legitimate users, and eavesdroppers.

[0007] Based on the coordinates of the communication nodes in the communication system, and using a preset free space path loss model, an UAV airborne base station channel and an active RIS channel are constructed. The UAV airborne base station channel includes the channel between the UAV airborne base station and the active RIS, the channel between the UAV airborne base station and the legitimate user, and the channel between the UAV airborne base station and the eavesdropper. The active RIS channel includes the channel between the active RIS and the legitimate user and the channel between the active RIS and the eavesdropper.

[0008] Based on the vibration characteristics of UAV airborne base stations, the channel error of UAV airborne base stations and the active RIS channel error are determined by using a pre-constructed set of uncertainties in azimuth and elevation angles.

[0009] Based on the UAV's onboard base station channel and active RIS channel, the signals received by legitimate users and those received by eavesdroppers are confirmed.

[0010] By combining the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal, the minimum transmission power of the active RIS-assisted UAV communication system is taken as the optimization problem. Using an iterative algorithm, the transmission beamforming matrix and the reflection coefficient matrix are solved to obtain the optimization result, and the communication decision of the active RIS-assisted UAV communication system is generated.

[0011] Optionally, by integrating the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user's received signal, and the eavesdropper's received signal, the minimum transmit power of the active RIS-assisted UAV communication system is taken as the optimization problem. An iterative algorithm is used to solve the transmit beamforming matrix and the reflection coefficient matrix to obtain the optimization result, and the communication decision of the active RIS-assisted UAV communication system is generated, including:

[0012] By combining the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal, the minimum transmission power of the active RIS-assisted UAV communication system is taken as the optimization problem, and the constraints of the optimization problem are constructed.

[0013] Based on the constructed optimization problem and its constraints, an iterative algorithm is used to solve the transmitted beamforming matrix and the reflection coefficient matrix to obtain the optimization results.

[0014] Based on the optimization results, the communication decision of the active RIS-assisted UAV communication system is generated using the equivalent transformation algorithm.

[0015] Optionally, the constraints of the constructed optimization problem satisfy the following expression:

[0016] ,

[0017] ,

[0018] ,

[0019] ,

[0020] ,

[0021] In the formula, This represents the power of the transmitted beamforming matrix; This represents the constraints on the transmit beamforming matrix; Indicates the minimum data rate accepted by a legitimate user; This indicates the preset data rate threshold for authorized users; Indicates the maximum data rate that the eavesdropper can accept; This indicates the preset data rate threshold that the eavesdropper can accept; Represents the reflection coefficient matrix; This indicates channel fading between the UAV's onboard base station and the active RIS; It is the first m The maximum magnification factor at each RE.

[0022] Optionally, based on the constructed optimization problem and constraints, an iterative algorithm is used to solve the transmitted beamforming matrix and the reflection coefficient matrix to obtain the optimization results, including:

[0023] Based on the constructed optimization problem, the optimization problem is decomposed to generate optimization sub-problems concerning the transmitted beamforming matrix and the reflection coefficient matrix;

[0024] Based on the constraints of the aforementioned optimization subproblem, the non-convex constraints are transformed into linear matrix inequalities using the S-lemma algorithm. Then, an iterative algorithm is used to iteratively solve the transmitted beamforming matrix and the reflection coefficient matrix to determine the interference and noise power of legitimate users and the interference and noise power of eavesdroppers.

[0025] Based on the aforementioned linear matrix inequality, by introducing slack variables and using the Schur complement lemma algorithm, the linear matrix inequality is equivalently transformed to obtain the transformed optimization problem;

[0026] Based on the transformed optimization problem, the CVX tool is used to solve it and obtain the optimization results.

[0027] Optionally, the optimization problem based on the construction is decomposed into optimization sub-problems, including:

[0028] Based on the constructed optimization problem, given the reflection coefficient matrix, the optimization sub-problem of the transmitted beamforming matrix is ​​obtained;

[0029] Based on the constructed optimization problem, optimization subproblems are generated by transmitting beamforming matrices to produce their respective reflection coefficient matrices.

[0030] Optionally, the step of constructing the UAV airborne base station channel and active RIS channel based on the coordinates of the communication nodes in the communication system and using a preset free space path loss model includes:

[0031] Based on the coordinates of the communication nodes in the communication system, the reflection system matrix of the active RIS is obtained using the UAV airborne base station and the uniform rectangular array of the active RIS.

[0032] Based on the LOS and NLOS components of the UAV airborne base station channel, and a pre-defined free space path loss model, the UAV airborne base station channel is obtained.

[0033] Based on the LOS and NLOS components of the active RIS channel, and a pre-defined free-space path loss model, the active RIS channel is obtained.

[0034] Optionally, after generating the communication decision of the active RIS-assisted UAV communication system based on the optimization result and using the equivalent transformation algorithm, the method further includes:

[0035] Based on the communication decision of the active RIS-assisted UAV communication system, and combined with the channel uncertainty caused by the jitter of the UAV airborne base station, the changes in the transmission power relative to the elevation angle of the legitimate user and the elevation angle of the eavesdropper are calculated to generate an evaluation result of the active RIS-assisted UAV secure communication.

[0036] On the other hand, the present invention also provides an active RIS-assisted jitter UAV air-to-ground secure communication system, the system comprising:

[0037] The coordinate determination module is used to obtain the coordinates of each communication node in the UAV communication system based on a preset active RIS-assisted communication system using a three-dimensional coordinate system. The communication nodes include UAV airborne base stations, active RIS, legitimate users, and eavesdroppers.

[0038] The channel construction module is used to construct UAV airborne base station channels and active RIS channels based on the coordinates of communication nodes in the communication system and using a preset free space path loss model. The UAV airborne base station channels include channels between the UAV airborne base station and the active RIS, channels between the UAV airborne base station and legitimate users, and channels between the UAV airborne base station and eavesdroppers. The active RIS channels include channels between the active RIS and legitimate users and channels between the active RIS and eavesdroppers.

[0039] The error confirmation module is used to determine the channel error of the UAV airborne base station and the active RIS channel error based on the vibration characteristics of the UAV airborne base station and by using a pre-constructed set of uncertainties in azimuth and elevation angles.

[0040] The signal confirmation module is used to confirm the signals received by legitimate users and the signals received by eavesdroppers based on the UAV's onboard base station channel and active RIS channel.

[0041] The decision generation module is used to integrate the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal. Taking the minimum transmission power of the active RIS-assisted UAV communication system as the optimization objective, the module uses an iterative algorithm to solve the transmission beamforming matrix and the reflection coefficient matrix to obtain the optimization result and generate the communication decision of the active RIS-assisted UAV communication system.

[0042] In another aspect, the present invention also provides an electronic device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus;

[0043] The memory is used to store one or more programs;

[0044] When the one or more programs are executed by the at least one processor, an active RIS-assisted jitter UAV air-to-ground secure communication method as described in the above technical solution is implemented.

[0045] In another aspect, the present invention also provides a readable storage medium having an executable program stored thereon, wherein when the executable program is executed, it implements an active RIS-assisted jitter UAV air-to-ground secure communication method as described in the above technical solution.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] This invention provides an active RIS-assisted jitter UAV air-to-ground secure communication method. By constructing the coordinates of each communication node in the communication system and utilizing a pre-defined free-space path loss model, it constructs the UAV onboard base station channel and the active RIS channel. Simultaneously, based on the vibration characteristics of the UAV onboard base station, it utilizes a pre-constructed set of uncertainties in azimuth and elevation angles. By considering the jitter characteristics under the influence of random airflow and airframe vibration, it determines the UAV onboard base station channel error and the active RIS channel error for secure communication. The constructed optimization problem is then iteratively solved to obtain the communication decision of the active RIS-assisted UAV communication system, thereby achieving the goal of reducing the impact of jitter characteristics under the influence of random airflow and airframe vibration on the secure communication of the UAV. Attached Figure Description

[0048] Figure 1 This is a flowchart of an active RIS-assisted jitter UAV air-to-ground secure communication method according to the present invention;

[0049] Figure 2 A schematic diagram of the active RIS-assisted UAV communication system constructed according to the present invention;

[0050] Figure 3The number of RIS units in an active RIS-assisted jitter UAV air-to-ground secure communication method of the present invention. M Maximum variation with transmit power Compared to Alice's AOD (Avoidance of Distance) as a legitimate user A diagram illustrating the relationship between the ratios;

[0051] Figure 4 The number of RIS units in an active RIS-assisted jitter UAV air-to-ground secure communication method of the present invention. M Maximum variation with transmit power Compared to Eve's AOD (Always-Only Occurrence) A diagram illustrating the relationship between the ratios;

[0052] Figure 5 The transmission power and maximum amplification factor of the RIS in an active RIS-assisted jitter UAV air-to-ground secure communication method of the present invention are discussed. A diagram illustrating the relationships between them;

[0053] Figure 6 This is a schematic diagram of the structure of an electronic device according to the present invention. Detailed Implementation

[0054] Example 1:

[0055] Reference Figure 1 This invention provides an active RIS-assisted jitter UAV air-to-ground secure communication method, comprising:

[0056] S1, based on the communication nodes in the preset active RIS-assisted UAV communication system, the coordinates of each communication node in the communication system are obtained using a three-dimensional coordinate system. The communication nodes include UAV airborne base station, active RIS, legitimate user and eavesdropper.

[0057] S2, based on the coordinates of the communication nodes in the communication system, and using a preset free space path loss model, construct the UAV airborne base station channel and the active RIS channel. The UAV airborne base station channel includes the channel between the UAV airborne base station and the active RIS, the channel between the UAV airborne base station and the legitimate user, and the channel between the UAV airborne base station and the eavesdropper. The active RIS channel includes the channel between the active RIS and the legitimate user and the channel between the active RIS and the eavesdropper.

[0058] S3, based on the vibration characteristics of the UAV airborne base station, uses a pre-constructed set of uncertainties in azimuth and elevation angles to determine the UAV airborne base station channel error and the active RIS channel error;

[0059] S4. Based on the UAV onboard base station channel and the active RIS channel, confirm the signal received by the legitimate user and the signal received by the eavesdropper.

[0060] S5. Combining the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal, the minimum transmission power of the active RIS-assisted UAV communication system is taken as the optimization problem. Using an iterative algorithm, the transmission beamforming matrix and the reflection coefficient matrix are solved to obtain the optimization result, and the communication decision of the active RIS-assisted UAV communication system is generated.

[0061] Reference Figure 2 To facilitate research on secure air-to-ground communication methods, a typical UAV secure air-to-ground communication scenario includes an onboard UAV base station, an active RIS (Radio Router Array), legitimate users, and eavesdroppers. To support secure UAV communication, the active RIS is usually fixedly deployed on building facades or other ground-based devices. The UAV hovers at a fixed altitude and provides air-to-ground communication services through its onboard airborne base station. Furthermore, because UAV communication is susceptible to interference or hacker attacks, physical layer security transmission methods are required to ensure the security of legitimate user communications.

[0062] In S1, the present invention constructs an active RIS-assisted UAV communication system, which includes a single-antenna legitimate user Alice and a single-antenna eavesdropper Eve. The active RIS, by additionally integrating a reflective power amplifier on each RIS unit, not only modulates the reflected signal but also amplifies it with high gain, thereby compensating for the path loss caused by multiplicative fading.

[0063] For example, in S2, the present invention provides an A2G wireless channel model, where the UAV-borne base station UBS and the active RIS can both be considered to be equipped with a size of and Uniform rectangular array (URA).

[0064] Indicates along The number of onboard base station antennas for the drone on the axis; along The number of onboard base station antennas for the drone on the axis; Indicates along The number of RIS reflecting elements (REs) on the axis; Indicates along The number of RIS reflecting elements (REs) on the axis.

[0065] All communication nodes are placed in a three-dimensional Cartesian coordinate system. The coordinates of UAV, Alice, and Eve are respectively (…). ), ( )and( ).

[0066] The reflection coefficient matrix of an active RIS is represented as:

[0067] ,

[0068] In the formula, Indicates amplitude, which can be greater than 1 in an active load; This indicates the phase; in contrast, passive RIS cannot amplify the incident signal, therefore, the amplitude of each RE is limited to . ; Represents the identity matrix; Represents the imaginary unit; express M OK M A set of matrices of columns.

[0069] Furthermore, the first element of the active RIS is considered as the reference point, and its coordinates are determined by ( ) indicates that, These represent active RIS. x , y and z coordinate.

[0070] For example, S2 provided by the present invention includes:

[0071] Based on the coordinates of the communication nodes in the communication system, the reflection system matrix of the active RIS is obtained using the UAV airborne base station and the uniform rectangular array of the active RIS.

[0072] Based on the LOS and NLOS components of the UAV airborne base station channel, and a pre-defined free space path loss model, the UAV airborne base station channel is obtained.

[0073] Based on the LOS and NLOS components of the active RIS channel, and a pre-defined free-space path loss model, the active RIS channel is obtained.

[0074] Therefore, the distance between the RIS and a certain communication node can be approximated as the distance between the reference point and the corresponding node. Assume that both the UBS-Alice / Eve link and the UBS-RIS link contain line-of-sight (LOS) and non-line-of-sight (NLOS) radio transmission components, which follow a free-space path loss model. Assume that all channels are defined by large-scale fading and small-scale fading, and that small-scale fading in the A2G link can be assumed to be Ricean fading. Specifically, , and It can be modeled as:

[0075] ,

[0076] ,

[0077] (1)

[0078] In the formula, Indicates the UBS-Alice channel; Indicates the UBS-Eve channel; Indicates the UBS-RIS channel; , and Representing the Rice values ​​of the UBS-Alice channel, UBS-Eve channel, and UBS-RIS channel, respectively. factor; and These are the path loss factors for LOS and NLOS, respectively. and These are the path loss coefficients for LOS and NLOS, respectively. and These represent the distances between UBS-Alice, UBS-Eve, and UBS-RIS, respectively.

[0079] The distances between UBS-Alice, UBS-Eve, and UBS-RIS satisfy the following expressions:

[0080] ,

[0081] ,

[0082] (2)

[0083] Furthermore, the channel fading between RIS-Alice and RIS-Eve also follows a Ricean distribution, which can be generated using a similar process and expressed as follows: and .

[0084] In equation (1), the UBS-Alice channel The LOS and NLOS components are respectively represented as and Furthermore, the UBS-Eve and UBS-RIS channels can be represented similarly.

[0085] In addition, NLOS components All follow a cyclic symmetric complex Gaussian distribution with zero mean and unit variance, i.e. .

[0086] LOS weight and It can be represented as:

[0087] ,

[0088] (3)

[0089] In the formula This indicates the azimuth angle of the path between URA and Alice at UBS; The elevation angle AOD of the path between URA and Alice at UBS; This indicates the azimuth of the path between URA and Eve at UBS; The elevation angle (AOD) of the path between URA and Eve at UBS; It is the distance between two adjacent UBS antennas; λ represents the wavelength of the carrier center frequency; Represents the identity matrix; Represents the imaginary unit; This represents the transpose of the matrix.

[0090] It can be represented as: ,

[0091] In the formula, Indicates the array response at RIS; This indicates the array response at UBS.

[0092] in, and All satisfy the following expression:

[0093] (4)

[0094] (5)

[0095] In the formula, Indicates the array response at RIS; Indicates the array response at UBS; This represents the azimuth angle of the path between RIS and Alice. The elevation angle (AOD) of the path between RIS and Alice; This indicates the azimuth angle between URA and RIS at UBS; Indicates the angle of arrival between URA and RIS at UBS; This refers to the antenna spacing of the URA during RIS; This indicates the azimuth angle between URA and RIS at UBS; This indicates the elevation angle AOD between URA and RIS at UBS.

[0096] For example, in S3 provided by the present invention, the present invention also provides a CSI error model that takes into account UAV jitter. Since the vibration characteristics of UAV are caused by a variety of factors, these random vibration characteristics will lead to imperfect CSI estimation and unstable wireless transmission, especially when equipped with a large antenna array.

[0097] For URA, varying elevation angles capture UAV jitter in pitch and roll angles, while varying azimuth angles capture jitter in yaw angles. (Elevation AOD) , and and azimuth , and They respectively satisfy the following expressions:

[0098] ,

[0099] ,

[0100] ,

[0101] ,

[0102] ,

[0103] ,

[0104] ,

[0105] ,

[0106] (6)

[0107] In the formula, This represents the uncertainty of the estimated azimuth angle (AOD) of the path between UBS and Alice. This represents the uncertainty in the estimated azimuth angle (AOD) of the path between UBS and Eve; This represents the uncertainty of the estimated azimuth angle (AOD) of the path between UBS and RIS. This represents the uncertainty of the azimuth angle (AOD) of the path between UBS and Alice; This represents the uncertainty of the azimuth angle (AOD) of the path between UBS and Eve; This represents the uncertainty of the azimuth angle (AOD) of the path between UBS and RIS. This represents the uncertainty in the estimated pitch angle of the path between UBS and Alice; This represents the uncertainty in the estimated pitch angle of the path between UBS and Eve; This represents the uncertainty in the estimated pitch angle of the path between UBS and RIS; This indicates the uncertainty in the pitch angle of the path between UBS and Alice; This indicates the uncertainty in the pitch angle of the path between UBS and Eve; This represents the uncertainty in the pitch angle of the path between UBS and RIS; , and Each represents the set of all possible AOD uncertainties including Alice, Eve, and RIS; Represents the set of real numbers; the uncertainties of Alice's azimuth AOD and elevation AOD change at their maximum values. and Using this as the boundary, the uncertainties of Eve's azimuth AOD and elevation AOD change at their maximum values. and Using this as the boundary, the uncertainties of the azimuth AOD and elevation AOD of the RIS change at their maximum values. and As a boundary.

[0108] because It is about and The nonlinear function; to solve this problem, this paper approximates it by applying Taylor expansion. That is, it satisfies the following expression:

[0109] (7)

[0110] in x , y This represents the estimated values ​​of two independent variables in the function. Therefore, each exponential term in equations (3) and (5) can be approximated by the following expression:

[0111] (8)

[0112] Indicates the edge of the UAV airborne base station antenna x The first axis n Each array element, Indicates the edge of the UAV airborne base station antenna y The first axis n Each array element; and These represent the estimated value and the error value of the azimuth angle AOD, respectively. + and These represent the estimated value and error value of the pitch angle AOD, respectively. To facilitate analysis and calculation, auxiliary variables are defined below. :

[0113] (9)

[0114] (10)

[0115] Then, in equation (1) , and Equations (3) and (5) can be expressed as:

[0116] ,

[0117] ,

[0118] (11)

[0119] In the formula, , , Substituting into equations (9) and (10) respectively, we can obtain

[0120] ,

[0121] ,

[0122] (12)

[0123] in, , and These are used to represent the channel components in the corresponding channel state information that are unaffected by UAV jitter, satisfying the following expressions:

[0124] ,

[0125] ,

[0126] (13)

[0127] In the formula,

[0128] ,

[0129] ,

[0130] ,

[0131] ,

[0132] ,

[0133] ,

[0134] ,

[0135] (14)

[0136] Furthermore, channel variations caused by UAV jitter can lead to channel estimation errors, but these errors cannot be modeled using bounded channel error models or statistical channel error models. Here, , and Satisfy the following expression:

[0137] ,

[0138] ,

[0139] (15)

[0140] in Therefore, in equations (1) and (2) , and It can be rewritten as the following expression:

[0141] ,

[0142] ,

[0143] (16)

[0144] To evaluate the bounded uncertainty of the channel caused by UAV jitter, we further derive... and The CSI error model satisfies the following expression:

[0145] ,

[0146] (17)

[0147] To further simplify the expression, auxiliary variables are introduced and variable substitutions are performed. , , , (6) and (17) can be rewritten as the following expressions:

[0148] ,

[0149] (18)

[0150] In the formula, All represent correction factors; Indicates auxiliary variables; and All represent correction factors; This represents an auxiliary variable.

[0151] Similarly, The CSI error model can satisfy the following expression:

[0152] (19)

[0153] In the formula, and All of these represent correction factors.

[0154] For ease of analysis, channels UBS-RIS-Alice and UBS-RIS-Eve are respectively composed of cascaded channels. and express.

[0155] make and These represent the cascaded channels of RIS at the locations of user Alice and eavesdropper Eve, respectively. and The conjugate transpose of the channels between RIS-Alice and RIS-Eve, where H Indicates conjugate transpose. Cascaded channel. and The CSI error model is expressed as:

[0156] ,

[0157] In the formula, and All are correction factors. It is an auxiliary variable.

[0158] (20)

[0159] It is an auxiliary variable. In the formula,

[0160] ,

[0161] ,

[0162] ,

[0163] ,(twenty one)

[0164] In S4 provided by this invention, the signals received at Alice from both the UBS-Alice and UBS-RIS-Alice channels can be represented by a pre-constructed signal model as follows:

[0165] ,(twenty two)

[0166] The signal received at Eve can be represented as:

[0167] ,(twenty three)

[0168] in, The variance at RIS is... Gaussian white noise, in which ; This indicates that Alice's prescription difference is Gaussian white noise; This indicates that Eve's prescription difference is Gaussian white noise; Represents a data symbol vector with unity power; Represents the transmit beamforming matrix; This represents the multiplication of two matrices; It also represents the multiplication of two matrices.

[0169] It is represented as a matrix containing A vector of diagonal elements, where, any of the first m Each element is represented as .

[0170] Therefore, the achievable rates of Alice and Eve satisfy the following expression:

[0171] ,

[0172] ,(twenty four)

[0173] In the formula,

[0174] ,

[0175] (25)

[0176] In the formula, express The conjugate transpose of; and They represent The estimated value and the error value; and They represent The estimated value and the error value; and They represent The estimated value and the error value; and They represent The estimated value and the error value; and They represent The estimated value and error value.

[0177] In practical applications, the transmit power of UAVs is strictly limited. While ensuring secure communication, the transmit power needs to be reduced as much as possible. Therefore, to reduce the transmit power of an active RIS-assisted UAV system under a given ASR constraint, i.e., in the worst-case scenario where Alice reaches its minimum required data rate and Eve reaches its maximum data rate, and to ensure secure transmission between UBS and Alice, the worst-case confidentiality rate should be greater than 0. Given, satisfying the following expression:

[0178] (26)

[0179] In the formula, Indicates the minimum data rate accepted by a legitimate user; This indicates the maximum data rate that the eavesdropper can receive.

[0180] Since an active RIS amplifies the received signal and noise at each RE, and given that the total power budget and amplification power of the RIS are limited, assuming PF represents the maximum amplification power of the active RIS, which is actually much smaller than that of a conventional RF amplifier, then the following expression holds:

[0181] (27)

[0182] The present invention provides S5, which includes:

[0183] S501, combining the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal, the minimum transmission power of the active RIS-assisted UAV communication system is taken as the optimization problem, and the constraints of the optimization problem are constructed.

[0184] S502, based on the constructed optimization problem and its constraints, an iterative algorithm is used to solve the transmitted beamforming matrix and the reflection coefficient matrix to obtain the optimization results;

[0185] S503, Based on the optimization results, the communication decision of the active RIS-assisted UAV communication system is generated using an equivalent transformation algorithm.

[0186] For example, the optimization problem to be constructed is as follows:

[0187] (P1):

[0188] Optionally, the constraints of the constructed optimization problem satisfy the following expression:

[0189] (28a)

[0190] (28b)

[0191] (28c)

[0192] (28d)

[0193] (28e)

[0194] In the formula, This represents the power of the transmitted beamforming matrix; This represents the constraints on the transmit beamforming matrix; Indicates the minimum data rate accepted by a legitimate user; This indicates the preset data rate threshold for authorized users; Indicates the maximum data rate that the eavesdropper can accept; This indicates the preset data rate threshold that the eavesdropper can accept; Represents the reflection coefficient matrix; This indicates channel fading between the UAV's onboard base station and the active RIS; It is the first m The maximum magnification factor at each RE.

[0195] According to equation (28a), Peak power limited Constraints; at the same time, it can be observed from equation (28d) that , The changes in AOD are highly coupled. Therefore, the optimization problem in equations (28a)-(28e) is non-convex and difficult to solve.

[0196] To address the non-convexity limitation of optimization problems, this invention proposes an AO method that iteratively optimizes... and Specifically, the optimization problem P1 is divided into the following two sub-problems:

[0197] 1) Given a reflection coefficient matrix The transmit beamforming matrix below Optimization;

[0198] 2) Given a transmit beamforming matrix The reflection coefficient matrix below Optimization.

[0199] For example, S502 is specifically implemented as follows:

[0200] Based on the constructed optimization problem, the optimization problem is decomposed to generate optimization sub-problems concerning the transmitted beamforming matrix and the reflection coefficient matrix;

[0201] Based on the constraints of the aforementioned optimization subproblem, the non-convex constraints are transformed into linear matrix inequalities using the S-lemma algorithm. Then, an iterative algorithm is used to iteratively solve the transmitted beamforming matrix and the reflection coefficient matrix to determine the interference and noise power of legitimate users and the interference and noise power of eavesdroppers.

[0202] Based on the aforementioned linear matrix inequality, by introducing slack variables and using the Schur complement lemma algorithm, the linear matrix inequality is equivalently transformed to obtain the transformed optimization problem.

[0203] Based on the transformed optimization problem, the CVX tool is used to solve it and obtain the optimization results.

[0204] Optionally, the optimization problem based on the constructed problem is decomposed into optimization sub-problems, including:

[0205] Based on the constructed optimization problem, given the reflection coefficient matrix, the optimization sub-problem of the transmitted beamforming matrix is ​​obtained;

[0206] Based on the constructed optimization problem, optimization subproblems are generated by transmitting beamforming matrices to produce their respective reflection coefficient matrices.

[0207] To achieve the goal of alternately solving the two subproblems to minimize the transmission power of UBS, the worst-case confidentiality constraint is transformed into a linear matrix inequality using the S-lemma for the non-convex constraint. Since the logarithmic function is monotonically increasing, the channel uncertainty in equations (18) and (20) is considered, and the following expression is defined:

[0208] ,

[0209] ,

[0210] Equations (28b) and (28c) can then be rewritten as the following expressions:

[0211] , (29)

[0212] , (30)

[0213] In the formula, , used to represent Alice's interference plus noise power; , is used to represent the interference plus noise power of Eve.

[0214] Furthermore, a linear approximation of the useful signal power in equation (29) is given in the lemma below.

[0215] Assumption and It is in iteration The optimal solution obtained at that time, then the left side of equation (29) exist( The lower bound of the linearity at () is as follows:

[0216] (31)

[0217] in It represents the independent variable.

[0218] ,

[0219] ,

[0220] ,

[0221] (32)

[0222] Where, in the formula , ,

[0223] ,

[0224] ,

[0225] ,

[0226] ,

[0227] ,

[0228] ,

[0229] (33)

[0230] In the formula, Represents the conjugate operation in a vector form.

[0231] Therefore, equation (29) is equivalently rewritten as:

[0232] (34)

[0233] Similarly, equation (30) can be rewritten equivalently as:

[0234] (35)

[0235] In the formula ;

[0236] ,

[0237] ,

[0238] (36)

[0239]

[0240] In the formula,

[0241] ,

[0242] ,

[0243] ,

[0244] ,

[0245] (37)

[0246] Lemma 2 (S-Lemma): Let the function , , Then it is defined as:

[0247] (38)

[0248] In the formula ,condition Established only if it exists , so that:

[0249] (39)

[0250] for Conversely, conditions Established only if it exists , so that:

[0251] (40)

[0252] Will Rewritten as the following quadratic expression:

[0253] (41)

[0254]

[0255] Then, by introducing as a slack variable and Then, equation (34) can be transformed into the following equivalent LMI by Lemma 1:

[0256] (42)

[0257] (43)

[0258] Introducing as a slack variable and Then, equation (35) can be transformed into the following order LMI:

[0259] ≥0, (44)

[0260] (45)

[0261] Then, using Schur's complement theorem, equation (45) is equivalently transformed into a matrix inequality, satisfying the following expression:

[0262] (46)

[0263] In conclusion, for a given... and The subproblems satisfy the following expression:

[0264]

[0265] st (28a), (42), (44), and (46)(47)

[0266] The problem corresponding to equation (47) is a convex problem, which can be solved directly using the CVX tool.

[0267] Because for a given and Solving the subproblems is a feasibility test. To improve the convergence of the optimization, slack variables are introduced. Rewrite the useful signal power inequality in equation (29) to satisfy the following expression:

[0268] (48)

[0269] Subsequently, LMI equation (42) is rewritten as:

[0270] (49)

[0271] By introducing slack variables Modify the Eve signal power inequality in equation (30) and rewrite it as follows:

[0272] (50)

[0273] And LMI equation (44) is rewritten as:

[0274] ≥0, (51)

[0275] set up ,in , They represent M If there are 1 element; then equation (27) can be expressed as .

[0276] therefore, The subproblem can be represented as:

[0277]

[0278] st (47), (49)

[0279] ,

[0280] (52)

[0281] in, express Problem (52) is a convex optimization problem, which can also be solved efficiently and optimally using the tool CVX.

[0282] This invention provides an active RIS-assisted jitter UAV air-to-ground secure communication method. By constructing the coordinates of each communication node in the communication system and utilizing a pre-defined free-space path loss model, it constructs the UAV onboard base station channel and the active RIS channel. Simultaneously, based on the vibration characteristics of the UAV onboard base station, it utilizes a pre-constructed set of uncertainties in azimuth and elevation angles. By considering the jitter characteristics under the influence of random airflow and airframe vibration, it determines the UAV onboard base station channel error and the active RIS channel error for secure communication. The constructed optimization problem is then iteratively solved to obtain the communication decision of the active RIS-assisted UAV communication system, thereby achieving the goal of reducing the impact of jitter characteristics under the influence of random airflow and airframe vibration on the secure communication of the UAV.

[0283] Optionally, after generating the communication decision of the active RIS-assisted UAV communication system based on the optimization result and using the equivalent transformation algorithm, the method further includes:

[0284] Based on the communication decision of the active RIS-assisted UAV communication system, and combined with the channel uncertainty caused by the jitter of the UAV airborne base station, the changes in the transmission power relative to the elevation angle of the legitimate user and the elevation angle of the eavesdropper are calculated to generate an evaluation result of the active RIS-assisted UAV secure communication.

[0285] For example, assume the UAV coordinates are (10, 20, 10), the RIS coordinates are (10, 0, 10), Alice's coordinates are (20, 20, 0), and Eve's coordinates are (10, 40, 0). Assume UBS is equipped with... =2 transmitting antennas, = , =30dB, =4.5, =1, environmental parameters =5, = Meanwhile, the simulation assumes a maximum transmit power. = Path loss factor =-2.14 , =-3.14 Path loss index =2.09, =3.75. Noise power is -10 The CSI error bound caused by UAV jitter can be defined as follows: and In addition, error tolerance is set. .

[0286] To demonstrate the superiority of the proposed scheme (denoted as "active RIS"), the results are compared with the benchmark scheme, namely a similar scheme assisted by passive RIS.

[0287] To assess the impact of channel uncertainty caused by UAV jitter on active RIS-assisted UAV secure communication. Figure 3 It shows the maximum change in transmit power. Compared to Alice's AOD The ratio, Figure 4 Shows the maximum change in transmit power Compared to Eve's AOD The ratio of .

[0288] Due to the angle of elevation Analysis and azimuth The analysis is similar; here we take the angle of elevation as an example. Figure 3 middle Similarly, Figure 4 middle It can be seen that the transmit power at UBS increases with the increase of AOD uncertainty. This means that the more severe the UAV jitter, the more transmit power is required to meet the requirements of legitimate link validity and confidential signal security. Furthermore, the active RIS scheme can improve confidentiality performance with only a small number of REs, i.e., reducing UAV transmit power under the same ASR. As the number of REs in the active RIS increases, the required transmit power also increases because the amplification effect of noise and channel error by the active RIS also increases.

[0289] Assumption and , Figure 5The relationship between transmit power and RE number in a RIS-assisted system was compared. In this setup, a passive RIS can use up to 90 REs to reflect the incident signal. However, even with 90 REs, the transmit power of the passive RIS is greater than that of a system equipped with a dedicated RIS-assisted system. One (best) The transmit power of an active RIS antenna is limited because an active RIS can directly amplify the incident signal. Conversely, an active RIS requires only a small number of REs (around 15-20) to achieve optimal security performance at different amplitude gains. Unlike passive RIS, where thermal noise is negligible when passively reflecting signals, active RIS introduces and amplifies non-negligible thermal noise while amplifying the reflected signal. Therefore, the performance gain does not continuously increase as the number of REs in an active RIS increases. In practice, active RIS designs typically use fewer REs. Due to the fewer REs, active RIS also have a smaller surface area, making them more suitable for payload-constrained UAV secure communication.

[0290] Example 2:

[0291] Based on the same inventive concept, the present invention also provides an active RIS-assisted jitter UAV air-to-ground secure communication system, the system comprising:

[0292] The coordinate determination module is used to obtain the coordinates of each communication node in the UAV communication system based on a preset active RIS-assisted communication system using a three-dimensional coordinate system. The communication nodes include UAV airborne base stations, active RIS, legitimate users, and eavesdroppers.

[0293] The channel construction module is used to construct UAV airborne base station channels and active RIS channels based on the coordinates of communication nodes in the communication system and using a preset free space path loss model. The UAV airborne base station channels include channels between the UAV airborne base station and the active RIS, channels between the UAV airborne base station and legitimate users, and channels between the UAV airborne base station and eavesdroppers. The active RIS channels include channels between the active RIS and legitimate users and channels between the active RIS and eavesdroppers.

[0294] The error confirmation module is used to determine the channel error of the UAV airborne base station and the active RIS channel error based on the vibration characteristics of the UAV airborne base station and by using a pre-constructed set of uncertainties in azimuth and elevation angles.

[0295] The signal confirmation module is used to confirm the signals received by legitimate users and the signals received by eavesdroppers based on the UAV's onboard base station channel and active RIS channel.

[0296] The decision generation module is used to integrate the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal. Taking the minimum transmission power of the active RIS-assisted UAV communication system as the optimization objective, the module uses an iterative algorithm to solve the transmission beamforming matrix and the reflection coefficient matrix to obtain the optimization result and generate the communication decision of the active RIS-assisted UAV communication system.

[0297] Example 3:

[0298] like Figure 6 As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0299] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to implement the corresponding method flow or corresponding function, so as to realize the steps of the active RIS-assisted jitter UAV air-to-ground secure communication method in the above embodiments.

[0300] Example 4:

[0301] Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the active RIS-assisted jitter UAV air-to-ground secure communication method described in the above embodiments.

[0302] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0303] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0304] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0305] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0306] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for secure air-to-ground communication of UAVs with active RIS-assisted jitter, characterized in that, include: Based on the communication nodes in the pre-defined active RIS-assisted UAV communication system, the coordinates of each communication node in the communication system are obtained using a three-dimensional coordinate system. The communication nodes include UAV airborne base stations, active RIS, legitimate users, and eavesdroppers. Based on the coordinates of the communication nodes in the communication system, and using a preset free space path loss model, an UAV airborne base station channel and an active RIS channel are constructed. The UAV airborne base station channel includes the channel between the UAV airborne base station and the active RIS, the channel between the UAV airborne base station and the legitimate user, and the channel between the UAV airborne base station and the eavesdropper. The active RIS channel includes the channel between the active RIS and the legitimate user and the channel between the active RIS and the eavesdropper. Based on the vibration characteristics of UAV airborne base stations, the channel error of UAV airborne base stations and the active RIS channel error are determined by using a pre-constructed set of uncertainties in azimuth and elevation angles. Based on the UAV's onboard base station channel and active RIS channel, the signals received by legitimate users and those received by eavesdroppers are confirmed. By combining the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal, the minimum transmission power of the active RIS-assisted UAV communication system is taken as the optimization problem. Using an iterative algorithm, the transmission beamforming matrix and the reflection coefficient matrix are solved to obtain the optimization result, and the communication decision of the active RIS-assisted UAV communication system is generated.

2. The active RIS-assisted jitter UAV air-to-ground secure communication method as described in claim 1, characterized in that, The method integrates the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal. Minimizing the transmit power of the active RIS-assisted UAV communication system is taken as the optimization problem. An iterative algorithm is used to solve for the transmit beamforming matrix and the reflection coefficient matrix to obtain the optimization result. The communication decision of the active RIS-assisted UAV communication system is then generated, including: By combining the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal, the minimum transmission power of the active RIS-assisted UAV communication system is taken as the optimization problem, and the constraints of the optimization problem are constructed. Based on the constructed optimization problem and its constraints, an iterative algorithm is used to solve the transmitted beamforming matrix and the reflection coefficient matrix to obtain the optimization results. Based on the optimization results, the communication decision of the active RIS-assisted UAV communication system is generated using the equivalent transformation algorithm.

3. The active RIS-assisted jitter UAV air-to-ground secure communication method as described in claim 2, characterized in that, The constraints of the constructed optimization problem satisfy the following expression: ， ， ， ， ， In the formula, This represents the power of the transmitted beamforming matrix; This represents the constraints on the transmit beamforming matrix; Indicates the minimum data rate accepted by a legitimate user; This indicates the preset data rate threshold for authorized users; Indicates the maximum data rate that the eavesdropper can accept; This indicates the preset data rate threshold that the eavesdropper can accept; Represents the reflection coefficient matrix; This indicates channel fading between the UAV's onboard base station and the active RIS; It is the first m The maximum magnification factor at each RE.

4. The active RIS-assisted jitter UAV air-to-ground secure communication method as described in claim 2, characterized in that, Based on the constructed optimization problem and constraints, an iterative algorithm is used to solve the transmitted beamforming matrix and the reflection coefficient matrix to obtain the optimization results, including: Based on the constructed optimization problem, the optimization problem is decomposed to generate optimization sub-problems concerning the transmitted beamforming matrix and the reflection coefficient matrix; Based on the constraints of the aforementioned optimization subproblem, the non-convex constraints are transformed into linear matrix inequalities using the S-lemma algorithm. Then, an iterative algorithm is used to iteratively solve the transmitted beamforming matrix and the reflection coefficient matrix to determine the interference and noise power of legitimate users and the interference and noise power of eavesdroppers. Based on the aforementioned linear matrix inequality, by introducing slack variables and using the Schur complement lemma algorithm, the linear matrix inequality is equivalently transformed to obtain the transformed optimization problem; Based on the transformed optimization problem, the CVX tool is used to solve it and obtain the optimization results.

5. The active RIS-assisted jitter UAV air-to-ground secure communication method as described in claim 4, characterized in that, The optimization problem based on the construction is decomposed into optimization sub-problems, including: Based on the constructed optimization problem, given the reflection coefficient matrix, the optimization sub-problem of the transmitted beamforming matrix is ​​obtained; Based on the constructed optimization problem, optimization subproblems are generated by transmitting beamforming matrices to produce their respective reflection coefficient matrices.

6. The active RIS-assisted jitter UAV air-to-ground secure communication method as described in claim 1, characterized in that, Based on the coordinates of the communication nodes in the communication system, and using a preset free-space path loss model, the UAV-borne base station channel and active RIS channel are constructed, including: Based on the coordinates of the communication nodes in the communication system, the reflection system matrix of the active RIS is obtained using the UAV airborne base station and the uniform rectangular array of the active RIS. Based on the LOS and NLOS components of the UAV airborne base station channel, and a pre-defined free space path loss model, the UAV airborne base station channel is obtained. Based on the LOS and NLOS components of the active RIS channel, and a pre-defined free-space path loss model, the active RIS channel is obtained.

7. The active RIS-assisted jitter UAV air-to-ground secure communication method as described in claim 2, characterized in that, After generating the communication decision of the active RIS-assisted UAV communication system based on the optimization results and using the equivalent transformation algorithm, the process further includes: Based on the communication decision of the active RIS-assisted UAV communication system, and combined with the channel uncertainty caused by the jitter of the UAV airborne base station, the changes in the transmission power relative to the elevation angle of the legitimate user and the elevation angle of the eavesdropper are calculated to generate an evaluation result of the active RIS-assisted UAV secure communication.

8. An active RIS-assisted jitter UAV air-to-ground secure communication system, characterized in that, The system includes: The coordinate determination module is used to obtain the coordinates of each communication node in the UAV communication system based on a preset active RIS-assisted communication system using a three-dimensional coordinate system. The communication nodes include UAV airborne base stations, active RIS, legitimate users, and eavesdroppers. The channel construction module is used to construct UAV airborne base station channels and active RIS channels based on the coordinates of communication nodes in the communication system and using a preset free space path loss model. The UAV airborne base station channels include channels between the UAV airborne base station and the active RIS, channels between the UAV airborne base station and legitimate users, and channels between the UAV airborne base station and eavesdroppers. The active RIS channels include channels between the active RIS and legitimate users and channels between the active RIS and eavesdroppers. The error confirmation module is used to determine the channel error of the UAV airborne base station and the active RIS channel error based on the vibration characteristics of the UAV airborne base station and by using a pre-constructed set of uncertainties in azimuth and elevation angles. The signal confirmation module is used to confirm the signals received by legitimate users and the signals received by eavesdroppers based on the UAV's onboard base station channel and active RIS channel. The decision generation module is used to integrate the reflection coefficient matrix of the active RIS, the UAV airborne base station channel, the active RIS channel, the UAV airborne base station channel error, the active RIS channel error, the legitimate user received signal, and the eavesdropper received signal. Taking the minimum transmission power of the active RIS-assisted UAV communication system as the optimization objective, the module uses an iterative algorithm to solve the transmission beamforming matrix and the reflection coefficient matrix to obtain the optimization result and generate the communication decision of the active RIS-assisted UAV communication system.

9. An electronic device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, an active RIS-assisted jitter UAV air-to-ground secure communication method as described in any one of claims 1 to 7 is implemented.

10. A readable storage medium, characterized in that, It contains an executable program, which, when executed, implements an active RIS-assisted jitter UAV air-to-ground secure communication method as described in any one of claims 1 to 7.

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