Quadrotor UAV trajectory control method and device under cyberattack

Abstract

This invention provides a method and apparatus for trajectory control of a quadcopter unmanned aerial vehicle (UAV) under network attack. The method includes acquiring the UAV's state information, position information, and attitude angle information; establishing a mathematical model and a trajectory tracking control model for the UAV based on the state information, position information, and attitude angle information; acquiring the attacker's state information and signal information when the UAV is under a fake data injection attack; establishing an attack model and an attack detection model for the UAV based on the state information and signal information; performing tracking performance processing on the UAV based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model to obtain a state observation model for the UAV; and using the state observation model to perform trajectory tracking control on the UAV.

Description

Technical Field

[0001] This invention relates to the field of remote control technology for unmanned aerial vehicles (UAVs), and in particular to a method and apparatus for trajectory control of a quadcopter UAV in the event of a cyberattack. Background Technology

[0002] In recent years, security status estimation and control have attracted increasing attention from researchers. For remotely controlled unmanned aerial vehicle (UAV) systems, control is achieved through wireless network communication, making them vulnerable to malicious attacks. These attacks primarily include communication channels between the ground control station and the UAV, communication channels between multiple UAVs, and communication between satellite navigation signals. Therefore, research on remote control of UAVs under attack is crucial. Summary of the Invention

[0003] This invention provides a method and apparatus for trajectory control of a quadcopter drone under network attack, which solves the technical problem of remote control of drones under attack.

[0004] This invention provides a method for trajectory control of a quadcopter drone under network attack, the method comprising:

[0005] Acquire the drone's status, position, and attitude angle information;

[0006] A mathematical model and a trajectory tracking control model for the UAV are established based on the state information, the position information, and the attitude angle information.

[0007] In the event that the drone is subjected to a fake data injection attack, the attacker's status information and signal information can be obtained;

[0008] An attack model and an attack detection model for the UAV are established based on the state information and the signal information.

[0009] Based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model, the UAV's tracking performance is processed to obtain the UAV's state observation model; the state observation model is used for trajectory tracking control of the UAV.

[0010] In some implementations, the attitude angle information includes the pitch angle, yaw angle, and roll angle information of the UAV; the step of establishing a mathematical model and trajectory tracking control model for the UAV based on the state information, the position information, and the attitude angle information includes:

[0011] The rotation information of the UAV is determined based on the pitch angle information, the yaw angle information, and the roll angle information;

[0012] A mathematical model of the UAV is established based on the state information, position information, rotation information, and attitude angle information;

[0013] Obtain the desired trajectory and speed information of the drone;

[0014] The position tracking error information and velocity tracking error information of the UAV are determined based on the trajectory information and the velocity information;

[0015] A trajectory tracking control model for the UAV is established based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information.

[0016] In some embodiments, the rotation information includes at least rotation matrices in both body coordinate system and inertial coordinate system; determining the rotation information of the UAV based on the pitch angle information, the yaw angle information, and the roll angle information includes:

[0017] The rotation matrix of the UAV in the body coordinate system and the inertial coordinate system is determined based on the pitch angle information, the yaw angle information and the roll angle information.

[0018] In some embodiments, the state information includes at least the speed information, acceleration information, noise information, and mass information of the UAV; the step of establishing a mathematical model of the UAV based on the state information, the position information, the rotation information, and the attitude angle information includes:

[0019] A mathematical model of the UAV is established based on its speed information, acceleration information, noise information, mass information, position information, rotation information, and attitude angle information.

[0020] In some implementations, establishing the trajectory tracking control model of the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information includes:

[0021] The attitude angle tracking error information of the UAV is determined based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information.

[0022] The desired propeller torque information of the UAV is determined based on the attitude angle tracking error information of the UAV.

[0023] A trajectory tracking control model for the UAV is established based on the expected propeller torque information of the UAV.

[0024] In some implementations, establishing the attack model and attack detection model for the UAV based on the state information and the signal information includes:

[0025] Based on the state information and the signal information, the desired trajectory information and control signal information received by the UAV are determined;

[0026] An attack model for the UAV is established based on the desired trajectory information and the control signal information;

[0027] Based on the signal information, the expected trajectory information, and the control signal information, determine the position tracking error information and velocity tracking error information when the UAV is subjected to a false data injection attack;

[0028] An attack detection model for the UAV is established based on the position tracking error information and the velocity tracking error information.

[0029] In some embodiments, the method further includes:

[0030] The desired trajectory information received by the UAV is encrypted using a first preset function to obtain encrypted desired trajectory information;

[0031] The encrypted desired trajectory information is decrypted using a second preset function to obtain the decrypted desired trajectory information.

[0032] In some embodiments, the trajectory tracking control model includes a trajectory tracking control model based on a fully symmetric polytope; the step of establishing the trajectory tracking control model of the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information includes:

[0033] The position tracking error information and the velocity tracking error information are processed by a fully symmetric polytope to obtain the tracking error set information of the UAV.

[0034] A trajectory tracking control model for the UAV is established based on the UAV's tracking error set information, state information, position information, rotation information, and attitude angle information.

[0035] This invention also provides a trajectory control device for a quadcopter drone in the event of a network attack, the device comprising:

[0036] The first acquisition module is used to acquire the UAV's status information, position information, and attitude angle information;

[0037] The first modeling module is used to establish a mathematical model and a trajectory tracking control model for the UAV based on the state information, the position information and the attitude angle information.

[0038] The second acquisition module is used to acquire the attacker's status information and signal information when the drone is subjected to a fake data injection attack.

[0039] The second module establishes an attack model and an attack detection model for the UAV based on the state information and the signal information.

[0040] The processing module is used to perform tracking performance processing on the UAV based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model to obtain the state observation model of the UAV; the state observation model is used to perform trajectory tracking control on the UAV.

[0041] This invention provides a trajectory control device for a quadcopter drone in the event of a network attack. The device includes a processor and a memory for storing a computer program that can run on the processor. When the processor runs the computer program, it executes the steps of any of the methods described above.

[0042] This invention provides a method for trajectory control of a quadcopter unmanned aerial vehicle (UAV) under network attack. The method includes: acquiring the UAV's state information, position information, and attitude angle information; establishing a mathematical model and a trajectory tracking control model for the UAV based on the state information, position information, and attitude angle information; acquiring the attacker's state information and signal information when the UAV is under a fake data injection attack; establishing an attack model and an attack detection model for the UAV based on the state information and signal information; performing tracking performance processing on the UAV based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model to obtain a state observation model for the UAV; and using the state observation model for trajectory tracking control of the UAV. The technical solution of this application establishes a mathematical model and a trajectory tracking control model for the UAV using the acquired UAV's state information, position information, and attitude angle information; acquires the attacker's state information and signal information when the UAV is under a fake data injection attack, thereby establishing an attack model and an attack detection model for the UAV; and performs tracking performance processing on the UAV based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model to obtain a state observation model for trajectory tracking control of the UAV. Specifically, for UAV control systems containing unknown but bounded noise, considering the possibility of false data injection attacks between the ground station and the UAV, a state observation model was designed to solve the UAV state estimation problem under this condition. This model was then used to solve the attack detection problem and also to solve the state estimation and control problem under unknown noise and interference statistical characteristics. Attached Figure Description

[0043] Figure 1 A flowchart illustrating a method for controlling the trajectory of a quadcopter drone under network attack, provided as an embodiment of the present invention;

[0044] Figure 2 A schematic diagram illustrating an application scenario of trajectory control methods for quadcopter drones under cyberattacks.

[0045] Figure 3 This is a schematic diagram of the structure of a quadcopter drone trajectory control device under network attack conditions, provided in an embodiment of the present invention.

[0046] Figure 4 This is a schematic diagram of a hardware structure for a quadcopter drone trajectory control device under network attack conditions, according to an embodiment of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0048] The specific technical features described in the various embodiments in the detailed implementation can be combined in various ways without contradiction. For example, different implementation methods can be formed by combining different specific technical features. In order to avoid unnecessary repetition, the various possible combinations of the specific technical features in this invention will not be described separately.

[0049] It should also be noted that, in order to avoid obscuring the present invention with unnecessary details, only the structures and / or processing steps closely related to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0050] Additionally, it should be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. In the following description, the terms "first," "second," etc., are used merely to distinguish different objects and do not indicate any similarity or connection between them. It should be understood that the directional descriptions such as "above," "below," "inside," and "outside" refer to the orientation under normal use conditions.

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the specific technical solutions of the invention will be further described in detail below with reference to the accompanying drawings of the embodiments of the present invention. The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0052] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0053] This invention provides a method for trajectory control of a quadcopter drone under network attack conditions, such as... Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for controlling the trajectory of a quadcopter drone under network attack conditions, provided by an embodiment of the present invention; the method includes:

[0054] Step S101: Obtain the UAV's status information, position information, and attitude angle information.

[0055] Step S102: Establish a mathematical model and trajectory tracking control model for the UAV based on the state information, the position information and the attitude angle information.

[0056] Step S103: In the event that the drone is subjected to a fake data injection attack, obtain the attacker's status information and signal information.

[0057] Step S104: Establish the attack model and attack detection model of the UAV based on the state information and the signal information.

[0058] Step S105: Based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model, perform tracking performance processing on the UAV to obtain the state observation model of the UAV; the state observation model is used to perform trajectory tracking control on the UAV.

[0059] In this embodiment, the drone can be determined according to the actual situation and is not limited here. As an example, the drone can be a quadcopter drone.

[0060] The trajectory control method for a quadcopter drone under network attack conditions can be determined based on the actual situation and is not limited here. As an example, the trajectory control method for a quadcopter drone under network attack conditions can be any method for controlling the trajectory of a quadcopter drone under network attack conditions.

[0061] In step S101, the state information, position information, and attitude angle information can all be determined according to actual conditions, and are not limited here. As an example, the state information at least includes the speed information, acceleration information, noise information, and mass information of the UAV; wherein, the speed information of the UAV can be denoted as... The acceleration information can be gravitational acceleration, which can be denoted as... The location information can be obtained through vectors. To describe, These respectively represent the drones in x , y and z The orientation and position. The attitude angle information includes the pitch angle, yaw angle, and roll angle information of the UAV; wherein, the pitch angle information can be simply referred to as the pitch angle, and can be denoted as... The yaw angle information can be simply referred to as the yaw angle, and can be denoted as... The roll angle information can be simply referred to as the roll angle, and can be denoted as... .

[0062] In step S102, the specific process of establishing the mathematical model and trajectory tracking control model of the UAV based on the state information, position information, and attitude angle information can be determined according to the actual situation and is not limited here. As an example, the attitude angle information includes the pitch angle information, yaw angle information, and roll angle information of the UAV; establishing the mathematical model and trajectory tracking control model of the UAV based on the state information, position information, and attitude angle information may include determining the rotation information of the UAV based on the pitch angle information, yaw angle information, and roll angle information; establishing the mathematical model of the UAV based on the state information, position information, rotation information, and attitude angle information; obtaining the UAV's desired trajectory information and velocity information; determining the UAV's position tracking error information and velocity tracking error information based on the trajectory information and velocity information; and establishing the UAV's trajectory tracking control model based on the position tracking error information, velocity tracking error information, state information, position information, rotation information, and attitude angle information.

[0063] In step S103, the presence of a fake data injection attack on the drone can be determined based on the actual situation and is not limited here. As an example, the presence of a fake data injection attack on the drone can be understood as a fake data injection attack by an attacker or a network attack.

[0064] The attacker's state and signal information can be determined based on the actual situation and are not limited here. As an example, the attacker's state information may include the attack system state, attack system matrix, etc.; wherein, the attack system state can be denoted as... The attack system matrix can be denoted as... The signal information may include attack signals, which can be denoted as... .

[0065] In step S104, the establishment of the attack model and attack detection model for the UAV based on the state information and the signal information can be determined according to the actual situation and is not limited here. As an example, the state information includes at least the speed information, acceleration information, noise information, and mass information of the UAV; the establishment of the mathematical model of the UAV based on the state information, the position information, the rotation information, and the attitude angle information may include establishing the mathematical model of the UAV based on the speed information, acceleration information, noise information, mass information, position information, rotation information, and attitude angle information.

[0066] In step S105, the specific processing steps in the UAV tracking performance processing based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model to obtain the UAV's state observation model can be determined according to the actual situation and are not limited here. As an example, the trajectory tracking control model includes a trajectory tracking control model based on a fully symmetric polytope; establishing the UAV's trajectory tracking control model based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information may include performing fully symmetric polytope processing on the position tracking error information and the velocity tracking error information to obtain the UAV's tracking error set information; establishing the UAV's trajectory tracking control model based on the UAV's tracking error set information, the state information, the position information, the rotation information, and the attitude angle information.

[0067] This invention provides a trajectory control method for a quadcopter unmanned aerial vehicle (UAV) under network attacks. A mathematical model and a trajectory tracking control model for the UAV are established using acquired UAV state, position, and attitude angle information. In the case of a spoofing attack, the attacker's state and signal information are acquired to establish an attack model and an attack detection model for the UAV. Based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model, the UAV's tracking performance is processed to obtain a state observation model for trajectory tracking control. Specifically, for UAV control systems containing unknown but bounded noise, considering the possibility of spoofing attacks between the ground station and the UAV, a state observation model is designed to solve the UAV state estimation problem in this situation. This model is also used to solve the attack detection problem and addresses the state estimation and control problem under unknown noise and interference statistical characteristics.

[0068] In some embodiments, the attitude angle information includes the pitch angle information, yaw angle information, and roll angle information of the UAV; the step of establishing a mathematical model and trajectory tracking control model of the UAV based on the state information, the position information, and the attitude angle information includes:

[0069] The rotation information of the UAV is determined based on the pitch angle information, the yaw angle information, and the roll angle information;

[0070] A mathematical model of the UAV is established based on the state information, position information, rotation information, and attitude angle information;

[0071] Obtain the desired trajectory and speed information of the drone;

[0072] The position tracking error information and velocity tracking error information of the UAV are determined based on the trajectory information and the velocity information;

[0073] A trajectory tracking control model for the UAV is established based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information.

[0074] In this embodiment, the attitude angle information includes the pitch angle information, yaw angle information, and roll angle information of the UAV; wherein, the pitch angle information can be simply referred to as the pitch angle, and can be denoted as... The yaw angle information can be simply referred to as the yaw angle, and can be denoted as... The roll angle information can be simply referred to as the roll angle, and can be denoted as... .

[0075] The specific determination process for determining the rotation information of the UAV based on the pitch angle information, yaw angle information, and roll angle information can be determined according to actual circumstances and is not limited here. As an example, the rotation information at least includes rotation matrices in the body coordinate system and the inertial coordinate system; determining the rotation information of the UAV based on the pitch angle information, yaw angle information, and roll angle information may include determining the rotation matrix of the UAV in the body coordinate system and the inertial coordinate system based on the pitch angle information, yaw angle information, and roll angle information.

[0076] The specific process of establishing the mathematical model of the UAV based on the state information, position information, rotation information, and attitude angle information can be determined according to the actual situation and is not limited here. As an example, the state information includes at least the speed information, acceleration information, noise information, and mass information of the UAV; the process of establishing the mathematical model of the UAV based on the state information, position information, rotation information, and attitude angle information may include establishing the mathematical model of the UAV based on the speed information, acceleration information, noise information, mass information, position information, rotation information, and attitude angle information.

[0077] The specific process of establishing the trajectory tracking control model of the UAV based on the position tracking error information, velocity tracking error information, state information, position information, rotation information, and attitude angle information can be determined according to the actual situation and is not limited here. As an example, establishing the trajectory tracking control model of the UAV based on the position tracking error information, velocity tracking error information, state information, position information, rotation information, and attitude angle information may include determining the attitude angle tracking error information of the UAV based on the position tracking error information, velocity tracking error information, state information, position information, rotation information, and attitude angle information; determining the desired propeller torque information of the UAV based on the attitude angle tracking error information of the UAV; and establishing the trajectory tracking control model of the UAV based on the desired propeller torque information of the UAV.

[0078] In some embodiments, the rotation information includes at least rotation matrices in the body coordinate system and the inertial coordinate system; determining the rotation information of the UAV based on the pitch angle information, the yaw angle information, and the roll angle information includes:

[0079] The rotation matrix of the UAV in the body coordinate system and the inertial coordinate system is determined based on the pitch angle information, the yaw angle information and the roll angle information.

[0080] In this embodiment, the attitude angle information includes the pitch angle information, yaw angle information, and roll angle information of the UAV; wherein, the pitch angle information can be simply referred to as the pitch angle, and can be denoted as... The yaw angle information can be simply referred to as the yaw angle, and can be denoted as... The roll angle information can be simply referred to as the roll angle, and can be denoted as... .

[0081] In practical applications, as an example, consider the trajectory control of a quadcopter drone, where its position is determined by vectors. To describe, These respectively represent the drones in x , y and z The orientation and position. Furthermore, the rotation matrix between the body coordinate system and the inertial coordinate system is calculated as follows:

[0082]

[0083] In some embodiments, the state information includes at least the speed information, acceleration information, noise information, and mass information of the UAV; the step of establishing a mathematical model of the UAV based on the state information, the position information, the rotation information, and the attitude angle information includes:

[0084] A mathematical model of the UAV is established based on its speed information, acceleration information, noise information, mass information, position information, rotation information, and attitude angle information.

[0085] In this embodiment, the speed information of the UAV can be simply referred to as the speed of the UAV, and can be denoted as... The acceleration information may include gravitational acceleration; the gravitational acceleration may be denoted as... The noise information may include unknown but bounded noise, which can be denoted as... The quality information may include the mass of the UAV, which can be denoted as... m。

[0086] In practical applications, as an example, the drone can be a quadcopter drone, and the mathematical model of the quadcopter drone can be as follows:

[0087] , ,

[0088] in, For drone speed, It is the acceleration due to gravity. , For propeller torque, m For the quality of drones, f For thrust, and Let these represent the diagonal moments of the inertial tensor and the eccentric Coriolis matrix, respectively. For unknown but bounded noise, satisfying Assume the initial conditions are satisfied. and ,in Indicates the center point as The generating matrix is The fully symmetrical multicellular form; similarly The center point is indicated as The generating matrix is It is a fully symmetrical multicellular structure.

[0089] In some embodiments, establishing the trajectory tracking control model of the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information includes:

[0090] The attitude angle tracking error information of the UAV is determined based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information.

[0091] The desired propeller torque information of the UAV is determined based on the attitude angle tracking error information of the UAV.

[0092] A trajectory tracking control model for the UAV is established based on the expected propeller torque information of the UAV.

[0093] In this embodiment, the trajectory tracking control model can be determined according to the actual situation, and is not limited here. As an example, the trajectory tracking control model can also be called a trajectory tracking controller.

[0094] Both the position tracking error information and the velocity tracking error information can be determined according to the actual situation, and are not limited here. As an example, the position tracking error information can be simply referred to as position tracking error, and can be denoted as... The speed tracking error information can be simply referred to as speed tracking error, and can be denoted as... In practical applications, the drone tracking the desired trajectory can be denoted as... The desired speed can be denoted as The position tracking error is... The speed tracking error is

[0095] The specific determination process for determining the attitude angle tracking error information of the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information can be determined according to actual conditions and is not limited here. The attitude angle tracking error information can be abbreviated as attitude angle tracking error, and can be denoted as... ; ,in .

[0096] The specific determination process for determining the desired propeller torque information of the UAV based on its attitude angle tracking error information can be determined according to actual circumstances and is not limited here. As an example, the desired propeller torque information of the UAV can be simply referred to as the desired propeller torque, and can be denoted as... ; ;in, and This is the attitude control gain matrix, used to control the attitude tracking error to approach zero.

[0097] The specific determination process for establishing the trajectory tracking control model of the UAV based on the expected propeller torque information of the UAV can be determined according to the actual situation and is not limited here. As an example, the trajectory tracking control model of the UAV may include the thrust of each propeller. Based on the obtained thrust and propeller torque The calculation results can be used to calculate the thrust of each propeller. , ,Right now

[0098] ;

[0099] in, , and These are the known parameters related to the structure of the quadcopter drone.

[0100] In practical applications, as an example, a trajectory tracking controller is designed to enable a drone to track a desired trajectory. and expected speed The position tracking error is defined as... The speed tracking error is Therefore, the drone tracking controller is designed as follows:

[0101] ;

[0102] in, , , and This is the controller gain. Because the controller contains... Therefore, the expected trajectory It must be continuously differentiable. From the above equation, we can obtain the following relationship:

[0103] ;

[0104] ;

[0105] ;

[0106] in, and These are the desired pitch and roll angles, respectively. This invention assumes the desired yaw angle is zero, i.e. .

[0107] Controller gain and This can be obtained by solving the following inequality, namely

[0108] ;

[0109] In this context, the asterisk (*) represents a symmetric element of the matrix. Given parameters, P 1. P 2 and X p The parameter matrix to be determined can be obtained using the inequalities above; after obtaining it, we can get... , .

[0110] Define the attitude angle tracking error as ,in Therefore, the desired propeller torque The design can be as follows:

[0111] ;

[0112] in, and This is the attitude control gain matrix, used to control the attitude tracking error to approach zero.

[0113] Based on the obtained thrust and propeller torque The calculation results can be used to calculate the thrust of each propeller. , ,Right now

[0114] ;

[0115] in, , and These are the known parameters related to the structure of the quadcopter drone.

[0116] In some embodiments, establishing the attack model and attack detection model of the UAV based on the state information and the signal information includes:

[0117] Based on the state information and the signal information, the desired trajectory information and control signal information received by the UAV are determined;

[0118] An attack model for the UAV is established based on the desired trajectory information and the control signal information;

[0119] Based on the signal information, the expected trajectory information, and the control signal information, determine the position tracking error information and velocity tracking error information when the UAV is subjected to a false data injection attack;

[0120] An attack detection model for the UAV is established based on the position tracking error information and the velocity tracking error information.

[0121] In this embodiment, the status information may include the attack system status and the attack system matrix; wherein, the attack system status can be denoted as... The attack system matrix can be denoted as... and .

[0122] The desired trajectory information and control signal information received by the UAV can be determined according to the actual situation, and are not limited here. As an example, the desired trajectory information received by the UAV can be simply referred to as the desired trajectory, and can be denoted as... The control signal information can be simply referred to as control signal, and can be denoted as... u .

[0123] The specific determination process for determining the desired trajectory information and control signal information received by the UAV based on the state information and the signal information can be determined according to the actual situation and is not limited here. As an example, an attacker's fake data injection attack design is as follows:

[0124] , ;

[0125] in, To attack the system state, and For attacking the system matrix, The attack signal is designed for the attacker. Considering that the attacker alters the drone's flight path by attacking the reference trajectory, the desired trajectory received by the drone controller... Become The control signal also changed from u to ua.

[0126] The specific process of establishing the attack model of the UAV based on the expected trajectory information and the control signal information can be determined according to the actual situation and is not limited here. As an example, ;in, .

[0127] The specific determination process for the position tracking error information and velocity tracking error information when the UAV is subjected to a fake data injection attack, based on the signal information, the expected trajectory information, and the control signal information, can be determined according to the actual situation and is not limited here. As an example, the position tracking error information can be simply referred to as position tracking error, and can be denoted as... The speed tracking error information can be simply referred to as speed tracking error, and can be denoted as... When a fake data injection attack occurs, the corresponding position and velocity tracking errors become... and .

[0128] The specific process for establishing the attack detection model for the UAV based on the position tracking error information and the velocity tracking error information can be determined according to the actual situation and is not limited here. As an example, to ensure that attackers cannot obtain the real reference trajectory information, this invention proposes an encryption and decryption method to process the relevant data, namely, using a function... To encrypt the expected trajectory And the function It is monotonically invertible, therefore the corresponding decryption function is: For ease of analysis, this application only discusses functions. For the linear case, i.e. ;in, and For design parameters, and , These are random numbers. For simplicity of analysis, we choose... In addition, parameters It can be generated using a pseudo-random number generator. Therefore, it can be obtained through calculation. From the above formula, we can derive... Therefore, by selecting appropriate parameters... It can be changed arbitrarily. The size of the attack detector. Based on this, the attack detector is designed as follows:

[0129] ;

[0130] Among them, parameters Attack detector thresholds designed for defenders. However, when The value is very large, while the parameter When the threshold is very small, the false positive rate can be extremely high. If the target value is too large, the attack detection rate will decrease. To resolve this contradiction, this invention will use position tracking error to design the attack detector, i.e.

[0131] ;

[0132] in, , The attack detector threshold designed for defenders, and The value can be greater than Small. To reduce false alarm rate and improve detection rate, the threshold is... The design is as follows:

[0133] ;

[0134] Where s is a matrix The number of columns, and The center point and generator matrix of the position tracking error set.

[0135] In some embodiments, the method further includes:

[0136] The desired trajectory information received by the UAV is encrypted using a first preset function to obtain encrypted desired trajectory information;

[0137] The encrypted desired trajectory information is decrypted using a second preset function to obtain the decrypted desired trajectory information.

[0138] In this embodiment, both the first preset function and the second preset function can be determined according to actual conditions, and no limitation is made here. As an example, the first preset function can be... The second preset function can be .

[0139] In practical applications, to ensure that attackers cannot obtain genuine reference trajectory information, this invention proposes an encryption and decryption method to process relevant data, namely, using a function... To encrypt the expected trajectory And the function It is monotonically invertible, therefore the corresponding decryption function is: For ease of analysis, this application only discusses functions. For the linear case, i.e. ;in, and For design parameters, and , These are random numbers. For simplicity of analysis, we choose... In addition, parameters It can be generated using a pseudo-random number generator. Therefore, it can be obtained through calculation. From the above formula, we can derive... Therefore, by selecting appropriate parameters... It can be changed arbitrarily. The size of the attack detector. Based on this, the attack detector is designed as follows:

[0140] ;

[0141] Among them, parameters Attack detector thresholds designed for defenders. However, when The value is very large, while the parameter When the threshold is very small, the false positive rate can be extremely high. If the target value is too large, the attack detection rate will decrease. To resolve this contradiction, this invention will use position tracking error to design the attack detector, i.e.

[0142] ;

[0143] in, , The attack detector threshold designed for defenders, and The value can be greater than Small. To reduce false alarm rate and improve detection rate, the threshold is... The design is as follows:

[0144] ;

[0145] Where s is a matrix The number of columns, and The center point and generator matrix of the position tracking error set.

[0146] In some embodiments, the trajectory tracking control model includes a trajectory tracking control model based on a fully symmetric polytope; the step of establishing the trajectory tracking control model of the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information includes:

[0147] The position tracking error information and the velocity tracking error information are processed by a fully symmetric polytope to obtain the tracking error set information of the UAV.

[0148] A trajectory tracking control model for the UAV is established based on the UAV's tracking error set information, state information, position information, rotation information, and attitude angle information.

[0149] In this embodiment, the trajectory tracking control model includes a trajectory tracking control model based on a fully symmetric polytope; the trajectory tracking control model based on a fully symmetric polytope can be determined according to the actual situation and is not limited here. As an example, the trajectory tracking control model based on a fully symmetric polytope can be a state observer based on a fully symmetric polytope.

[0150] The specific processing steps for obtaining the UAV's tracking error set information by performing fully symmetric multi-cell processing on the position tracking error information and the velocity tracking error information can be determined according to the actual situation and are not limited here. The UAV's tracking error set information can be simply referred to as the tracking error set.

[0151] The specific process for establishing the trajectory tracking control model of the UAV based on its tracking error set information, state information, position information, rotation information, and attitude angle information can be determined according to actual conditions and is not limited here. The trajectory tracking control model of the UAV can also be referred to as a state observer based on a fully symmetric multicellular structure.

[0152] As an example, a tracking performance analysis is performed, and a state observer based on a fully symmetric multicell is designed; by and It can be obtained ; ;definition You can get ,in , , Represents a 3x3 matrix containing only zeros. This represents the three-dimensional identity matrix. When subjected to a fake data injection attack, the tracking error is calculated as follows:

[0153] ;

[0154] ;

[0155] ;

[0156] ;

[0157] definition You can get ;

[0158] in, , .

[0159] Using the Euler method, the above equation is discretized to obtain... ;

[0160] in, To use time intervals, It can be generated iteratively, i.e. Using the theory of fully symmetric polytopes, the tracking error set can be obtained, that is, if So there are ,in,

[0161] , ;

[0162] definition You can get

[0163] ;

[0164] in, , , Using the Euler discretization method, the following discrete-time linearized system model can be obtained.

[0165] ;

[0166] in, , , , .

[0167] Based on this, the following unknown input observer is designed:

[0168] , ;

[0169] in, For the observer state, These are estimates of the system state. Matrices T and N can be calculated as follows:

[0170] ;

[0171] ;

[0172] in, For matrix The pseudo-inverse of the matrix It is a random matrix; , Solve the following matrix inequalities

[0173] ;

[0174] A positive definite symmetric matrix can be obtained. And matrix W. Therefore, the gain matrix L can be obtained from... Calculated.

[0175] In practical applications, as an example, the trajectory control method for a quadcopter drone under network attack conditions can specifically be a trajectory control method for a quadcopter drone under network attack conditions. It can be combined with... Figure 2 To understand, Figure 2 This diagram illustrates an application scenario for a quadcopter drone trajectory control method under cyberattack conditions; it can be implemented through the following steps.

[0176] (1) Establish the dynamic model and controller model of the quadcopter UAV.

[0177] This invention primarily considers the trajectory control of a quadcopter unmanned aerial vehicle (UAV), whose position is determined by vectors. To describe, These respectively represent the drones in x , y and z The orientation and position. Furthermore, the rotation matrix between the body coordinate system and the inertial coordinate system is calculated as follows:

[0178]

[0179] in, The pitch angle, Yaw angle For roll angle; defined The attitude angle of the drone.

[0180] The mathematical model of the quadcopter drone is as follows:

[0181] , , (1);

[0182] in, For drone speed, It is the acceleration due to gravity. , For propeller torque, m For the quality of drones, f For thrust, and Let these represent the diagonal moments of the inertial tensor and the eccentric Coriolis matrix, respectively. For unknown but bounded noise, satisfying Assume the initial conditions are satisfied. and ,in The center point is indicated as The generating matrix is The fully symmetrical multicellular form; similarly The center point is indicated as The generating matrix is It is a fully symmetrical multicellular structure.

[0183] Next, we will design a trajectory tracking controller to enable the drone to track the desired trajectory. and expected speed The position tracking error is defined as... The speed tracking error is Therefore, the drone tracking controller is designed as follows:

[0184] (2);

[0185] in, , , and This is the controller gain. Because the controller contains... Therefore, the expected trajectory It must be continuously differentiable. From the above equation, we can obtain the following relationship:

[0186] (3);

[0187] (4);

[0188] (5);

[0189] in, and These are the desired pitch and roll angles, respectively. This invention assumes the desired yaw angle is zero, i.e. .

[0190] Controller gain and This can be obtained by solving the following inequality, namely

[0191] (6);

[0192] In this context, the asterisk (*) represents a symmetric element of the matrix. Given parameters, P 1. P 2 and X p The parameter matrix to be determined can be obtained using the inequalities above; after obtaining it, we can get... , .

[0193] Define the attitude angle tracking error as ,in Therefore, the desired propeller torque The design can be as follows:

[0194] (7);

[0195] in, and This is the attitude control gain matrix, used to control the attitude tracking error to approach zero.

[0196] Based on the obtained thrust and propeller torque The calculation results can be used to calculate the thrust of each propeller. , ,Right now

[0197] (8);

[0198] in, , and These are the known parameters related to the structure of the quadcopter drone.

[0199] (2) Establish attack models and attack detectors

[0200] The attacker's fake data injection attack is designed as follows:

[0201] , (9);

[0202] in, To attack the system state, and For attacking the system matrix, The attack signal is designed for the attacker. Considering that the attacker alters the drone's flight path by attacking the reference trajectory, the desired trajectory received by the drone controller... Become The control signal is also from u become u a ,Right now

[0203] (10);

[0204] in, .

[0205] When a fake data injection attack occurs, the corresponding position and velocity tracking errors become and .

[0206] To ensure that attackers cannot obtain authentic reference trajectory information, this invention proposes an encryption and decryption method to process related data, namely, using a function... To encrypt the expected trajectory And the function It is monotonically invertible, therefore the corresponding decryption function is: For ease of analysis, this application only discusses functions. For the linear case, i.e.

[0207] (11);

[0208] in, and For design parameters, and , These are random numbers. For simplicity of analysis, we choose... In addition, parameters It can be generated using a pseudo-random number generator. Therefore, it can be obtained through calculation.

[0209] (12);

[0210] From the above formula, we can derive Therefore, by selecting appropriate parameters... It can be changed arbitrarily. The size of the attack detector. Based on this, the attack detector is designed as follows:

[0211] (13);

[0212] Among them, parameters Attack detector thresholds designed for defenders. However, when The value is very large, while the parameter When the threshold is very small, the false positive rate can be extremely high. If the target value is too large, the attack detection rate will decrease. To resolve this contradiction, this invention will use position tracking error to design the attack detector, i.e.

[0213] (14);

[0214] in, , The attack detector threshold designed for defenders, and The value can be greater than Small. To reduce false alarm rate and improve detection rate, the threshold is... The design is as follows:

[0215] (15);

[0216] in, s For matrix The number of columns, and The center point and generator matrix of the position tracking error set.

[0217] (3) Conduct tracking performance analysis and design a state observer based on a fully symmetric multicell.

[0218] Depend on and It can be obtained

[0219] (16);

[0220] (17);

[0221] definition You can get ,in , , Represents a 3x3 matrix containing only zeros. Represents the three-dimensional identity matrix.

[0222] When subjected to a fake data injection attack, the tracking error is calculated as follows:

[0223] (18);

[0224] (19);

[0225] (20);

[0226] (twenty one);

[0227] definition You can get

[0228] (twenty two);

[0229] in, , .

[0230] Using the Euler method, the above equation is discretized to obtain...

[0231] (twenty three);

[0232] in, To use time intervals, It can be generated iteratively, i.e. Using the theory of fully symmetric polytopes, the tracking error set can be obtained, that is, if So there are ,in,

[0233] , (twenty four);

[0234] definition You can get

[0235] (25);

[0236] in, , , Using the Euler discretization method, the following discrete-time linearized system model can be obtained.

[0237] (26);

[0238] in, , , , .

[0239] Based on this, the following unknown input observer is designed:

[0240] , (27);

[0241] in, For the observer state, This is an estimate of the system state. (Matrix) T and N The following can be calculated:

[0242] (28);

[0243] (29);

[0244] in, For matrix The pseudo-inverse of the matrix It is a random matrix; , Solve the following matrix inequalities

[0245] (30);

[0246] A positive definite symmetric matrix can be obtained. sum matrix W Therefore, the gain matrix L It can be by Calculated.

[0247] This invention addresses the control system of a quadrotor drone containing unknown but bounded noise. Considering the possibility of spoofing attacks between the ground station and the drone, a state observer based on a fully symmetric multicell is designed to solve the state estimation problem of a quadrotor drone under such conditions, and is then applied to solve the attack detection problem. This invention also proposes a trajectory control method for a quadrotor drone under network attacks, solving the state estimation and control problem when the statistical characteristics of noise and interference are unknown.

[0248] Based on the same inventive concept as described above Figure 3 This is a schematic diagram of the structure of a quadcopter drone trajectory control device under network attack conditions, provided by an embodiment of the present invention. Figure 3 As shown, the device 300 includes:

[0249] The first acquisition module 301 is used to acquire the state information, position information and attitude angle information of the UAV;

[0250] The first modeling module 302 is used to establish a mathematical model and a trajectory tracking control model for the UAV based on the state information, the position information and the attitude angle information.

[0251] The second acquisition module 303 is used to acquire the attacker's status information and signal information when the drone is subjected to a fake data injection attack.

[0252] The second establishment module 304 establishes an attack model and an attack detection model for the UAV based on the state information and the signal information.

[0253] The processing module 305 is used to perform tracking performance processing on the UAV based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model to obtain the state observation model of the UAV; the state observation model is used to perform trajectory tracking control on the UAV.

[0254] In some embodiments, the attitude angle information includes the pitch angle information, yaw angle information, and roll angle information of the UAV; the first establishment module 302 is further configured to determine the rotation information of the UAV based on the pitch angle information, the yaw angle information, and the roll angle information; establish a mathematical model of the UAV based on the state information, the position information, the rotation information, and the attitude angle information; obtain the UAV's desired trajectory information and velocity information; determine the UAV's position tracking error information and velocity tracking error information based on the trajectory information and the velocity information; and establish a trajectory tracking control model of the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information.

[0255] In some embodiments, the rotation information includes at least rotation matrices in the body coordinate system and the inertial coordinate system; the first establishment module 302 is further configured to determine the rotation matrix of the UAV in the body coordinate system and the inertial coordinate system based on the pitch angle information, the yaw angle information and the roll angle information.

[0256] In some embodiments, the state information includes at least the speed information, acceleration information, noise information, and mass information of the UAV; the first establishment module 302 is further configured to establish a mathematical model of the UAV based on the speed information, acceleration information, noise information, mass information, position information, rotation information, and attitude angle information of the UAV.

[0257] In some embodiments, the first establishing module 302 is further configured to determine the attitude angle tracking error information of the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information; determine the desired propeller torque information of the UAV based on the attitude angle tracking error information of the UAV; and establish the trajectory tracking control model of the UAV based on the desired propeller torque information of the UAV.

[0258] In some embodiments, the second establishment module 304 is further configured to: determine the expected trajectory information and control signal information received by the UAV based on the state information and the signal information; establish an attack model for the UAV based on the expected trajectory information and the control signal information; determine the position tracking error information and velocity tracking error information when the UAV is subjected to a false data injection attack based on the signal information, the expected trajectory information and the control signal information; and establish an attack detection model for the UAV based on the position tracking error information and the velocity tracking error information.

[0259] In some embodiments, the device 300 further includes an encryption module and a decryption module; wherein,

[0260] The encryption module is used to encrypt the desired trajectory information received by the UAV using a first preset function to obtain the encrypted desired trajectory information.

[0261] The decryption module is used to decrypt the encrypted expected trajectory information using a second preset function to obtain the decrypted expected trajectory information.

[0262] In some embodiments, the trajectory tracking control model includes a trajectory tracking control model based on a fully symmetric polytope; the first establishment module 302 is further configured to perform fully symmetric polytope processing on the position tracking error information and the velocity tracking error information to obtain the tracking error set information of the UAV; and establish the trajectory tracking control model of the UAV based on the tracking error set information of the UAV, the state information, the position information, the rotation information and the attitude angle information.

[0263] It should be noted that the quadcopter drone trajectory control device under network attack provided in the embodiments of the present invention and the configuration method provided in the aforementioned embodiments of the present invention belong to the same inventive concept. The meanings of the terms appearing here have been explained in detail above and will not be repeated here.

[0264] This invention also provides a storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0265] This invention also provides a quadcopter drone trajectory control device in the event of a network attack. The quadcopter drone trajectory control device in the event of a network attack includes: a processor and a memory for storing a computer program that can run on the processor, wherein when the processor runs the computer program, it executes the steps of the above-described method embodiments stored in the memory.

[0266] Figure 4 This is a schematic diagram of a hardware structure for a quadcopter drone trajectory control device under network attack conditions, according to an embodiment of the present invention. The quadcopter drone trajectory control device 400 under network attack conditions includes: at least one processor 401 and a memory 402. Optionally, the quadcopter drone trajectory control device 400 under network attack conditions may further include at least one communication interface 403. The various components in the quadcopter drone trajectory control device 400 under network attack conditions are coupled together through a bus system 404. It can be understood that the bus system 404 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 404 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 4 The general designated all buses as Bus System 404.

[0267] It is understood that memory 402 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Sync Link Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 402 described in this embodiment of the invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0268] In this embodiment of the invention, the memory 402 is used to store various types of data to support the operation of the quadcopter drone trajectory control device 400 in the presence of a cyberattack. Examples of such data include any computer program for operating on the quadcopter drone trajectory control device 400 in the presence of a cyberattack, and programs implementing the methods of this embodiment of the invention may be included in the memory 402.

[0269] The methods disclosed in the above embodiments of the present invention can be applied to processor 401, or implemented by processor 401. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of the present invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory. The processor reads information from the memory and, in conjunction with its hardware, completes the steps of the aforementioned method.

[0270] In an exemplary embodiment, the quadcopter drone trajectory control device 400 under network attack conditions can be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the above-described method.

[0271] In the several embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units; some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs. In addition, all functional units in the various embodiments of this invention can be integrated into one processing module, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated units can be implemented in hardware or in the form of hardware plus software functional units.

[0272] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. A method for trajectory control of a quadcopter unmanned aerial vehicle (UAV) under network attack, characterized in that, The method includes: Acquire the drone's status, position, and attitude angle information; A mathematical model and a trajectory tracking control model for the UAV are established based on the state information, the position information, and the attitude angle information. In the event that the drone is subjected to a fake data injection attack, the attacker's status information and signal information can be obtained; An attack model and an attack detection model for the UAV are established based on the state information and the signal information. Based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model, the UAV's tracking performance is processed to obtain the UAV's state observation model; the state observation model is used for trajectory tracking control of the UAV. The attitude angle information includes the pitch angle, yaw angle, and roll angle information of the UAV; the step of establishing a mathematical model and trajectory tracking control model for the UAV based on the state information, the position information, and the attitude angle information includes: The rotation information of the UAV is determined based on the pitch angle information, the yaw angle information, and the roll angle information; A mathematical model of the UAV is established based on the state information, position information, rotation information, and attitude angle information; Obtain the desired trajectory and speed information of the drone; The position tracking error information and velocity tracking error information of the UAV are determined based on the trajectory information and the velocity information; A trajectory tracking control model for the UAV is established based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information. The trajectory tracking control model includes a trajectory tracking control model based on a fully symmetric polytope; the establishment of the UAV's trajectory tracking control model based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information includes: The position tracking error information and the velocity tracking error information are processed by a fully symmetric polytope to obtain the tracking error set information of the UAV. A trajectory tracking control model for the UAV is established based on the UAV's tracking error set information, state information, position information, rotation information, and attitude angle information.

2. The method according to claim 1, characterized in that, The rotation information includes at least rotation matrices in the body coordinate system and the inertial coordinate system; determining the rotation information of the UAV based on the pitch angle information, the yaw angle information, and the roll angle information includes: The rotation matrix of the UAV in the body coordinate system and the inertial coordinate system is determined based on the pitch angle information, the yaw angle information and the roll angle information.

3. The method according to claim 1, characterized in that, The status information includes at least the speed information, acceleration information, noise information, and mass information of the UAV; The step of establishing a mathematical model of the UAV based on the state information, the position information, the rotation information, and the attitude angle information includes: A mathematical model of the UAV is established based on its speed information, acceleration information, noise information, mass information, position information, rotation information, and attitude angle information.

4. The method according to claim 1, characterized in that, The process of establishing a trajectory tracking control model for the UAV based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information includes: The attitude angle tracking error information of the UAV is determined based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information. The desired propeller torque information of the UAV is determined based on the attitude angle tracking error information of the UAV. A trajectory tracking control model for the UAV is established based on the expected propeller torque information of the UAV.

5. The method according to claim 1, characterized in that, The step of establishing the attack model and attack detection model for the UAV based on the state information and the signal information includes: Based on the state information and the signal information, the desired trajectory information and control signal information received by the UAV are determined; An attack model for the UAV is established based on the desired trajectory information and the control signal information; Based on the signal information, the expected trajectory information, and the control signal information, determine the position tracking error information and velocity tracking error information when the UAV is subjected to a false data injection attack; An attack detection model for the UAV is established based on the position tracking error information and the velocity tracking error information.

6. The method according to claim 5, characterized in that, The method further includes: The desired trajectory information received by the UAV is encrypted using a first preset function to obtain encrypted desired trajectory information; The encrypted desired trajectory information is decrypted using a second preset function to obtain the decrypted desired trajectory information.

7. A trajectory control device for a quadcopter unmanned aerial vehicle (UAV) under network attack, characterized in that, The device includes: The first acquisition module is used to acquire the UAV's status information, position information, and attitude angle information; The first modeling module is used to establish a mathematical model and a trajectory tracking control model for the UAV based on the state information, the position information and the attitude angle information. The second acquisition module is used to acquire the attacker's status information and signal information when the drone is subjected to a fake data injection attack. The second module establishes an attack model and an attack detection model for the UAV based on the state information and the signal information. The processing module is used to perform tracking performance processing on the UAV based on the mathematical model, the trajectory tracking control model, the attack model, and the attack detection model to obtain the state observation model of the UAV; the state observation model is used for trajectory tracking control of the UAV. The attitude angle information includes the pitch angle, yaw angle, and roll angle information of the UAV; the step of establishing a mathematical model and trajectory tracking control model for the UAV based on the state information, the position information, and the attitude angle information includes: The rotation information of the UAV is determined based on the pitch angle information, the yaw angle information, and the roll angle information; A mathematical model of the UAV is established based on the state information, position information, rotation information, and attitude angle information; Obtain the desired trajectory and speed information of the drone; The position tracking error information and velocity tracking error information of the UAV are determined based on the trajectory information and the velocity information; A trajectory tracking control model for the UAV is established based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information. The trajectory tracking control model includes a trajectory tracking control model based on a fully symmetric polytope; the establishment of the UAV's trajectory tracking control model based on the position tracking error information, the velocity tracking error information, the state information, the position information, the rotation information, and the attitude angle information includes: The position tracking error information and the velocity tracking error information are processed by a fully symmetric polytope to obtain the tracking error set information of the UAV. A trajectory tracking control model for the UAV is established based on the UAV's tracking error set information, state information, position information, rotation information, and attitude angle information.

8. A trajectory control device for a quadcopter drone under network attack, characterized in that, The device includes: a processor and a memory for storing a computer program capable of running on the processor, wherein, when the processor runs the computer program, it performs the steps of the method according to any one of claims 1 to 6.

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