Method and system for designing collaborative route of manned aerial vehicle and unmanned aerial vehicle

Abstract

The invention relates to the technical field of manned vehicle and unmanned aerial vehicle cooperative control, in particular to a manned vehicle and unmanned aerial vehicle cooperative route design method and system, and the method comprises the steps: constructing a cooperative formation route planning model of a manned vehicle and an unmanned aerial vehicle; constructing a reference route of collaborative formation movement of the manned aerial vehicles and the unmanned aerial vehicles; and on the basis of the reference route, performing convex optimization processing on the collaborative formation route planning model of the manned aerial vehicle and the unmanned aerial vehicle to obtain an optimized route. According to the scheme of the invention, the method can adapt to various types of threat areas, quickly obtains the reference route meeting the threat avoidance constraint and data size requirements, and further employs a sequence convex optimization method to apply the reference route to a manned aerial vehicle and unmanned aerial vehicle cooperative formation route planning model. And a more reasonable planned route can be obtained in a shorter time.

Description

Technical Field

[0001] The present invention relates to the technical field of coordinated control of manned aircraft and unmanned aircraft, and in particular to a method and system for designing a coordinated route for manned aircraft and unmanned aircraft. Background Art

[0002] There are two main approaches to modeling and analysis for the route planning problem of manned / unmanned aerial vehicle (UAV) cooperative formation: the first approach is to establish the differential motion equation of the research object based on control quantities such as acceleration and overload, thereby converting the route planning problem into an optimal control problem for solution; the second approach is to establish the algebraic motion equation of the research object based on geometric quantities such as segment length and turning angle, and use planning methods such as potential field method, tree search, and graph search to solve it. The first solution method can be divided into two categories: direct method and indirect method. The direct method is to further convert the optimal control problem into a finite-dimensional parameter optimization problem, and then use the nonlinear programming method to solve the problem. Its main disadvantage is that the solution accuracy is relatively low; the indirect method studies the first-order necessary conditions of the optimal control problem and converts it into a Hamilton boundary value problem for solution. Its main disadvantage is that it has high requirements for initial values ​​and a small convergence radius. The second approach uses graphical and algebraic methods to solve the planning problem, which has high solution efficiency, but also has the problem of low accuracy, and it is difficult to meet the formation control and coordination requirements of heterogeneous systems such as manned / unmanned aerial vehicle formations.

[0003] In the first solution approach, the use of convex optimization methods to solve multidimensional optimal control problems has obvious advantages. Convex optimization methods are mainly solved by interior point methods, which are essentially direct methods. In recent years, convex optimization methods have been widely used in the research of multi-agent route planning, drone formation reconstruction and other problems in the aerospace field. Generally, non-convex problems are transformed into a series of convex optimization sub-problems by performing constraint relaxation, linearization, discretization and other operations, and then solved using the idea of ​​sequential convex programming. Satisfactory optimization solutions can be obtained more efficiently, but they have high initial value sensitivity. Setting different reference routes will have a greater impact on the calculation efficiency and calculation results. The traditional reference route setting method generally connects the starting point and the end point with a straight line, and interpolates the reference route according to the data volume requirements. The reference route set by this method does not integrate the threat area information, resulting in reduced calculation efficiency and difficulty in obtaining an ideal optimization route. Summary of the invention

[0004] The purpose of the present invention is to solve at least one technical problem in the background technology and to provide a method and system for collaborative route design of manned aircraft and unmanned aircraft.

[0005] To achieve the above object, the present invention provides a method for designing a coordinated route for a manned aircraft and an unmanned aircraft, comprising: Construct a collaborative formation route planning model for manned and unmanned aircraft; Constructing benchmark routes for coordinated formation movement of manned and unmanned aircraft; Based on the reference route, a convex optimization process is performed on the collaborative formation route planning model of the manned aircraft and the unmanned aircraft to obtain an optimized route; The construction of a reference route for the coordinated formation movement of manned aircraft and unmanned aircraft includes: Step 1: To avoid the threat area, a coordinate system is established with the node where the manned aircraft is currently located as the origin, and the radius of the threat area is from the origin to the The direction angles of the two tangent lines to the circle are and ,and , the direction angle of the line from the origin to the target area is ; Step 2: Judgement and If the size , then select The corresponding waypoint, otherwise, select The corresponding waypoint; Step 3: Establish a coordinate system with the selected waypoint as the origin, and repeat steps 1 to 3 until the last threat area is avoided; Step 4: Based on each of the waypoints, an interpolation algorithm is used to obtain the reference route.

[0006] According to one aspect of the present invention, a collaborative formation route planning model for manned aircraft and unmanned aircraft is constructed, including: Constructing a coordinated formation motion model for manned and unmanned aircraft: Based on the collaborative formation motion model, adding constraints to the flight of manned aircraft and unmanned aircraft; Based on the collaborative formation motion model, an objective function with the minimum energy consumption of manned aircraft as the optimization goal and an objective function with the shortest arrival time of unmanned aerial vehicles in the mission area as the optimization goal are constructed.

[0007] According to one aspect of the present invention, construct Manned aircraft and The coordinated formation motion model of the UAVs is: ; and ; Where: is the gravitational acceleration, taken as ; For the system Manned or unmanned aircraft, ; Respectively The three-dimensional coordinates of a manned or unmanned aircraft in the ground coordinate system; Respectively The flight path inclination and heading angle of manned or unmanned aircraft; For the The speed of the manned or unmanned aircraft in the ground coordinate system; Respectively Horizontal axial overload, horizontal normal overload and vertical normal overload of manned or unmanned aircraft; and Respectively The control quantity and state quantity of a manned or unmanned aircraft.

[0008] According to one aspect of the present invention, based on the collaborative formation motion model, constraints are added to the flight of manned aircraft and unmanned aircraft, including: Amplitude constraints of state and control variables: The flight state and control quantity of manned and unmanned aircraft must be kept within a certain range, which can be expressed as: ; Where: , Respectively The lower limit and upper limit of the state quantity of a manned aircraft or an unmanned aircraft; , , and Respectively The lower limit value of the control amount, the upper limit value of the control amount, the lower limit value of the control amount change rate, and the upper limit value of the control amount change rate of the manned or unmanned aircraft; Avoid Threat Constraints: For the detected A known threat is handled conservatively. Neither manned aircraft nor unmanned aircraft can enter its projection area in the horizontal plane during flight. This constraint can be expressed as: ; Where: express norm; matrix ; is the coordinate of the center of the cross section of the threat area; is the radius of the cross section of the threat area; For the system Fly manned or unmanned aircraft; The first detected Threats; is the time variable during the flight; The initial moment for manned aircraft route planning; Terminal times planned for manned aircraft routes; Distance Constraint: Including distance constraints between UAVs in the formation and distance constraints between UAVs and manned aircraft; Distance constraint between drones: Based on the information exchange and flight safety considerations of drones within the formation, the distance between two drones at any time is greater than the set safety distance and less than the maximum communication transmission distance, specifically: ; Where: ; , Respectively represent Frame, Drone The state value at the moment; The three-dimensional safety distance between drones; The upper limit of the communication transmission distance between drones; and They represent the initial and terminal moments of the UAV route planning in the formation. Since the UAV route planning needs to be based on the manned aircraft route planning, ; During the flight, the drones must maintain a certain formation according to tactical requirements and meet the following constraints: and Always maintain a certain tactical formation. The specific formation constraints are: ; Where: for The relative state matrix between machines at the time; for The relative state matrix between machines at the time; Distance constraints between UAVs and manned aircraft: During the coordinated formation flight of manned and UAVs, UAVs should maintain a safe distance from manned aircraft and avoid collision. At the same time, they should always be within the command and control range of manned aircraft and within the communication transmission range. The specific constraints are: ; Where: It is the safe distance between manned aircraft and unmanned aircraft; It indicates the maximum distance between manned aircraft and unmanned aircraft that can ensure stable information transmission.

[0009] According to one aspect of the present invention, the objective function for optimizing the minimum energy consumption of manned machines is: ; Where: for norm; The objective function for optimizing the time it takes for the drone to reach the mission area is: .

[0010] To achieve the above object, the present invention also provides a manned aircraft and unmanned aircraft collaborative route design system, comprising: Route planning model building module, building a collaborative formation route planning model for manned and unmanned aircraft; The reference route construction module constructs the reference route for the coordinated formation movement of manned and unmanned aircraft; An optimized route acquisition module performs convex optimization processing on the coordinated formation route planning model of the manned aircraft and the unmanned aircraft based on the reference route to obtain an optimized route; The reference route construction module includes: The direction angle acquisition submodule, in order to avoid the threat area, establishes a coordinate system with the node where the manned aircraft is currently located as the origin, and uses the origin to the threat area with a radius of The direction angles of the two tangent lines to the circle are and ,and , the direction angle of the line from the origin to the target area is ; Waypoint selection submodule, judge and If the size , then select The corresponding waypoint, otherwise, select The corresponding waypoint; The waypoint cycle selection and confirmation submodule establishes a coordinate system with the selected waypoint as the origin, and repeats the execution steps of the direction angle acquisition submodule, the waypoint selection submodule and the waypoint cycle selection and confirmation submodule until the last threat area is avoided; The reference route acquisition submodule uses an interpolation algorithm to obtain the reference route based on each of the waypoints.

[0011] To achieve the above-mentioned purpose, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the method for collaborative route design of manned and unmanned aircraft as described above.

[0012] To achieve the above objectives, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for designing a collaborative route for manned and unmanned aircraft as described above is implemented.

[0013] According to the solution of the present invention, the present invention can adapt to various types of threat areas and quickly obtain a reference route that meets the threat avoidance constraints and data volume requirements. Furthermore, a sequential convex optimization method is used to apply the reference route to the manned and unmanned aircraft collaborative formation route planning model, which can obtain a more reasonable planned route in a shorter time. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A flowchart schematically showing a method for collaborative route design of manned aircraft and unmanned aircraft according to an embodiment of the present invention; Figure 2 A schematic diagram of a reference route setting architecture according to an embodiment of the present invention is shown; Figure 3 A diagram schematically showing a comparison between a manned aircraft reference route and a manned aircraft optimized route according to Embodiment 1 of the present invention; Figure 4 A diagram schematically showing a comparison of the control amount of a manned aircraft reference route and a manned aircraft optimized route according to Embodiment 1 of the present invention; Figure 5 A schematic diagram showing a comparison between the optimized route of a manned aircraft and the optimized route of an unmanned aircraft according to Example 1 of the present invention. DETAILED DESCRIPTION

[0015] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only to enable those skilled in the art to better understand and thus implement the present invention, rather than implying any limitation on the scope of the present invention.

[0016] As used herein, the term “including” and variations thereof are to be interpreted as open-ended terms meaning “including, but not limited to.” The term “based on” is to be interpreted as “based, at least in part, on.” The terms “one embodiment” and “an embodiment” are to be interpreted as “at least one embodiment.”

[0017] Figure 1 The flowchart schematically shows a method for designing a coordinated route between a manned aircraft and an unmanned aircraft according to an embodiment of the present invention. Figure 1 As shown, in this embodiment, the method for designing a coordinated route between a manned aircraft and an unmanned aircraft includes: Construct a collaborative formation route planning model for manned and unmanned aircraft; Constructing benchmark routes for coordinated formation movement of manned and unmanned aircraft; Based on the reference route, the convex optimization process is performed on the coordinated formation route planning model of manned aircraft and unmanned aircraft to obtain the optimized route (including the optimized route of manned aircraft and the optimized route of unmanned aircraft). Among them, Figure 2 As shown, a reference route for the coordinated formation movement of manned aircraft and unmanned aircraft (manned aircraft reference route) is constructed, including: Step 1: To avoid the threat area, a coordinate system is established with the node O0 where the manned aircraft is currently located as the origin, and the radius of the threat area is from the origin to the The direction angles of the two tangent lines to the circle are and ,and , the direction angle of the line from the origin to the target area is ; where m is 1, 2, 3… .

[0018] Step 2: Judgement and If the size , then select The corresponding waypoint, otherwise, select The corresponding waypoint; Step 3: Establish a coordinate system with the selected waypoint as the origin, and repeat steps 1 to 3 until the last threat area is avoided; Step 4: Based on each waypoint, use the interpolation algorithm to obtain the reference route.

[0019] In this embodiment, if Figure 2 As shown, from the starting point to the target area, it takes For example, take the threat area as an example. For obstacles such as irregular mountains, the maximum radius of their profile is the threat radius. In order to effectively avoid the threat area and ensure the safety of the entire manned / unmanned aerial vehicle formation, set: ; Where: is a natural constant; is the radius of the circumscribed circle of the threat area; In this embodiment, in order to ensure that the data volume meets the requirements of the sequential convex optimization method and the data points do not exceed the node range and meet the requirements for avoiding the threat area, the Hermite interpolation algorithm is adopted to form a reference route.

[0020] Furthermore, in this embodiment, before constructing the baseline route, it also includes: according to the threat characteristics of the target area, the threats are divided into three basic types: known stationary threats, known mobile threats and unknown threats, and when clarifying the route planning, the different requirements of the three threats are met: being able to effectively avoid known stationary threats and to avoid known mobile threats and unknown threats to the greatest extent.

[0021] Furthermore, in this embodiment, the reference route designed and constructed according to the above method is applied to the route planning model of the collaborative formation of manned and unmanned aircraft. Through convex optimization processing, iterative solution is performed in the order of manned aircraft first and then unmanned aircraft to obtain an optimized route that satisfies conditions such as inter-aircraft distance constraints, collaborative space-time constraints, and threat avoidance constraints.

[0022] Furthermore, according to an embodiment of the present invention, a collaborative formation route planning model of manned aircraft and unmanned aircraft is constructed, including: Constructing a coordinated formation motion model for manned and unmanned aircraft: Based on the collaborative formation motion model, adding constraints to the flight of manned aircraft and unmanned aircraft; Based on the collaborative formation motion model, an objective function with the minimum energy consumption of manned aircraft as the optimization goal and an objective function with the shortest arrival time of unmanned aircraft in the mission area as the optimization goal are constructed.

[0023] Furthermore, according to an embodiment of the present invention, a coordinated formation motion model of manned aircraft and unmanned aircraft is constructed as follows: The coordinated system formed by N unmanned aerial vehicles and M manned aircraft uses kinematic differential equations to describe the motion process of the aircraft (manned and unmanned aircraft) in the formation. Assuming that the manned and unmanned aircraft in the formation are flying in the air without sideslip, and the thrust direction of the engine is consistent with the flight speed direction, the point mass motion model of manned and unmanned aircraft in three-dimensional space can be obtained, as shown in the formula: ; and ; Where: is the gravitational acceleration, taken as ; For the system Manned or unmanned aircraft, ; Respectively The three-dimensional coordinates of a manned or unmanned aircraft in the ground coordinate system; Respectively The flight path inclination and heading angle of manned or unmanned aircraft; For the The speed of the manned or unmanned aircraft in the ground coordinate system; Respectively Horizontal axial overload, horizontal normal overload and vertical normal overload of manned or unmanned aircraft; and Respectively The control quantity and state quantity of a manned or unmanned aircraft.

[0024] In the above manned / unmanned aerial vehicle collaborative architecture, the manned aircraft serves as the command and control center of the system. In the specific implementation process, the route is first planned according to the optimization target, the reference route and the motion model, and the manned aircraft's and , the actual flight route is generated through the control of manned aircraft pilots; the UAVs in the formation need to be combined with the manned aircraft , Construct constraint conditions, obtain the optimized route of each UAV based on the above motion model, optimization objectives and benchmark routes, and use the onboard control system to control and form the actual route.

[0025] Furthermore, according to an embodiment of the present invention, based on the cooperative formation motion model, constraints are added to the flight of manned aircraft and unmanned aircraft, including: Amplitude constraints of state and control variables: The flight state and control quantity of manned and unmanned aircraft must be kept within a certain range, which can be expressed as: ; Where: , Respectively The lower limit and upper limit of the state quantity of a manned aircraft or an unmanned aircraft; , , and Respectively The lower limit value of the control amount, the upper limit value of the control amount, the lower limit value of the control amount change rate, and the upper limit value of the control amount change rate of manned or unmanned aircraft.

[0026] Avoid Threat Constraints: For the detected A known static threat is conservatively processed. Neither manned aircraft nor unmanned aircraft can enter its projection area in the horizontal plane during flight. This constraint can be expressed as: ; Where: express norm; matrix ; is the coordinate of the center of the cross section of the threat area; is the radius of the cross section of the threat area; For the system Fly manned or unmanned aircraft; The first detected Threats; is the time variable during the flight; The initial moment for manned aircraft route planning; Terminal times planned for manned aircraft routes; Distance Constraint: Including distance constraints between UAVs in the formation and distance constraints between UAVs and manned aircraft; Distance constraint between drones: Based on the information exchange and flight safety considerations of drones within the formation, the distance between two drones at any time is greater than the set safety distance and less than the maximum communication transmission distance, specifically: ; Where: ; , Respectively represent Frame, Drone The state value at the moment; The three-dimensional safety distance between drones; The upper limit of the communication transmission distance between drones; and They represent the initial and terminal moments of the UAV route planning in the formation. Since the UAV route planning needs to be based on the manned aircraft route planning, ; During the flight, the drones must maintain a certain formation according to tactical requirements and meet the following constraints: and Always maintain a certain tactical formation. The specific formation constraints are: ; Where: for The relative state matrix between machines at the time; for The relative state matrix between machines at the time; Distance constraints between UAVs and manned aircraft: During the coordinated formation flight of manned and UAVs, UAVs should maintain a safe distance from manned aircraft and avoid collision. At the same time, they should always be within the command and control range of manned aircraft and within the communication transmission range. The specific constraints are: ; Where: It is the safe distance between manned aircraft and unmanned aircraft; It indicates the maximum distance between manned aircraft and unmanned aircraft that can ensure stable information transmission.

[0027] Not only that, but also: Start and end condition constraints: The status values ​​for starting and ending route planning must be certain and known, and must be clarified based on the battlefield environment and tactical requirements when actually carrying out route planning.

[0028] Furthermore, according to an embodiment of the present invention, in order to achieve a longer flight time of a manned aircraft and reduce its fuel consumption, the minimum energy consumption during its flight is set as the optimization goal, and the objective function for minimizing the energy consumption of the manned aircraft as the optimization goal is constructed as follows: ; Where: for norm; In order to achieve the UAV to quickly reach the designated mission area, the optimization goal is set to the shortest time to reach the mission area. At this time, the objective function of the UAV route planning in the formation is: .

[0029] According to the above scheme of the present invention, the present invention can adapt to various types of threat areas and quickly obtain a reference route that meets the threat avoidance constraints and data volume requirements. Furthermore, a sequential convex optimization method is used to apply the reference route to the manned and unmanned aircraft collaborative formation route planning model, which can obtain a more reasonable planned route in a shorter time.

[0030] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a manned aircraft and unmanned aircraft collaborative route design system, comprising: Route planning model building module, building a collaborative formation route planning model for manned and unmanned aircraft; The reference route construction module constructs the reference route for the coordinated formation movement of manned and unmanned aircraft; The optimized route acquisition module performs convex optimization processing on the coordinated formation route planning model of manned and unmanned aircraft based on the reference route to obtain the optimized route; Baseline building blocks, including: The direction angle acquisition submodule, in order to avoid the threat area, establishes a coordinate system with the node where the manned aircraft is currently located as the origin, and uses the origin to the threat area with a radius of The direction angles of the two tangent lines to the circle are and ,and , the direction angle of the line from the origin to the target area is ; Waypoint selection submodule, judge and If the size , then select The corresponding waypoint, otherwise, select The corresponding waypoint; The waypoint cycle selection and confirmation submodule establishes a coordinate system with the selected waypoint as the origin, and repeats the execution steps of the direction angle acquisition submodule, the waypoint selection submodule and the waypoint cycle selection and confirmation submodule until the last threat area is avoided; The reference route acquisition submodule uses an interpolation algorithm to obtain the reference route based on each waypoint.

[0031] In this embodiment, if Figure 2 As shown, from the starting point to the target area, it takes For example, take the threat area as an example. For obstacles such as irregular mountains, the maximum radius of their profile is the threat radius. In order to effectively avoid the threat area and ensure the safety of the entire manned / unmanned aerial vehicle formation, set: ; Where: is a natural constant; is the radius of the circumscribed circle of the threat area; In this embodiment, in order to ensure that the data volume meets the requirements of the sequential convex optimization method and the data points do not exceed the node range and meet the requirements for avoiding the threat area, the Hermite interpolation algorithm is adopted to form a reference route.

[0032] Furthermore, in this embodiment, before constructing the baseline route, it also includes: according to the threat characteristics of the target area, the threats are divided into three basic types: known stationary threats, known mobile threats and unknown threats, and when clarifying the route planning, the different requirements of the three threats are met: being able to effectively avoid known stationary threats and to avoid known mobile threats and unknown threats to the greatest extent.

[0033] Furthermore, in this embodiment, the reference route designed and constructed according to the above method is applied to the route planning model of the collaborative formation of manned and unmanned aircraft. Through convex optimization processing, iterative solution is performed in the order of manned aircraft first and then unmanned aircraft to obtain an optimized route that satisfies conditions such as inter-aircraft distance constraints, collaborative space-time constraints, and threat avoidance constraints.

[0034] Furthermore, according to an embodiment of the present invention, a collaborative formation route planning model of manned aircraft and unmanned aircraft is constructed, including: Constructing a coordinated formation motion model for manned and unmanned aircraft: Based on the collaborative formation motion model, adding constraints to the flight of manned aircraft and unmanned aircraft; Based on the collaborative formation motion model, an objective function with the minimum energy consumption of manned aircraft as the optimization goal and an objective function with the shortest arrival time of unmanned aerial vehicles in the mission area as the optimization goal are constructed.

[0035] Further, according to an embodiment of the present invention, the coordinated formation motion model of manned aircraft and unmanned aircraft is constructed as follows: The coordinated system formed by N unmanned aerial vehicles and M manned aircraft uses kinematic differential equations to describe the motion process of the aircraft (manned and unmanned aircraft) in the formation. Assuming that the manned and unmanned aircraft in the formation are flying in the air without sideslip, and the thrust direction of the engine is consistent with the flight speed direction, the point mass motion model of manned and unmanned aircraft in three-dimensional space can be obtained, as shown in the formula: ; and ; Where: is the gravitational acceleration, taken as ; For the system Manned or unmanned aircraft, ; Respectively The three-dimensional coordinates of a manned or unmanned aircraft in the ground coordinate system; Respectively The flight path inclination and heading angle of manned or unmanned aircraft; For the The speed of the manned or unmanned aircraft in the ground coordinate system; Respectively Horizontal axial overload, horizontal normal overload and vertical normal overload of manned or unmanned aircraft; and Respectively The control quantity and state quantity of a manned or unmanned aircraft.

[0036] In this embodiment, in the above hybrid collaborative architecture, the human-machine and As the input of the entire manned and unmanned aircraft coordinated formation, the corresponding route is generated through the control of the manned pilot, and the route is used as the input of the route planning model of the manned and unmanned aircraft coordinated formation to ensure the priority of the manned route and the command and control of the formation by the manned pilot; the unmanned aircraft in the formation are based on the route generated by the manned aircraft. and , input into each UAV control system, and use the UAV's motion model to output the actual flight route.

[0037] Furthermore, according to an embodiment of the present invention, based on the cooperative formation motion model, constraints are added to the flight of manned aircraft and unmanned aircraft, including: Amplitude constraints of state and control variables: The flight state and control quantity of manned and unmanned aircraft must be kept within a certain range, which can be expressed as: ; Where: , Respectively The lower limit and upper limit of the state quantity of a manned aircraft or an unmanned aircraft; , , and Respectively The lower limit value of the control amount, the upper limit value of the control amount, the lower limit value of the control amount change rate, and the upper limit value of the control amount change rate of manned or unmanned aircraft.

[0038] Avoid Threat Constraints: For the detected A known static threat is conservatively processed. Neither manned aircraft nor unmanned aircraft can enter its projection area in the horizontal plane during flight. This constraint can be expressed as: ; Where: express norm; matrix ; is the coordinate of the center of the cross section of the threat area; is the radius of the cross section of the threat area; For the system Fly manned or unmanned aircraft; The first detected Threats; is the time variable during the flight; The initial moment for manned aircraft route planning; Terminal times planned for manned aircraft routes; Distance Constraint: Including distance constraints between UAVs in the formation and distance constraints between UAVs and manned aircraft; Distance constraint between drones: Based on the information exchange and flight safety considerations of drones within the formation, the distance between two drones at any time is greater than the set safety distance and less than the maximum communication transmission distance, specifically: ; Where: ; , Respectively represent Frame, Drone The state value at the moment; The three-dimensional safety distance between drones; The upper limit of the communication transmission distance between drones; and They represent the initial and terminal moments of the UAV route planning in the formation. Since the UAV route planning needs to be based on the manned aircraft route planning, ; During the flight, the drones must maintain a certain formation according to tactical requirements and meet the following constraints: and Always maintain a certain tactical formation. The specific formation constraints are: ; Where: for The relative state matrix between machines at the time; for The relative state matrix between machines at the time; Distance constraints between UAVs and manned aircraft: During the coordinated formation flight of manned and UAVs, UAVs should maintain a safe distance from manned aircraft and avoid collision. At the same time, they should always be within the command and control range of manned aircraft and within the communication transmission range. The specific constraints are: ; Where: It is the safe distance between manned aircraft and unmanned aircraft; It indicates the maximum distance between manned aircraft and unmanned aircraft that can ensure stable information transmission.

[0039] Not only that, but also: Start and end condition constraints: The status values ​​for starting and ending route planning must be certain and known, and must be clarified based on the battlefield environment and tactical requirements when actually carrying out route planning.

[0040] Furthermore, according to an embodiment of the present invention, in order to achieve a longer flight time of a manned aircraft and reduce its fuel consumption, the minimum energy consumption during its flight is set as the optimization goal, and the objective function for minimizing the energy consumption of the manned aircraft as the optimization goal is constructed as follows: ; Where: for norm; In order to achieve the UAV to quickly reach the designated mission area, the optimization goal is set to the shortest time to reach the mission area. At this time, the objective function of the UAV route planning in the formation is:

[0041] According to the above scheme of the present invention, the present invention can adapt to various types of threat areas and quickly obtain a reference route that meets the threat avoidance constraints and data volume requirements. Furthermore, a sequential convex optimization method is used to apply the reference route to the manned and unmanned aircraft collaborative formation route planning model, which can obtain a more reasonable planned route in a shorter time.

[0042] Furthermore, to achieve the above-mentioned purpose, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the method for collaborative route design of manned and unmanned aircraft as described above is implemented.

[0043] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for collaborative route design of manned and unmanned aircraft as described above is implemented.

[0044] Based on the above solution of the present invention, the solution of the present invention is described in detail in the following in conjunction with the accompanying drawings in the form of a specific embodiment.

[0045] Example 1 Taking the example of the Red Side sending out manned and unmanned aircraft in coordinated formation to pass through the Blue Side's area, the route planning for this process is carried out.

[0046] 1. Status setting In the initial area, the manned and unmanned aircraft coordinated formations formed a circular escort formation. The initial status of each aircraft in the formation is shown in Table 1.

[0047] Table 1 Table of the status of each aircraft in the circular escort formation Aircraft Type Location coordinates / km Speed / (m / s) Heading angle / rad Route inclination / rad Manned aircraft 0，0，5 300 π / 4 0 Drone 1 1，0，5 350 π / 4 0 Drone 2 0，1，5 350 π / 4 0 Drone 3 -1，0，5 350 π / 4 0 Drone 4 0，-1，5 350 π / 4 0 set up is the time when the manned machine arrives at the mission area. , the relative position matrix between drones in the formation As shown in Table 2.

[0048] Table 2 UAV relative state matrix Matrix Name Relative position coordinates 2. Threat area parameter setting Assume that when the manned and unmanned aircraft coordinated formation flies from the initial position to the target mission area, there are two man-made static threat areas and one static threat area caused by mountain shielding. The cross-sectional centers and radii of the above three threat areas are set as follows: ; 3. Performance parameter setting Due to the limitation of mission area and the performance level of manned aircraft and unmanned aircraft, the amplitude of state parameters of manned aircraft is set as follows: ; The state parameter amplitude of the drone is set as follows: ; The Matlab2017a convex optimization toolkit CVX is used to plan the routes of manned and unmanned aerial vehicle collaborative formations. Figure 3 Optimized route shown.

[0049] Figure 3 It can be seen that both the baseline route and the optimized route can effectively avoid the threat area. The optimized route adopts a more conservative strategy and maintains a greater safety distance from the threat area. After optimization, the manned aircraft first climbs, then slowly hovers and dives to reach the mission area. Figure 4 It can be seen that when the optimized route is taken, the control amount of the manned aircraft at each discrete moment is basically maintained at a constant value, and is smaller than the control amount of the baseline route, indicating that the optimized route obtained after optimization can reduce energy consumption, ensure the maximum range of the manned aircraft, and improve battlefield survivability.

[0050] From the attached Figure 5 According to the analysis, unlike manned aircraft that first climb and then slowly descend, in order to reach the mission area in a shorter time, the four drones in the formation completed assembly at the initial position and then avoided the threat area in a dense formation. Since the set flight altitude of the mission area is higher than the initial position, the drones maintained a slow climbing state, thus ensuring minimal speed loss and reaching the mission area in the shortest time.

[0051] Those skilled in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0052] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method implementation methods, and will not be repeated here.

[0053] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0054] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0055] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0056] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal sending / receiving method of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0057] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

[0058] It should be understood that the size of the serial numbers of each step in the content of the invention and the implementation methods of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of the present invention.

Claims

1. A method for designing a coordinated route between manned aircraft and unmanned aircraft, characterized in that: include: Construct a collaborative formation route planning model for manned and unmanned aircraft; Constructing benchmark routes for coordinated formation movement of manned and unmanned aircraft; Based on the reference route, a convex optimization process is performed on the collaborative formation route planning model of the manned aircraft and the unmanned aircraft to obtain an optimized route; The construction of a reference route for the coordinated formation movement of manned aircraft and unmanned aircraft includes: Step 1: To avoid the threat area, a coordinate system is established with the node where the manned aircraft is currently located as the origin, and the radius of the threat area is from the origin to the The direction angles of the two tangent lines to the circle are and ,and , the direction angle of the line from the origin to the target area is ; Step 2: Judgement and If the size , then select The corresponding waypoint, otherwise, select The corresponding waypoint; Step 3: Establish a coordinate system with the selected waypoint as the origin, and repeat steps 1 to 3 until the last threat area is avoided; Step 4: Based on each of the waypoints, an interpolation algorithm is used to obtain the reference route.

2. The method for designing a coordinated route between a manned aircraft and an unmanned aircraft according to claim 1, characterized in that: Construct a collaborative formation route planning model for manned and unmanned aircraft, including: Constructing a coordinated formation motion model for manned and unmanned aircraft: Based on the collaborative formation motion model, adding constraints to the flight of manned aircraft and unmanned aircraft; Based on the collaborative formation motion model, an objective function with the minimum energy consumption of manned aircraft as the optimization goal and an objective function with the shortest arrival time of unmanned aerial vehicles in the mission area as the optimization goal are constructed.

3. The method for designing a coordinated route between a manned aircraft and an unmanned aircraft according to claim 2, characterized in that: Build Manned aircraft and The coordinated formation motion model of the UAVs is: ； and ; Where: is the gravitational acceleration, taken as ; For the system Manned or unmanned aircraft, ; Respectively The three-dimensional coordinates of a manned or unmanned aircraft in the ground coordinate system; Respectively The flight path inclination and heading angle of manned or unmanned aircraft; For the The speed of the manned or unmanned aircraft in the ground coordinate system; Respectively Horizontal axial overload, horizontal normal overload and vertical normal overload of manned or unmanned aircraft; and Respectively The control quantity and state quantity of a manned or unmanned aircraft.

4. The method for designing a coordinated route between a manned aircraft and an unmanned aircraft according to claim 3, characterized in that: Based on the collaborative formation motion model, constraints are added to the flight of manned and unmanned aircraft, including: (1) Amplitude constraints of state variables and control variables: The flight state and control quantity of manned and unmanned aircraft must be kept within a certain range, which can be expressed as: ； Where: , Respectively The lower limit and upper limit of the state quantity of a manned aircraft or an unmanned aircraft; , , and Respectively The lower limit value of the control amount, the upper limit value of the control amount, the lower limit value of the control amount change rate, and the upper limit value of the control amount change rate of the manned or unmanned aircraft; (2) Avoiding threat constraints: For the detected A known threat is handled conservatively. Neither manned aircraft nor unmanned aircraft can enter its projection area in the horizontal plane during flight. This constraint can be expressed as: ； Where: express norm; matrix ; is the coordinate of the center of the cross section of the threat area; is the radius of the cross section of the threat area; For the system Fly manned or unmanned aircraft; The first detected Threats; is the time variable during the flight; The initial moment for manned aircraft route planning; Terminal times planned for manned aircraft routes; (3) Distance constraint: Including distance constraints between UAVs in the formation and distance constraints between UAVs and manned aircraft; ① Distance constraint between drones: Based on the information exchange and flight safety considerations of drones within the formation, the distance between two drones at any time is greater than the set safety distance and less than the maximum communication transmission distance, specifically: ； Where: ； , Respectively represent Frame, Drone The state value at the moment; The three-dimensional safety distance between drones; The upper limit of the communication transmission distance between drones; and They represent the initial and terminal moments of the UAV route planning in the formation. Since the UAV route planning needs to be based on the manned aircraft route planning, ; During the flight, the drones must maintain a certain formation according to tactical requirements and meet the following constraints: and Always maintain a certain tactical formation. The specific formation constraints are: ； Where: for The relative state matrix between machines at the time; for The relative state matrix between machines at the time; ② Distance constraints between UAVs and manned aircraft: During the coordinated formation flight of manned and UAVs, UAVs and manned aircraft should maintain a safe distance and avoid collision. At the same time, they should always be within the command and control range of manned aircraft and within the communication transmission range. The specific constraints are as follows: ； Where: It is the safe distance between manned aircraft and unmanned aircraft; It indicates the maximum distance between manned aircraft and unmanned aircraft that can ensure stable information transmission.

5. The method for designing a coordinated route between a manned aircraft and an unmanned aircraft according to claim 4, characterized in that: The objective function for optimizing the minimum energy consumption of manned machines is: ； Where: for norm; The objective function for optimizing the time it takes for the drone to reach the mission area is: 。 6. A manned and unmanned aircraft collaborative route design system, characterized in that: include: Route planning model building module, building a collaborative formation route planning model for manned and unmanned aircraft; The reference route construction module constructs the reference route for the coordinated formation movement of manned and unmanned aircraft; An optimized route acquisition module performs convex optimization processing on the coordinated formation route planning model of the manned aircraft and the unmanned aircraft based on the reference route to obtain an optimized route; The reference route construction module includes: The direction angle acquisition submodule, in order to avoid the threat area, establishes a coordinate system with the node where the manned aircraft is currently located as the origin, and uses the origin to the threat area with a radius of The direction angles of the two tangent lines to the circle are and ,and , the direction angle of the line from the origin to the target area is ; Waypoint selection submodule, judge and If the size , then select The corresponding waypoint, otherwise, select The corresponding waypoint; The waypoint cycle selection and confirmation submodule establishes a coordinate system with the selected waypoint as the origin, and repeats the execution steps of the direction angle acquisition submodule, the waypoint selection submodule and the waypoint cycle selection and confirmation submodule until the last threat area is avoided; The reference route acquisition submodule uses an interpolation algorithm to obtain the reference route based on each of the waypoints.

7. An electronic device, characterized in that The method comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the method for designing a collaborative route for a manned aircraft and an unmanned aircraft as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the method for designing a collaborative route for a manned aircraft and an unmanned aircraft as described in any one of claims 1 to 5 is implemented.

Images