A method and system for designing a trajectory of an unmanned aerial vehicle under a point cruise mission constraint

Abstract

The application provides a UAV trajectory design method and system under the constraint of a fixed-point cruise task, which comprises the following steps: acquiring a communication channel parameter of a UAV and a ground user and a cruise point position, and establishing an original trajectory optimization problem for maximizing communication throughput; mapping a time domain problem to a path domain to obtain a joint optimization problem in the path domain; constructing an artificial potential field with the ground user as the center, and equivalently taking the cruise point as a fixed pulley node; converting the joint optimization problem in the path domain into an equivalent mechanical problem of minimizing the total potential energy of a variable density rope in the artificial potential field; based on the equivalence between the joint optimization problem in the path domain and the equivalent mechanical problem, solving a segmented trajectory analytical expression; and according to whether the flight time is sufficient, constructing a rope optimal configuration and restoring a continuous trajectory of the UAV, respectively. The application solves the trajectory design demand of the UAV under the constraint of the fixed-point cruise task to realize the optimization of communication performance.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) communication technology, and particularly relates to a method and system for designing UAV trajectories under the constraints of fixed-point cruise missions. Background Technology

[0002] In recent years, unmanned aerial vehicles (UAVs) have been widely used in communication, monitoring, and search and rescue due to their flexible deployment, high mobility, and low cost. Especially with the development of 5G and future 6G networks, UAVs have demonstrated enormous application potential in disaster emergency communication, monitoring missions, and network coverage optimization. In UAV-assisted communication networks, the UAV's flight trajectory directly affects the stability of the communication link, the quality of data transmission, and the timeliness of the mission; therefore, trajectory design is one of the key factors affecting communication performance. By optimizing the trajectory, the UAV can dynamically adjust its position to always remain within the optimal communication range, thereby maximizing signal strength and system throughput.

[0003] In particular, in many real-world scenarios, drones must pass through multiple predetermined cruise points in sequence during flight, such as for data collection, environmental monitoring, equipment inspection, or providing relay communication services in certain key areas. This places higher demands on the continuity and smoothness of the trajectory, and also introduces more optimization variables and constraints.

[0004] Current technologies often discretize continuous trajectories, approximating the UAV trajectory by optimizing the positions of discrete points. However, due to the lack of continuity between discrete points, this discretization method cannot guarantee the continuity and smoothness of the flight trajectory, leading to local optima in the final solution. Furthermore, the computational complexity increases dramatically with the number of discrete points. To address these issues, YUAN X et al. introduced a mechanical concept into the artificial potential field, proposing a novel UAV continuous trajectory design method based on a mechanically equivalent strategy. This method equates the UAV's continuous trajectory to the equilibrium state of a variable-density, extremely thin rope under the influence of an artificial potential field. Within this framework, maximizing the UAV's communication performance is transformed into minimizing the total potential energy of the rope. This method has been successfully applied to various typical scenarios: under discrete coding rate constraints, YUAN X et al. obtained the optimal flight trajectory with the highest communication throughput through a rope balance model; in data acquisition tasks, YUAN X et al. used this method to analytically derive an efficient path that minimizes task completion time; in covert communication scenarios, HUANGY et al. jointly optimized the trajectory and transmission power to achieve stronger security and communication efficiency; in energy-constrained networks, YUAN X et al. uniformly optimized the path and power control to achieve a globally optimal trade-off between communication performance and energy consumption. However, the above techniques are only applicable to scenarios where UAVs have "start-end" path constraints, and further research is needed on UAV trajectory design under fixed-point cruise constraints. Summary of the Invention

[0005] To address the current lack of a suitable trajectory design method for UAVs under fixed-point cruise constraints based on mechanical equivalence, this invention proposes a UAV trajectory design method combining an artificial potential field based on mechanical equivalence and a fixed pulley model. This method equates the UAV's cruise point to a fixed pulley node, mechanically transforming the continuous trajectory design problem involving infinite variables into a problem of minimizing the total potential energy of the rope. This method fully considers flight mission constraints and communication requirements, solving the trajectory design problem for UAVs under fixed-point cruise mission constraints to optimize communication performance.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] A method for designing UAV trajectories under the constraints of fixed-point cruise missions includes the following steps:

[0008] S1. Obtain the communication channel parameters between the UAV and the ground user and the location of the cruise point, and establish the original trajectory optimization problem to maximize the communication throughput;

[0009] S2. Divide the UAV path into segments according to the cruise point positions and represent them parametrically, mapping the time domain problem to the path domain to obtain the joint optimization problem in the path domain;

[0010] S3. Construct an artificial potential field centered on ground users, with its potential energy function set as the inverse of the communication rate, and the cruise point equivalent to a fixed pulley node;

[0011] S4. The joint optimization problem in the path domain is transformed into an equivalent mechanical problem of minimizing the total potential energy of the variable density rope in an artificial potential field;

[0012] S5. Derive the force balance equations for each segment of the rope, and based on the equivalence between the joint optimization problem in the path domain and the equivalent mechanical problem, solve the analytical expression of the segment trajectory, and establish a mapping table between the initial tension direction angle and the rope physical parameters.

[0013] S6. Depending on whether there is sufficient flight time, construct the optimal rope configuration and restore it to the continuous trajectory of the UAV.

[0014] Furthermore, the communication channel parameters in S1 include:

[0015] Ground user location Drone starting point and the finish line , cruise point locations ;

[0016] Drone flight altitude Total communication time between UAVs and ground users Maximum speed limit for drones ;

[0017] Channel gain between drones and ground users ; Indicates that drones are in Current location; maximum communication rate between the drone and ground users. ;

[0018] in, Indicates the reference distance as Channel gain, This indicates the horizontal distance between the drone's current location and the ground user; For channel bandwidth, It is channel noise power. This indicates the transmit power from ground users in the uplink or from drones in the downlink.

[0019] Furthermore, the original trajectory optimization problem in S1 that maximizes communication throughput is:

[0020]

[0021] in, This indicates the drone's path information. This represents the total throughput of communication between the drone and ground users. It is the system channel bandwidth. It is channel noise power. It is a drone Flight speed at any moment Indicates that drones are in Time reaches the One cruise point; , , These respectively represent the drones in , , The current location at any given moment.

[0022] Furthermore, the path parameterization in S2 is represented as follows: ;

[0023] Among them, path variables This indicates the time from the drone's departure point to the specified time. The length of the path taken by the aircraft along the trajectory. It is a drone Flight speed at any moment This represents the total length of the drone's flight path from the starting point to the destination, for any given path variable. , , These respectively represent the drones in The path and velocity information at each moment need to be obtained, and global constraints also need to be introduced. .

[0024] Furthermore, the joint optimization problem in the path domain of S2 is:

[0025]

[0026] in, It is the drone's path information. Path variable The maximum communication rate between the drone and the ground user at the location. This indicates that the drone is in the path variable. When to reach the One cruise point; , , These represent the drone's path variable as follows: , , The location at that time.

[0027] Furthermore, the potential energy function in S3 is:

[0028] ;

[0029] in, Indicates the drone's path variable The potential energy at the current location; Indicates the drone's path variable The horizontal distance from the current location to the ground user.

[0030] Furthermore, the equivalent mechanical problem in S4 of minimizing the total potential energy of the variable density rope in the artificial potential field is:

[0031]

[0032] in, It is rope-shaped. It is the linear density of the rope. This indicates the minimum linear density limit for the rope. It is the length of the rope. It's the quality of the rope. Indicates the rope is in Arrive at the first One fixed pulley; , , They represent the lengths of the ropes respectively. , , The location of the rope at that time.

[0033] Furthermore, the force balance equations for each segment of the rope in S5 are as follows:

[0034]

[0035] in, This represents the optimal initial tension at the starting point of each rope segment. The optimal initial tension direction is defined at the starting point of each rope segment. For the rope in The magnitude of the artificial potential force at the location, , These are the potential field center and the UAV in the path variable. The coordinates of the current location. It is the distance between the rope and the center of the potential field. It is the tension of the rope at the corresponding position. , These represent the projections of the sum of the optimal initial tension of the rope and the gravitational force of the potential field onto the x-axis and y-axis, respectively.

[0036] Furthermore, the analytical expression for the segmented trajectory in S5 is:

[0037] ;

[0038] in, Indicates the drone at a certain time Location information described by time parameter Indicates the drone's path variable Location information described by a path parameter;

[0039] ;

[0040] in, , They represent the first The location of each cruise point is axis, Coordinate representation on the axis;

[0041] Mapping table of initial tension direction angle and rope physical parameters for:

[0042] ;

[0043] in, Representing different trajectory segments, It is the optimal initial tension magnitude. It is the segment length, It is the tension at the end of each rope segment.

[0044] On the other hand, the present invention provides a UAV trajectory design system under the constraints of a fixed-point cruise mission, comprising:

[0045] The original trajectory optimization problem construction module is used to obtain the communication channel parameters and cruise point positions between the UAV and the ground user, and to establish the original trajectory optimization problem that maximizes communication throughput.

[0046] The joint optimization problem construction module is used to segment the UAV path according to the cruise point position and represent it parametrically, mapping the time domain problem to the path domain to obtain the joint optimization problem in the path domain.

[0047] Equivalent module for fixed pulley node. It is used to construct an artificial potential field centered on the ground user, with its potential energy function set as the inverse of the communication rate, and the cruise point is equivalent to a fixed pulley node;

[0048] Equivalent mechanical problem transformation module. It is used to transform the joint optimization problem in the path domain into an equivalent mechanical problem of minimizing the total potential energy of a variable density rope in an artificial potential field;

[0049] The mapping table establishment module is used to derive the force balance equations of each segment of the rope, solve the segment trajectory analytical expression based on the equivalence between the joint optimization problem in the path domain and the equivalent mechanical problem, and establish a mapping table between the initial tension direction angle and the rope physical parameters.

[0050] The restoration module is used to construct the optimal rope configuration and restore it to the continuous trajectory of the UAV, depending on whether there is sufficient flight time.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] This invention proposes a novel continuous trajectory design method based on a mechanically equivalent artificial potential field and a fixed pulley model under the constraints of fixed-point cruise missions. It extends the original "start-end" trajectory design scenario to trajectory design under fixed-point cruise mission constraints. By constructing an artificial potential field with the ground user as the attraction center, a fixed pulley model is further proposed, equating the UAV's cruise point to a fixed pulley node. This transforms the communication performance objective into a problem of minimizing the total potential energy of the rope, allowing for the acquisition of the optimal closed-form solution for the UAV's trajectory under fixed-point cruise mission constraints with extremely low complexity. Based on the principle of mechanical equivalence, this invention transforms the originally non-convex, high-dimensional, continuous trajectory optimization problem into a physical problem of minimizing the total potential energy of a variable-density rope, thus solving the trajectory design requirement for achieving optimal communication performance for UAVs under fixed-point cruise mission constraints. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0054] Figure 1 This is a schematic diagram of a drone fixed-point patrol mission scenario according to an embodiment of the present invention;

[0055] Figure 2 This is a UAV trajectory model diagram under the constraints of a fixed-point cruise mission according to an embodiment of the present invention;

[0056] Figure 3 This is a flowchart of a method according to an embodiment of the present invention;

[0057] Figure 4 This is a shape model diagram of the rope in an artificial potential field in an embodiment of the present invention;

[0058] Figure 5 This is a schematic diagram comparing the throughput performance of the method proposed in this embodiment of the invention with that of a traditional method;

[0059] Figure 6 This diagram illustrates a comparison of the computational complexity of the method proposed in this embodiment of the invention with that of traditional methods. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0061] Example 1

[0062] The invention will now be further described with reference to the accompanying drawings.

[0063] The following is combined Figure 1-6 This invention introduces a method and system for designing UAV trajectories under the constraints of a fixed-point cruise mission based on mechanical equivalence, as detailed below:

[0064] like Figure 1 This invention considers a UAV communication scenario under the constraint of a fixed-point cruise mission, where the UAV is required to operate within a fixed total flight time budget. Inside, from the starting point Departure, flying sequentially to the pre-planned cruise point cluster. Finally reached the finish line Each cruise point here Each of these corresponds to a specific task phase. Failure to accurately reach any cruise point will result in blind spots in target information acquisition, missed communication time slots, and even unnecessary energy consumption due to returning to base or lateral movement. Under this constraint, designing a UAV trajectory with the goal of maximizing system throughput is difficult to achieve using traditional methods.

[0065] like Figure 2 As shown, this invention considers a communication mission scenario where a drone passes through two cruise points. One drone, flying at a fixed altitude, serves a single ground user in a two-dimensional plane. The drone must pass through the known cruise points sequentially. , That is, the trajectory must satisfy the following spatial path order requirements: in, Starting from, The endpoint is the ground user's fixed ground location during the communication mission. The drones, on the other hand, fly at a fixed altitude. It moves in a two-dimensional plane and transmits information to ground users. This indicates the horizontal distance from the drone's current location to the ground user, i.e. ,in, , These represent the time intervals of the drone. The location of axis, Coordinate representation on the axis.

[0066] like Figure 3 The diagram shown is a flowchart of the method of the present invention, which includes the following steps:

[0067] Step 1: Obtain the parameters of the communication channel between the UAV and the user under the constraint of fixed-point cruise, and establish the original trajectory optimization problem.

[0068] The communication parameters between the UAV and the ground user mentioned in step 1 include: ground user location. Information on the starting and ending points of the drone , Cruise point location information , The drone's flight altitude is fixed at Total communication time between UAVs and ground users Maximum speed limit .

[0069] Since UAVs are highly likely to establish line-of-sight links, this invention employs a free-space path loss model to describe the wireless communication characteristics between the UAV and ground users. (Step 1 describes the channel gain between the UAV and ground users.) for: ;

[0070] in, Indicates the reference distance as Channel gain, It is the flight altitude of the drone. This indicates the horizontal distance from the drone's current location to the ground user, i.e. ;

[0071] According to Shannon's formula, the maximum communication rate between the drone and the ground user... for:

[0072] ;

[0073] in, It is the system channel bandwidth. It is channel noise power. This indicates the transmit power from a ground user in the uplink (or from a drone in the downlink).

[0074] In communication between drones and ground users, the objective of the original problem is to maximize the total throughput of communication between the drone and the ground user. The original continuous trajectory optimization problem can be formally described as:

[0075]

[0076] in, It is the drone's path information. It is the total throughput of communication between drones and ground users. It is the system channel bandwidth. It is channel noise power. Indicates the transmit power in the link. Indicates the reference distance as Channel gain, Indicates the horizontal distance between the drone and the ground user. It is the total communication time between the drone and the ground user. It is a drone Flight speed at any moment This is the maximum speed limit for drones. Indicates that drones are in Time reaches the One cruise point.

[0077] Step 2: Parametrically represent the UAV path and segment the path at the cruise point.

[0078] The path parameterization described in step 2 is as follows:

[0079] ;

[0080] Among them, path variables This indicates the time from the drone's departure point to the specified time. The length of the path taken by the aircraft along the trajectory. It is a drone Flight speed at any moment This represents the total length of the drone's flight path from the starting point to the destination. For any given path variable... , , These respectively represent the drones in The path and velocity information at each moment need to be obtained, and global constraints also need to be introduced. .

[0081] To clarify the path segmentation, the path segmentation in step 2 is described as follows:

[0082]

[0083] Path parameterization maps the original time-continuous optimization problem to the path domain, resulting in a joint optimization problem in the path domain:

[0084]

[0085] in, It is the drone's path information. Path variable The maximum communication rate between the drone and the ground user at the location. This indicates that the drone is in the path variable. When to reach the One cruise point.

[0086] Step 3: Establish an equivalent artificial potential energy field to transform the original trajectory design problem into an equivalent mechanical problem under the artificial potential energy field.

[0087] In step 3, imagine an extremely thin and flexible rope, such as Figure 4 As shown, its two ends are fixed to the starting and ending points of the drone, respectively, and the preset cruise points are modeled as ideal fixed pulley support points, so that the rope is forced to pass through these points on the geometric path. This represents the geometric shape of the rope in two-dimensional space.

[0088] To establish an equivalent relationship between UAV communication performance and tether energy, a potential energy function of an artificial potential field is constructed. For communication rate The opposite number:

[0089] ;

[0090] in, Indicates the drone's path variable The horizontal distance from the ground user.

[0091] Now assume there is a sufficiently thin, variable-density rope in the potential field, the shape of which can represent the flight trajectory of the UAV. At the same time, the cruise points of the UAV are modeled as ideal fixed pulley support points in the artificial potential field, so that the rope is forced to pass through these points geometrically, but the tension remains continuous mechanically.

[0092] The objective of maximizing the communication throughput of the UAV in the original trajectory optimization problem can be transformed into minimizing the total potential energy of the rope under an artificial potential field. The equivalent mechanical problem is constructed as follows:

[0093]

[0094] Step 4: Analyze the characteristics of the artificial potential field and the corresponding gravitational field.

[0095] Furthermore, in step 4, the constructed artificial potential field is first analyzed, and its force vector is equal to the negative gradient:

[0096]

[0097] Clearly, the force field corresponding to the artificial potential energy field points towards the center point. Therefore, to maximize channel gain, the UAV should be positioned as close as possible to the ground user's location. Furthermore, according to the principle of minimum potential energy in physics, the optimal state of the system should correspond to the stable configuration where the rope reaches mechanical equilibrium in an external force field; that is, the system is in equilibrium with zero net force and zero torque in the absence of external disturbances.

[0098] Step 5: Derive the piecewise force equilibrium equations, solve for the piecewise trajectory analytical expressions, and establish a trajectory parameter mapping table.

[0099] Step 5 shows the segmented rope from the starting point to the point... The force balance analysis is as follows:

[0100]

[0101] in, This represents the optimal initial tension at the starting point of each rope segment. The optimal initial tension direction is defined at the starting point of each rope segment. For the rope in The magnitude of the artificial potential force at the location, For the minimum linear density of the rope, , These are the potential field center and the UAV in the path variable. The coordinates of the current location. It is the distance between the rope and the center of the potential field. It is the tension of the rope at the corresponding position. , These represent the projections of the sum of the optimal initial tension of the rope and the gravitational force of the potential field onto the x-axis and y-axis, respectively.

[0102] Based on existing geometric constraints You can get

[0103]

[0104] Therefore, for this section of rope, only the optimal initial tension at the starting point is needed. and direction It is known that the optimal solution for this segmented rope can be described as follows:

[0105] ;

[0106] Based on the equivalence between the original UAV trajectory design problem and the problem of minimizing the total potential energy of the rope, a closed-form solution for the continuous trajectory of the UAV segment can be constructed:

[0107] ;

[0108] To solve the problem when the initial tension is known Under these conditions, how can we effectively determine the tension direction angle corresponding to the optimal solution for the rope? The problem is based on the fact that for any fixed direction angle Under mechanical equilibrium conditions, the trajectory solution can be uniquely determined. This invention proposes to construct a formalized "initial tension direction angle"... A mapping table between the physical properties of ropes, i.e.

[0109] ;

[0110] in, Representing different trajectory segments, It is the optimal initial tension magnitude. It is the segment length, It is the tension at the end of that segment.

[0111] Step 6: Construct the optimal solution for the rope shape under both conditions of sufficient and insufficient drone flight time, and then mechanically convert it into the continuous trajectory solution of the drone.

[0112] Furthermore, step 6 solves for the optimal continuous trajectory of the UAV under the constraints of the fixed-point cruise mission, under both cases where the UAV has sufficient flight time and insufficient flight time. First, if the UAV has sufficient flight time, in the equivalent rope model, a mass point can be introduced into any rope segment. That is, the rope runs along the straight line with the minimum linear density from the starting point of the segment to the center of the potential field, and then along the straight line to the end point of the segment. The shapes of the other two segments are solved by the equilibrium equation and mapping table, and the remaining mass forms a mass point at the center of the potential field.

[0113] When the mass point appears in the first segment, a closed-form solution expression can be obtained:

[0114]

[0115] Meanwhile, its linear density function is:

[0116]

[0117] When the mass point appears in the second segment, a closed-form solution expression can be obtained:

[0118]

[0119] Meanwhile, its linear density function is:

[0120]

[0121] When the mass point appears in the third segment, a closed-form solution expression can be obtained:

[0122]

[0123] Meanwhile, its linear density function is:

[0124]

[0125] in, Let represent the distances from the starting point, the ending point, and the two fixed pulley nodes to the center of the potential field, respectively. It is the first The rope length corresponding to each rope segment in the mapping table. They represent the first The projection of the sum of the optimal initial tension of the rope segment and the gravitational force of the potential field onto the x-axis and y-axis.

[0126] If the drone's flight time is insufficient, first fix the angle parameters of the first two segments. and Through the mapping table and Find the corresponding rope lengths respectively and Then, based on the total rope length constraint, the length of the third segment can be deduced. In the mapping table From the perspective of searching for conditions And its corresponding tension solution, thus determining a complete rope configuration. Next, check whether the tension between adjacent segments is continuous (i.e., ... Ultimately, based on the total potential energy of the system... All candidate solutions are evaluated and selected, and the solution with the lowest potential energy is chosen as the optimal trajectory scheme. Its closed-form expression is:

[0127]

[0128] After establishing the optimal solution for the rope in both cases in step 6, it can be determined according to... Restore the drone's continuous trajectory:

[0129] ;

[0130] This invention proposes a novel continuous trajectory design method based on a mechanically equivalent artificial potential field and a fixed pulley model under the constraints of fixed-point cruise missions. It extends the original "start-end" trajectory design scenario to trajectory design under fixed-point cruise mission constraints. By constructing an artificial potential field with the ground user as the attraction center, a fixed pulley model is further proposed, equating the UAV's cruise point to a fixed pulley node. This transforms the communication performance objective into a problem of minimizing the total potential energy of the rope, allowing for the acquisition of the optimal closed-form solution for the UAV's trajectory under fixed-point cruise mission constraints with extremely low complexity. Based on the principle of mechanical equivalence, this invention transforms the originally non-convex, high-dimensional, continuous trajectory optimization problem into a physical problem of minimizing the total potential energy of a variable-density rope, thus solving the trajectory design requirement for achieving optimal communication performance for UAVs under fixed-point cruise mission constraints.

[0131] Figure 5 The differences in average system throughput between the method used in this embodiment and the SCP-based method under different flight time constraints are presented. It can be seen that the method is always superior to the SCP method in terms of system throughput and can achieve better communication performance under various flight time budgets. In particular, its advantages are more prominent under the resource-constrained conditions that are common in practical applications.

[0132] Figure 6 The CPU runtime required for trajectory design by the two methods under different flight times was compared. It can be seen that the proposed method, by adopting a strategy that combines offline generation of pre-computation mapping tables, closed trajectory construction and global search of optimization algorithms, avoids large-scale matrix operations and tedious iterative solutions. The overall computation time is very short, only a tiny fraction of that of the traditional SCP method, and the computational complexity is extremely low. In actual deployment, it can greatly reduce system response latency and support near real-time trajectory generation requirements.

[0133] Example 2

[0134] This embodiment provides a UAV trajectory design system under the constraints of a fixed-point cruise mission, including:

[0135] The original trajectory optimization problem construction module is used to obtain the communication channel parameters and cruise point positions between the UAV and the ground user, and to establish the original trajectory optimization problem that maximizes communication throughput.

[0136] The joint optimization problem construction module is used to segment the UAV path according to the cruise point position and represent it parametrically, mapping the time domain problem to the path domain to obtain the joint optimization problem in the path domain.

[0137] Equivalent module for fixed pulley node. It is used to construct an artificial potential field centered on the ground user, with its potential energy function set as the inverse of the communication rate, and the cruise point is equivalent to a fixed pulley node;

[0138] Equivalent mechanical problem transformation module. It is used to transform the joint optimization problem in the path domain into an equivalent mechanical problem of minimizing the total potential energy of a variable density rope in an artificial potential field;

[0139] The mapping table establishment module is used to derive the force balance equations of each segment of the rope, solve the segment trajectory analytical expression based on the equivalence between the joint optimization problem in the path domain and the equivalent mechanical problem, and establish a mapping table between the initial tension direction angle and the rope physical parameters.

[0140] The restoration module is used to construct the optimal rope configuration and restore it to the continuous trajectory of the UAV, depending on whether there is sufficient flight time.

[0141] It should be understood that any parts not described in detail in this specification belong to the prior art.

[0142] It should be understood that the above description of the preferred embodiments is quite detailed, but this should not be construed as limiting the scope of protection of this invention. It is neither necessary nor possible to exhaustively describe all possible implementations. Those skilled in the art, guided by this invention, can make substitutions or modifications without departing from the scope of the claims, all of which fall within the scope of protection of this invention. The scope of protection of this invention should be determined by the appended claims.

Claims

1. A method for designing UAV trajectories under the constraints of a fixed-point cruise mission, characterized in that, Includes the following steps: S1. Obtain the communication channel parameters between the UAV and the ground user and the location of the cruise point, and establish the original trajectory optimization problem to maximize the communication throughput; S2. Divide the UAV path into segments according to the cruise point positions and represent them parametrically, mapping the time domain problem to the path domain to obtain the joint optimization problem in the path domain; S3. Construct an artificial potential field centered on ground users, with its potential energy function set as the inverse of the communication rate, and the cruise point equivalent to a fixed pulley node; S4. The joint optimization problem in the path domain is transformed into an equivalent mechanical problem of minimizing the total potential energy of the variable density rope in an artificial potential field; S5. Derive the force balance equations for each segment of the rope, and based on the equivalence between the joint optimization problem in the path domain and the equivalent mechanical problem, solve the analytical expression of the segment trajectory, and establish a mapping table between the initial tension direction angle and the rope physical parameters. S6. Depending on whether there is sufficient flight time, construct the optimal rope configuration and restore it to the continuous trajectory of the UAV.

2. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission as described in claim 1, characterized in that, The communication channel parameters in S1 include: Ground user location Drone starting point and the finish line , cruise point locations ; Drone flight altitude Total communication time between UAVs and ground users Maximum speed limit for drones ; Channel gain between drones and ground users ; Indicates that drones are in Current location; maximum communication rate between the drone and ground users. ; in, Indicates the reference distance as Channel gain, This indicates the horizontal distance between the drone's current location and the ground user; For channel bandwidth, It is channel noise power. This indicates the transmit power from ground users in the uplink or from drones in the downlink.

3. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission according to claim 2, characterized in that, The original trajectory optimization problem for maximizing communication throughput in S1 is as follows: in, This indicates the drone's path information. This represents the total throughput of communication between the drone and ground users. It is the system channel bandwidth. It is channel noise power. It is a drone Flight speed at any moment Indicates that drones are in Time reaches the One cruise point; , , These respectively represent the drones in , , The current location at any given moment.

4. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission according to claim 3, characterized in that, The path parameterization in S2 is represented as follows: ； Among them, path variables This indicates the time from the drone's departure point to the specified time. The length of the path taken by the aircraft along the trajectory. It is a drone Flight speed at any moment This represents the total length of the drone's flight path from the starting point to the destination, for any given path variable. , , These respectively represent the drones in The path and velocity information at each moment need to be obtained, and global constraints also need to be introduced. .

5. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission according to claim 4, characterized in that, The joint optimization problem in the path domain of S2 is: in, It is the drone's path information. Path variable The maximum communication rate between the drone and the ground user at the location. This indicates that the drone is in the path variable. When to reach the One cruise point; , , These represent the drone's path variable as follows: , , The location at that time.

6. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission according to claim 5, characterized in that, The potential energy function in S3 is: ； in, Indicates the drone's path variable The potential energy at the current location; Indicates the drone's path variable The horizontal distance from the current location to the ground user.

7. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission as described in claim 6, characterized in that, The equivalent mechanical problem in S4 that minimizes the total potential energy of the variable density rope in an artificial potential field is: in, It is rope-shaped. It is the linear density of the rope. This indicates the minimum linear density limit for the rope. It is the length of the rope. It's the quality of the rope. Indicates the rope is in Arrive at the first One fixed pulley; ( 、( 、( They represent the lengths of the ropes respectively. , , The location of the rope at that time.

8. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission according to claim 7, characterized in that, The force balance equations for each segment of the rope in S5 are as follows: in, This represents the optimal initial tension at the starting point of each rope segment. The optimal initial tension direction is defined at the starting point of each rope segment. For the rope in The magnitude of the artificial potential force at the location, , These are the potential field center and the UAV in the path variable. The coordinates of the current location. It is the distance between the rope and the center of the potential field. It is the tension of the rope at the corresponding position. , These represent the projections of the sum of the optimal initial tension of the rope and the gravitational force of the potential field onto the x-axis and y-axis, respectively.

9. The method for designing UAV trajectories under the constraints of a fixed-point cruise mission as described in claim 8, characterized in that, The analytical expression for the segmented trajectory in S5 is: ； in, Indicates the drone at a certain time Location information described by time parameter Indicates the drone's path variable Location information described by a path parameter; ； in, , They represent the first The location of each cruise point is axis, Coordinate representation on the axis; Mapping table of initial tension direction angle and rope physical parameters for: ； in, Representing different trajectory segments, It is the optimal initial tension magnitude. It is the segment length, It is the tension at the end of each rope segment.

10. A UAV trajectory design system under the constraint of fixed-point cruise mission, characterized in that, include: The original trajectory optimization problem construction module is used to obtain the communication channel parameters and cruise point positions between the UAV and the ground user, and to establish the original trajectory optimization problem that maximizes communication throughput. The joint optimization problem construction module is used to segment the UAV path according to the cruise point position and represent it parametrically, mapping the time domain problem to the path domain to obtain the joint optimization problem in the path domain. Equivalent module for fixed pulley node. It is used to construct an artificial potential field centered on the ground user, with its potential energy function set as the inverse of the communication rate, and the cruise point is equivalent to a fixed pulley node; Equivalent mechanical problem transformation module. It is used to transform the joint optimization problem in the path domain into an equivalent mechanical problem of minimizing the total potential energy of a variable density rope in an artificial potential field; The mapping table establishment module is used to derive the force balance equations of each segment of the rope, solve the segment trajectory analytical expression based on the equivalence between the joint optimization problem in the path domain and the equivalent mechanical problem, and establish a mapping table between the initial tension direction angle and the rope physical parameters. The restoration module is used to construct the optimal rope configuration and restore it to the continuous trajectory of the UAV, depending on whether there is sufficient flight time. The UAV trajectory design system under the constraint of a fixed-point cruise mission is used to perform the steps in the UAV trajectory design method under the constraint of a fixed-point cruise mission as described in any one of claims 1-9.

Images