An unmanned aerial vehicle threat avoidance method based on decision and control delay speed obstacle method

Abstract

This invention discloses a UAV threat avoidance method based on the decision and control delay speed obstacle method, comprising: threat detection: during mission execution, the UAV continuously acquires flight status information of itself and threat sources in the airspace, including speed, position, and heading; based on the flight status information of the UAV and the threat source, it is determined whether the UAV is at risk of being detected; if so, threat avoidance and trajectory recovery are performed; threat avoidance and trajectory recovery: based on whether the UAV's heading change is within the heading change range, it is determined whether threat avoidance should be performed; if it is within the range, the heading adjustment amount required to avoid the threat source is calculated, and then the UAV's heading is adjusted to perform threat avoidance, and then the heading is restored. This invention can serve as an extension of UAV autonomous trajectory planning technology, enabling UAVs to effectively avoid threat sources encountered during flight, improving the safety of UAV trajectory planning, and increasing the robustness of UAV combat missions.

Description

Technical Field

[0001] This invention relates to the field of autonomous obstacle avoidance flight decision-making technology for unmanned aerial vehicles (UAVs), and in particular to a UAV threat avoidance method based on decision and control delay speed obstacle method. Background Technology

[0002] With continuous advancements in defense technology, unmanned systems face increasingly complex situations and a growing number of threats when performing intelligence reconnaissance and surveillance, offensive and defensive combat missions. In recent years, researchers have been exploring unmanned system technologies in greater depth, and unmanned combat is gradually moving from theory to engineering practice. For unmanned aerial vehicles (UAVs), threat avoidance is a hot research topic. The speed obstacle method is one of the important approaches to achieving threat avoidance.

[0003] Current research on velocity-based obstacle avoidance methods primarily focuses on improving existing obstacle avoidance techniques. Some international scholars have proposed using the velocity cone method for collision detection, and employing nonlinear geometric guidance and differential geometric guidance to enable UAVs to quickly determine their course. Others have used the potential field method, establishing the repulsive force of obstacles and the attractive force of targets to achieve obstacle avoidance. Existing potential field collision avoidance methods often combine with intelligent algorithms, such as the A* algorithm and genetic algorithms, to achieve collision avoidance by dividing the target region. However, these algorithms only optimize the collision avoidance mechanism and do not fully consider the actual situation, such as autonomous decision-making and control delays after obstacle detection. This leads to discrepancies between the algorithm results and actual performance, posing a risk of collision avoidance failure.

[0004] Therefore, researching a UAV threat avoidance method based on decision and control delay speed barrier method is of great theoretical and practical significance for UAV autonomous threat avoidance. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a drone threat avoidance method based on the decision and control delay speed obstacle method, which addresses the deficiencies in the prior art.

[0006] The technical solution adopted by this invention to solve its technical problem is:

[0007] This invention provides a drone threat avoidance method based on decision and control delay velocity obstacle method, the method comprising the following steps:

[0008] Threat Detection:

[0009] During missions, drones continuously acquire flight status information of themselves and threat sources in the airspace through various devices, including radar, including speed, position, and heading.

[0010] Based on the flight status information of the drone and the threat source, determine whether the drone is at risk of being detected. If there is no risk of being detected, continue threat detection; if there is a risk of being detected, perform threat avoidance and flight path recovery.

[0011] Threat avoidance and track recovery:

[0012] Whether threat avoidance should be carried out depends on whether the change in the drone's heading is within the range of the heading change. If it is within the range, the heading adjustment required to avoid the threat source is calculated, and the drone's heading is adjusted to avoid the threat before restoring the heading. If it is not within the range, other avoidance measures, including electronic jamming of the threat source, are adopted.

[0013] Furthermore, the method for determining whether a drone is at risk of being detected in this invention employs the speed barrier method, specifically:

[0014] The speed barrier method defines a relative speed barrier zone. When the direction of the relative speed coincides with this zone, the drone is at risk of being detected by a threat source; otherwise, there is no risk of detection.

[0015] Furthermore, the method for defining the relative velocity barrier region in this invention is as follows:

[0016] Let points A and O represent the centers of the drone and the threat source, respectively, and their velocities be v1 and v2, respectively. The relative velocity between the drone and the threat source is v. R = v1 - v2, where α is the angle between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone, and γ is the angle between the line AO ​​connecting the drone and the threat source and the relative velocity v. R The angle between them;

[0017] definition Among them l AO The relative velocity v R The line in question, The safe zone surrounding the threat source is represented by the relative velocity v. R The safe zone between the line of sight and the threat source A non-empty set.

[0018] Furthermore, the calculation method in the method of the present invention includes:

[0019] Calculate the angle α between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone:

[0020] α = arcsin(d1 / D0)

[0021] Using complex numbers to represent the speed of the drone and the threat source, then:

[0022] v1 = v1(cosα1 + i sinα1)

[0023] v2 = v2(cosα2 + i sinα2)

[0024] In the formula: α1 and α2 are the angles between the drone and the threat source and the positive x-axis, respectively; then the velocity of the drone relative to the threat source is:

[0025] v R =v1-v2=(v1 cosα1-v2cosα2)+i(v1 sinα1-v2 sinα2)

[0026] Assuming the drone and the threat source continue moving along their respective flight paths, their initial positions in the conflict avoidance phase are respectively... and If both the heading and speed remain unchanged, then after time t, the position of the UAV is represented as:

[0027]

[0028] After time t, the location of the threat source is represented as:

[0029]

[0030] After time t is calculated, the distance between the drone and the threat source is:

[0031]

[0032] When a drone avoids a threat source, it requires a certain decision-making time and control delay. Let the decision-making time be Δt1 and the control delay be Δt2. Then, the position of the drone after time t is represented as:

[0033]

[0034] Further calculations were performed to determine the distance between the drone and the threat source after time t:

[0035]

[0036] To simplify the expression, let

[0037] Then, after time t, the distance between the drone and the threat source is:

[0038] D 2 (t)=((Δv x ) 2 +(Δv y ) 2 )t0 2 +2(ΔxΔv x+ΔyΔv y )t0+D1 2

[0039] If (Δv) x ) 2 +(Δv y ) 2 If the distance between the drone and the threat source is not equal to 0, then the expression for D is... 2 Let (t) be a parabola. According to the properties of a parabola, if Δx Δv x +ΔyΔv y If the value is less than 0, the distance between the drone and the threat source gradually decreases, meaning the drone is at risk of being detected by the threat source. To further determine whether the drone will enter the threat source's detection range, D... 2 Differentiating (t) with respect to t, we get:

[0040] dD 2 (t) / dt=2((Δv x ) 2 +(Δv v ) 2 )t+2(ΔxΔv x +ΔyΔv v )

[0041] Let dD 2 Since (t) / dt = 0, we get:

[0042]

[0043] Substituting into the distance formula, the minimum distance between the drone and the threat source is:

[0044]

[0045] The time consumed by the decision-making and control latency of the drone is much less than the time required for conflict between the drone and the threat source. Therefore, the above formula can be approximated as follows:

[0046]

[0047] Based on geometric relationships, the following can be calculated:

[0048] γ=arcsin(d min / D0)

[0049] When the relative velocity v R The line l AO When landing in a speed obstacle zone, the drone is at risk of being detected; otherwise, there is no risk of detection. That is, when α > γ, the drone is at risk of flight conflict, and when α ≤ γ, the drone is not at risk of being detected.

[0050] Furthermore, the method for calculating the heading adjustment required to avoid the threat source in the method of the present invention is specifically as follows:

[0051] Converting the time delay caused by drone decision-making and control into the distance of the speed obstacle zone, we have:

[0052]

[0053] The angle α between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone should be modified to α':

[0054] α' = arcsin(d1' / D0)

[0055] Within low-altitude airspace, according to the model assumptions, the UAV and the threat source are at the same altitude layer. Based on the relative velocity vector diagram before and after the UAV's heading adjustment, the relative velocity v between the UAV and the threat source is... R The angle between v2 and v2 is ε. After the UAV's heading is adjusted, the relative speed v R The angle between v2 and v2 is ε.

[0056] Calculate the relative velocity v of the UAV after heading adjustment based on geometric relationships. R The angle between v2 and v2 is ε.

[0057] ε'=θ2+α'

[0058] In the velocity vector triangle after heading adjustment, by the law of sines:

[0059]

[0060] Solving for:

[0061] θ1′=arcsin(v2sin(ε′) / v1)+α'

[0062] During threat avoidance, the UAV's heading adjustment Δθ1 is:

[0063] Δθ1=θ1′-θ1=arcsin(v2sin(θ2+α′) / v1)+α′-θ1

[0064] Threat avoidance can be achieved by adjusting the course.

[0065] Furthermore, the method for restoring the course in the method of the present invention specifically includes:

[0066] After the UAV completes threat avoidance at point P on the relative heading, it resumes its flight path. Point E is the tangent point between the relative flight path AP and the safety circle of the threat source. When the UAV reaches point P, it begins to resume its flight path. A' is the UAV's flight path recovery point. According to the UAV heading adjustment method, AP and A'P are symmetrical about OP, and AP = A'P. Point F is the tangent point between the relative flight path A'P and the safety circle of the threat source.

[0067] Based on geometric relationships, the relative distance S during drone threat avoidance is:

[0068]

[0069] At this point, the threat avoidance time t m for:

[0070]

[0071] That is, once the drone's flight path recovery point P is determined, when the drone reaches point P, it changes its course and recovers its original flight path;

[0072] In the velocity vector triangle for drone threat avoidance, the drone's avoidance velocity v1' and the relative avoidance velocity v' R The angle between for:

[0073]

[0074] In the velocity vector triangle for UAV trajectory recovery, the relative velocity v” R The angle between v2 and v2 is ε”:

[0075] ε”=ε'-2β

[0076] By the Law of Sines:

[0077]

[0078] Solving for:

[0079]

[0080] The heading adjustment Δθ1' when the UAV recovers its trajectory is:

[0081]

[0082] The heading is restored based on the heading adjustment amount when the drone's track is restored.

[0083] This invention provides a drone threat avoidance system based on the decision and control delay velocity obstacle method, comprising:

[0084] The threat detection unit is used to continuously acquire flight status information of itself and threat sources in the airspace through various devices, including radar, during the execution of a mission. This information includes speed, position, and heading. Based on the flight status information of the UAV and the threat source, it determines whether the UAV is at risk of being detected. If there is no risk, it continues to perform threat detection. If there is a risk, it performs threat avoidance and track recovery.

[0085] The threat avoidance and track recovery unit is used to determine whether to take threat avoidance measures based on whether the change in the UAV's heading is within the heading change range. If it is within the range, it calculates the heading adjustment required to avoid the threat source, adjusts the UAV's heading to avoid the threat, and then restores the heading. If it is not within the range, it adopts other avoidance measures, including electronic interference with the threat source.

[0086] The beneficial effects of this invention are:

[0087] This invention proposes a threat avoidance decision-making method for unmanned aerial vehicles (UAVs) based on the speed obstacle method. It introduces the speed obstacle method and defines a method for determining the safe range of threat sources. After threat detection, threat avoidance and trajectory recovery methods are employed. This method accurately calculates the directional adjustment amount for trajectory recovery, ensuring that the designated mission can still be completed after evading the threat using speed obstacle avoidance. This invention's method can serve as an extension to UAV autonomous trajectory planning technology, enabling UAVs to effectively avoid potential threats during flight, improving the safety of UAV trajectory planning, and thus increasing the robustness of UAV combat missions. Attached Figure Description

[0088] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0089] Figure 1 This is a schematic diagram of a speed obstacle model according to an embodiment of the present invention;

[0090] Figure 2 This is a schematic diagram of the flight state according to an embodiment of the present invention;

[0091] Figure 3 This is a schematic diagram of the relative velocity vector of the UAV before and after heading adjustment according to an embodiment of the present invention;

[0092] Figure 4 This is a schematic diagram illustrating the recovery of a drone's flight path according to an embodiment of the present invention;

[0093] Figure 5 This is a flowchart of drone threat avoidance according to an embodiment of the present invention. Detailed Implementation

[0094] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0095] Unmanned aerial vehicle (UAV) target threat avoidance refers to a maneuvering decision-making method used by UAVs to maneuver and avoid potential threats during specific missions such as reconnaissance, search, and rescue, thereby improving their survivability. This invention proposes a UAV threat avoidance decision-making method based on the speed obstacle method. First, the risk level of UAV flight is assessed by analyzing the spatial geometric relationship and relative velocity vector between the UAV and the target. Then, based on information such as the threat source's position and speed, the required heading adjustment to avoid the threat source is calculated. Finally, the feasibility of the calculated heading adjustment is judged, and the effectiveness of the threat avoidance is output. This invention can serve as an extension to UAV autonomous trajectory planning technology, enabling UAVs to effectively avoid potential threats during flight, improving the safety of UAV trajectory planning, and thus increasing the robustness of UAV combat missions.

[0096] like Figures 1-5 As shown, attached Figure 1 This describes the possible relative positional relationships between the UAV and threat sources during flight, and further provides a geometric description of the speed barrier zone. (Appendix) Figure 2 This describes a method for decomposing the velocity vector of a UAV based on the velocity obstacle zone. (Appendix) Figure 3 This describes the change in relative velocity vector of a UAV after adjusting its course to avoid threats during flight. (Appendix) Figure 4 A geometric calculation method for recovering a flight path after avoiding a threat is described. (Appendix) Figure 5 The main process of using speed obstacle avoidance tactics during drone flight is described.

[0097] In a specific embodiment of the present invention, the speed barrier method defines a relative speed barrier region. When the direction of the relative speed coincides with this region, the drone is considered to be at risk of being detected by a threat source; otherwise, it is not. The key to determining whether a drone is at risk of being detected is calculating the relative speed between the drone and the threat source; therefore, relative speed can be used as the research object.

[0098] Appendix Figure 1 In the diagram, points A and O represent the centers of the drone and the threat source, respectively, with velocities v1 and v2. The relative velocity between the drone and the threat source is v. R = v1 - v2, where α is the angle between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone, and γ is the angle between the line AO ​​connecting the drone and the threat source and the relative velocity v. R The angle between them.

[0099] A Cartesian coordinate system is established with the center of the threat source as the origin, OA as the positive x-axis, and the vertical direction perpendicular to OA as the positive y-axis. The velocities of the drone and the threat source are v1 and v2, respectively, and the drone's velocity relative to the threat source is v. R v R The angle between v and the x-axis is γ, v R The angle between v and the boundary line of the velocity barrier is β, v R The angle between the drone and v2 is ε, and the angles between the drone's velocities v1 and v2 and the x-axis are θ1 and θ2, respectively. The initial distance between the drone and the threat source is D0.

[0100] From the appendix Figure 2 Based on the geometric relationship, the angle α between the line AO ​​connecting the UAV and the threat source and the boundary of the velocity obstacle zone can be calculated:

[0101] α = arcsin(d1 / D0)

[0102] For ease of analysis, we use complex numbers to represent the speeds of the drone and the threat source, then:

[0103] v1 = v1(cosα1 + i sinα1)

[0104] v2 = v2(cosα2 + i sinα2)

[0105] In the formula: α1 and α2 are the angles between the drone and the threat source and the positive x-axis, respectively. Then the velocity of the drone relative to the threat source is:

[0106] v R =v1-v2=(v1 cosα1-v2cosα2)+i(v1 sinα1-v2 sinα2)

[0107] Assuming the drone and the threat source continue moving along their respective flight paths, their initial positions in the conflict avoidance phase are respectively... and If both the heading and speed remain unchanged, then after time t, the position of the UAV can be represented as:

[0108]

[0109] After time t, the location of the threat source can be represented as:

[0110]

[0111] Based on the above formula, the distance between the drone and the threat source after time t can be calculated as follows:

[0112]

[0113] When a drone avoids a threat source, it requires a certain decision-making time and control delay. Let the decision-making time be Δt1 and the control delay be Δt2. Then, the position of the drone after time t can be represented as:

[0114]

[0115] Accordingly, the distance between the drone and the threat source after time t is further calculated:

[0116]

[0117] To simplify the expression, let

[0118] Then, after time t, the distance between the drone and the threat source is:

[0119]

[0120] If (Δv) x ) 2 +(Δv y ) 2 If the distance between the drone and the threat source is not equal to 0, then the expression for D is... 2 Let (t) be a parabola. According to the properties of a parabola, if Δx Δv x +ΔyΔv y If the value is less than 0, the distance between the drone and the threat source gradually decreases, meaning the drone is at risk of being detected by the threat source. To further determine whether the drone will enter the threat source's detection range, D... 2 Differentiating (t) with respect to t, we get:

[0121] dD 2 (t) / dt=2((Δv x ) 2 +(Δv v ) 2 )t+2(ΔxΔv x +ΔyΔv v )

[0122] Let dD 2 Since (t) / dt = 0, we get:

[0123]

[0124] Substituting the above formula into the original distance formula, we can obtain the minimum distance between the drone and the threat source as follows:

[0125]

[0126] Typically, the time consumed by the decision-making and control delay of a drone is much less than the time required for a conflict between the drone and the threat source. Therefore, for ease of calculation, the above formula can be approximated as follows:

[0127]

[0128] According to the appendix Figure 2 The geometric relationships in the figure can be used to calculate:

[0129] γ=arcsin(d min / D0)

[0130] According to the description, when the relative velocity v R The line l AO When landing in a speed obstacle zone, the drone faces the risk of being detected; otherwise, there is no risk of detection. That is, when α > γ, the drone faces a flight conflict; when α ≤ γ, the drone faces no risk of being detected.

[0131] Converting the time delay caused by drone decision-making and control into the distance of the speed obstacle zone, we have:

[0132]

[0133] Accordingly, the angle α between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone should be modified to α':

[0134] α' = arcsin(d1' / D0)

[0135] Within low-altitude airspace, according to the model assumptions, the UAV and the threat source are at the same altitude layer. Based on the relative velocity vector diagram before and after the UAV's heading adjustment, the relative velocity v between the UAV and the threat source is... R The angle between v2 and v2 is ε. The red dashed line represents the selectable heading range of the UAV. After the UAV's heading is adjusted, the relative speed v R The angle between v2 and v2 is ε.

[0136] According to the appendix Figure 3 Based on geometric relationships, the relative velocity v of the UAV after heading adjustment can be calculated. R The angle between v2 and v2 is ε.

[0137] ε'=θ2+α'

[0138] In the velocity vector triangle after heading adjustment, the law of sines yields the following:

[0139]

[0140] Solving for:

[0141] θ1′=arcsin(v2sin(ε′) / v1)+α'

[0142] During threat avoidance, the UAV's heading adjustment Δθ1 is:

[0143] Δθ1=θ1′-θ1=arcsin(v2sin(θ2+α′) / v1)+α′-θ1

[0144] While adjusting its course can help avoid threats, this alters the drone's original flight path, significantly impacting its flight plan and potentially preventing it from completing its mission. Therefore, it is necessary to restore the drone's original flight path after successfully avoiding the threat.

[0145] Appendix Figure 4 The diagram illustrates the trajectory recovery process of a UAV at point P after completing threat avoidance. Point E is the tangent point between the relative flight path AP and the safety circle of the threat source. When the UAV reaches point P, trajectory recovery begins. A' is the UAV trajectory recovery point. According to the UAV heading adjustment method, AP and A'P are symmetrical about OP, and AP = A'P. Point F is the tangent point between the relative flight path A'P and the safety circle of the threat source.

[0146] According to the appendix Figure 4 Based on geometric relationships, the relative distance S during drone threat avoidance is derived as follows:

[0147]

[0148] At this point, the threat avoidance time t m for:

[0149]

[0150] That is, the drone's flight path recovery point P can be determined. When the drone reaches point P, it changes its course and recovers its original flight path.

[0151] In the velocity vector triangle for drone threat avoidance, the drone's avoidance velocity v1' and the relative avoidance velocity v' R The angle between for:

[0152]

[0153] In the velocity vector triangle for UAV trajectory recovery, the relative velocity v” R The angle between v2 and v2 is ε”:

[0154] ε”=ε'-2β

[0155] By the Law of Sines:

[0156]

[0157] Solving for:

[0158]

[0159] The heading adjustment Δθ1' when the UAV recovers its trajectory is:

[0160]

[0161] During missions in low-altitude airspace, drones, with the help of radar and other equipment, continuously acquire flight status information such as speed, position, and heading of themselves and threat sources within the airspace. Based on trajectory prediction models, they detect whether there is a risk of being detected. If there is no risk, they continue to detect threats. If there is a risk, they adjust their heading to avoid the threat. If they cannot avoid the threat, they consider other means, such as electronic jamming of the threat source.

[0162] See attached document for drone threat avoidance and flight path recovery procedures. Figure 5 First, based on the trajectory prediction model, it is determined whether there is a risk of detection between the drone and the threat source. Then, it is determined whether to adopt a course avoidance method based on whether the change in the drone's heading is within the heading change range. If not, other means are considered to avoid the threat.

[0163] It should be understood that the sequence number of each step in the above embodiments does not imply 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 embodiments of this application.

[0164] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A drone threat avoidance method based on decision and control delay velocity obstacle method, characterized in that, The method includes the following steps: Threat Detection: During missions, drones continuously acquire flight status information of themselves and threat sources in the airspace through various devices, including radar, including speed, position, and heading. Based on the flight status information of the drone and the threat source, determine whether the drone is at risk of being detected. If there is no risk of being detected, continue threat detection; if there is a risk of being detected, perform threat avoidance and flight path recovery. Threat avoidance and track recovery: Whether threat avoidance should be carried out depends on whether the change in the drone's heading is within the range of the heading change. If it is within the range, the heading adjustment required to avoid the threat source is calculated, and the drone's heading is adjusted to avoid the threat before restoring the heading. If it is not within the range, other avoidance measures, including electronic jamming of the threat source, are adopted.

2. The UAV threat avoidance method based on decision and control delay speed obstacle method according to claim 1, characterized in that, The speed barrier method is used to determine whether a drone is at risk of being detected. Specifically: The speed barrier method defines a relative speed barrier zone. When the direction of the relative speed coincides with this zone, the drone is at risk of being detected by a threat source; otherwise, there is no risk of detection.

3. The UAV threat avoidance method based on decision and control delay speed obstacle method according to claim 2, characterized in that, The method for defining the relative velocity barrier region is as follows: Let points A and O represent the centers of the drone and the threat source, respectively, and their velocities be v1 and v2, respectively. The relative velocity between the drone and the threat source is v. R = v1 - v2, where α is the angle between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone, and γ is the angle between the line AO ​​connecting the drone and the threat source and the relative velocity v. R The angle between them; definition Among them l AO The relative velocity v R The line in question, The safe zone surrounding the threat source is represented by the relative velocity v. R The safe zone between the line of sight and the threat source A non-empty set.

4. The UAV threat avoidance method based on decision and control delay speed obstacle method according to claim 3, characterized in that, The calculation methods in this method include: Calculate the angle α between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone: α = arcsin(d1 / D0) Using complex numbers to represent the speed of the drone and the threat source, then: v1 = v1(cosα1 + isinα1) v2 = v2(cosα2 + isinα2) In the formula: α1 and α2 are the angles between the drone and the threat source and the positive x-axis, respectively; then the velocity of the drone relative to the threat source is: v R =v1-v2=(v1cosα1-v2cosα2)+i(v1sinα1-v2sinα2) Assuming the drone and the threat source continue moving along their respective flight paths, their initial positions in the conflict avoidance phase are respectively... and If both the heading and speed remain unchanged, then after time t, the position of the UAV is represented as: After time t, the location of the threat source is represented as: After time t is calculated, the distance between the drone and the threat source is: When a drone avoids a threat source, it requires a certain decision-making time and control delay. Let the decision-making time be Δt1 and the control delay be Δt2. Then, the position of the drone after time t is represented as: Further calculations were performed to determine the distance between the drone and the threat source after time t: To simplify the expression, let Then, after time t, the distance between the drone and the threat source is: D 2 (t)=((Δv x ) 2 +(Δv y ) 2 )t0 2 +2(ΔxΔv x +ΔyΔv y )t0+D1 2 If (Δv) x ) 2 +(Δv y ) 2 If the distance between the drone and the threat source is not equal to 0, then the expression for D is... 2 Let (t) be a parabola. According to the properties of a parabola, if Δx Δv x +ΔyΔv y If the value is less than 0, the distance between the drone and the threat source gradually decreases, meaning the drone is at risk of being detected by the threat source. To further determine whether the drone will enter the threat source's detection range, D... 2 Differentiating (t) with respect to t, we get: dD 2 (t) / dt=2((Δv x ) 2 +(Δv v ) 2 )t+2(ΔxΔv x +ΔyΔv v ) Let dD 2 Since (t) / dt = 0, we get: Substituting into the distance formula, the minimum distance between the drone and the threat source is: The time consumed by the decision-making and control latency of the drone is much less than the time required for conflict between the drone and the threat source. Therefore, the above formula can be approximated as follows: Based on geometric relationships, the following can be calculated: γ=arcsin(d min / D0) When the relative velocity v R The line l AO When landing in a speed obstacle zone, the drone is at risk of being detected; otherwise, there is no risk of detection. That is, when α > γ, the drone is at risk of flight conflict, and when α ≤ γ, the drone is not at risk of being detected.

5. The UAV threat avoidance method based on decision and control delay speed obstacle method according to claim 4, characterized in that, The specific method for calculating the course adjustment required to avoid the threat source in this approach is as follows: Converting the time delay caused by drone decision-making and control into the distance of the speed obstacle zone, we have: The angle α between the line AO ​​connecting the drone and the threat source and the boundary of the speed obstacle zone should be modified to α': α' = arcsin(d′1 / D0) Within low-altitude airspace, according to the model assumptions, the UAV and the threat source are at the same altitude layer. Based on the relative velocity vector diagram before and after the UAV's heading adjustment, the relative velocity v between the UAV and the threat source is... R The angle between v2 and v2 is ε. After the UAV's heading is adjusted, the relative speed v R The angle between v' and v2 is ε'; Calculate the relative velocity v of the UAV after heading adjustment based on geometric relationships. R The angle between v2 and v2 is ε. ε'=θ2+α' In the velocity vector triangle after heading adjustment, by the law of sines: Solving for: θ'1=arcsin(v2sin(ε') / v1)+α' During threat avoidance, the UAV's heading adjustment Δθ1 is: Δθ1=θ′1-θ1=arcsin(v2sin(θ2+α′) / v1)+α′-θ1 Threat avoidance can be achieved by adjusting the course.

6. The UAV threat avoidance method based on decision and control delay speed obstacle method according to claim 5, characterized in that, The specific method for restoring the course in this method is as follows: After the UAV completes threat avoidance at point P on the relative heading, it resumes its flight path. Point E is the tangent point between the relative flight path AP and the safety circle of the threat source. When the UAV reaches point P, it begins to resume its flight path. A' is the UAV's flight path recovery point. According to the UAV heading adjustment method, AP and A'P are symmetrical about OP, and AP = A'P. Point F is the tangent point between the relative flight path A'P and the safety circle of the threat source. Based on geometric relationships, the relative distance S during drone threat avoidance is: At this point, the threat avoidance time t m for: That is, once the drone's flight path recovery point P is determined, when the drone reaches point P, it changes its course and recovers its original flight path; In the velocity vector triangle for drone threat avoidance, the drone's avoidance velocity v′1 and the relative avoidance velocity v′ R The angle between for: In the velocity vector triangle for UAV trajectory recovery, the relative velocity v″ R The angle between v2 and v2 is ε”: ε”=ε'-2β By the Law of Sines: Solving for: Then the heading adjustment Δθ′1 when the UAV recovers its trajectory is: The heading is restored based on the heading adjustment amount when the drone's track is restored.

7. A drone threat avoidance system based on the decision-making and control delay speed obstacle method, characterized in that, include: The threat detection unit is used to continuously acquire flight status information of itself and threat sources in the airspace through various devices, including radar, during the execution of a mission. This information includes speed, position, and heading. Based on the flight status information of the UAV and the threat source, it determines whether the UAV is at risk of being detected. If there is no risk, it continues to perform threat detection. If there is a risk, it performs threat avoidance and track recovery. The threat avoidance and track recovery unit is used to determine whether to take threat avoidance based on whether the change in the UAV's heading is within the heading change range; if it is within the range, it calculates the heading adjustment required to avoid the threat source, adjusts the UAV's heading to avoid the threat, and then restores the heading. If it is outside the scope, other evasion methods, including electronic interference with the threat source, will be adopted.

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