Method and device for predicting inter-aircraft collision in formation flight of unmanned aerial vehicles

Abstract

The invention provides an inter-aircraft collision prediction method and device in formation flight of unmanned aerial vehicles, and the method comprises the steps: S10, judging whether to carry out the collision prediction of a local aircraft or not according to a preset unmanned aerial vehicle starting anti-collision prediction condition; s20, calculating a safe flight height 2 [delta] H; s30, calculating a safe flight horizontal distance delta R; s40, establishing a cylindrical anti-collision area, when the anti-collision areas between the unmanned aerial vehicles are predicted not to coincide, determining that no collision occurs between the unmanned aerial vehicles, otherwise, determining that there is a collision risk between the unmanned aerial vehicles; s50, acquiring the three-axis position and the three-axis speed of the other aircraft relative to the course of the local aircraft; s60, the forward speed V0xt 'and the lateral speed V0yt' of the local machine are predicted; s70, according to the three-axis position and the three-axis speed of the other aircraft relative to the course of the aircraft, the forward speed Vxt'and the lateral speed Vyt 'of the other aircraft relative to the aircraft are predicted; s80, predicting the position St'of the other machine relative to the local machine; and S90, according to the position St'of the other machine relative to the local machine and the cylindrical anti-collision area, collision prediction judgment is carried out.

Description

Technical Field

[0001] The present invention belongs to UAV cluster flight control technology, and in particular relates to a method and device for predicting collisions between UAVs in UAV formation flight. Background Art

[0002] Drones play an increasingly important role in military and civilian missions. Drone swarms can complete tasks that a single drone cannot complete, such as collaborative search, through formation collaboration, and also improve the efficiency and success rate of mission execution. With the development of drone clusters and drone swarms, the demand for large-scale intensive drone flights is increasing. In addition, during the flight of drone formations, the risk of collision between drones is increased due to factors such as airborne equipment failures, environmental interference, limitations in algorithm application, and inter-machine transmission and communication delays. Summary of the invention

[0003] The present invention proposes a method and device for predicting collisions between drones in formation flight, aiming to solve the problem of high false alarm rate of collision prediction between drones in the process of drone formation flight.

[0004] In a first aspect, the present application provides a method for predicting collisions between drones in formation flight, the method comprising:

[0005] S10, judging whether to perform a collision prediction of the drone according to the pre-set UAV startup collision avoidance prediction conditions;

[0006] S20, calculating the safe flight altitude 2ΔH;

[0007] S30, calculating the safe flight horizontal distance ΔR;

[0008] S40, establishing a cylindrical anti-collision area with the center of gravity of the aircraft as the center, a height of 2ΔH being the safe flight height, and a radius of ΔR being the safe flight horizontal distance. When it is predicted that the anti-collision areas between the UAVs will not overlap, it is determined that there is no collision between the UAVs. Otherwise, it is determined that there is a collision risk between the UAVs.

[0009] S50, obtaining the forward position P of the other aircraft relative to the heading of the aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z ;

[0010] S60, predict the forward speed V of the aircraft 0x _t', lateral speed V 0y _t';

[0011] S70, based on the forward position P of the other aircraft relative to the heading of the aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z , predict the forward speed V of the other aircraft relative to the own aircraft x _t', lateral speed V y _t';

[0012] S80, according to Predict the forward speed V of the other aircraft relative to the own aircraft at time t' x _t'River lateral speed V y _t', predict the relative position of the other aircraft to this aircraft S_t';

[0013] S90, predict and determine the collision based on the relative position of the other aircraft to the aircraft itself, St', and the cylindrical anti-collision area.

[0014] Furthermore, S10 includes:

[0015] S101, obtaining the status of the aircraft's positioning system, the status of the inter-aircraft link, and the flight phase;

[0016] S102: When one of the following conditions is met, the collision prediction of the local computer is not performed; otherwise, the collision prediction of the local computer is performed:

[0017] 1) The machine's positioning system status is faulty;

[0018] 2) The link status between the local machines is faulty;

[0019] 3) The aircraft is in the automatic flight stage in the air.

[0020] Furthermore, S20 includes:

[0021] S201. Obtain the absolute value H_error of the steady-state error of the altitude control of the UAV, the fuselage length L, and the maximum climbing track angle γ from the UAV performance library. max , obtain the longitudinal separation distance Formation_H of the formation units from the formation performance library;

[0022] S202, based on the absolute value H_error, the fuselage length L, and the maximum climb track angle γ max The vertical separation distance Formation_H of the formation unit is used to calculate the safe flight altitude 2ΔH, where the value range of ΔH is [H_min,H_max].

[0023]

[0024] H_min=sin(γ max )·L+H_error.

[0025] Furthermore, S30 includes:

[0026] S301, obtaining the wingspan length b of the drone from the drone performance library, and obtaining the forward separation distance Formation_X and the lateral separation distance Formation_Y of the formation units from the formation performance library;

[0027] S302, according to the wingspan length b of the UAV, the forward separation distance Formation_X of the formation unit and the lateral separation distance Formation_Y of the formation unit, the safe flight horizontal distance of the UAV is calculated as ΔR, and the value range of ΔR is (R_min, R_max], where,

[0028] R_max is and The large value in

[0029] R_min is the smaller value of L and b.

[0030] Furthermore, S50 includes:

[0031] S501, obtaining the relative position and relative speed of the other machine from the inter-machine link;

[0032] S502, establish the heading coordinate system of the aircraft, with the center of gravity of the aircraft as the coordinate origin, the current speed direction of the aircraft as the x-axis, the vertical horizontal ground upward as the z-axis, and the y-axis determined by the left-hand rule;

[0033] S503, the relative position and relative speed of the other aircraft are transformed into the heading coordinate system of the own aircraft through coordinate transformation, and the forward position P of the other aircraft relative to the own aircraft is obtained. x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z .

[0034] Furthermore, S60 includes:

[0035] S601, obtain the tilt angle of the aircraft n times before the calculation time, and average the tilt angle of the aircraft n times to obtain Among them, the value range of n is [1, ΔT / Δt], ΔT is the data transmission period between machines, and Δt is the local calculation period; obtain the local speed n beats before the calculation time, and average it n beats to get

[0036] S602: Obtain the forward velocity, lateral velocity, and vertical velocity n times before the calculation time, and average them n times to obtain

[0037] S603, according to and The turning angle rate dψ0 of the other aircraft at the predicted time t' is calculated as follows:

[0038]

[0039] Where g is the acceleration due to gravity;

[0040] S604, according to the turning angle rate dψ0 and Calculate the forward speed V of the aircraft at the predicted time t' as follows: 0x _t', lateral speed V 0y _t' are

[0041]

[0042] Furthermore, S70 includes:

[0043] S701, obtain the forward position P of the other aircraft relative to the heading of the aircraft n times before the calculation time x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z , and average them by n times to get

[0044] S702: Obtain the tilt angle of the other machine n times before the calculation time through the inter-machine link, and average the tilt angle of the other machine n times before the calculation time.

[0045] S703, obtain the local speed n beats before the calculation time, and average it n beats to obtain

[0046]

[0047] S704, according to and The turn rate of the aircraft at the predicted time t' is calculated as follows:

[0048]

[0049] S705, according to and the turning angle rate dψ0, the forward speed V of the other aircraft relative to the own aircraft at the predicted time t' is calculated as follows: x _t', lateral speed V y_t' are

[0050]

[0051] Furthermore, S80 includes:

[0052] S801, calculate the average speed of the other machine relative to the machine in three axes at the predicted time t'

[0053]

[0054] S802. Calculate the position S_t of the other machine relative to the local machine at the predicted time t' as follows:

[0055]

[0056] Furthermore, S90 includes:

[0057] S901, in the time range [0t max ] to find the predicted time t' of the other machine with the closest distance to the machine CAP At this time, the horizontal distance S_Hor and the height difference S_Ver of the other aircraft relative to the local aircraft are respectively

[0058]

[0059] Among them, t max The upper limit of the collision prediction time is set;

[0060] S902, if S_Hor<2ΔR and S_Ver<2ΔH, then determine that the other machine and the local machine will be at t' CAP If the collision occurs after the predicted time, otherwise, it is determined that there is no risk of collision between the other aircraft and this aircraft within the predicted time range.

[0061] In a second aspect, the present application provides a device for predicting collisions between drones in formation flight, and the device is used to implement the above-mentioned method for predicting collisions between drones in formation flight.

[0062] To sum up, the present application provides a method and device for predicting collisions between drones in drone formation flight. By accurately predicting the risk of collision between drones, it can help to shorten the formation interval between drones, realize intensive coordinated flight of drone clusters, reduce the false alarm rate of collision prediction, and improve the safety of drone cluster flight. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 Schematic diagram of the effect of machine-to-machine collision prediction in Example 1 provided in the present application;

[0064] Figure 2A schematic diagram of the machine-to-machine collision prediction effect of Example 2 provided in the present application. DETAILED DESCRIPTION

[0065] The present invention provides a method for predicting collisions between drones in formation flight, comprising the following steps:

[0066] S10, judging whether to perform a collision prediction of the drone according to the pre-set UAV startup collision avoidance prediction conditions;

[0067] Specifically, S10 includes:

[0068] S101. Obtain the status of the aircraft's positioning system, the status of the inter-aircraft link, and the flight phase.

[0069] S102: When one of the following conditions is met, the collision prediction of the local computer is not performed; otherwise, the collision prediction of the local computer is performed:

[0070] 1) The machine's positioning system status is faulty;

[0071] 2) The link status between the local machines is faulty;

[0072] 3) The aircraft is in the automatic flight stage in the air.

[0073] S20, calculating the safe flight altitude 2ΔH;

[0074] Specifically, S20 includes:

[0075] S201. Obtain the absolute value H_error of the steady-state error of the altitude control of the UAV, the fuselage length L, and the maximum climbing track angle γ from the UAV performance library. max , obtain the longitudinal separation distance Formation_H of the formation units from the formation performance library.

[0076] S202, based on the absolute value H_error, the fuselage length L, and the maximum climb track angle γ max The vertical separation distance Formation_H of the formation unit is used to calculate the safe flight altitude 2ΔH, where the value range of ΔH is [H_min,H_max].

[0077]

[0078] H_min=sin(γ max )·L+H_error.

[0079] S30, calculating the safe flight horizontal distance ΔR;

[0080] Specifically, S30 includes:

[0081] S301. Obtain the wingspan length b of the drone from the drone performance library, and obtain the forward spacing distance Formation_X and the lateral spacing distance Formation_Y of the formation units from the formation performance library.

[0082] S302, according to the wingspan length b of the UAV, the forward separation distance Formation_X of the formation unit and the lateral separation distance Formation_Y of the formation unit, the safe flight horizontal distance of the UAV is calculated as ΔR, and the value range of ΔR is (R_min, R_max], where,

[0083]

[0084] R_min is the smaller value of L and b.

[0085] S40, establishing a cylindrical anti-collision area with the center of gravity of the aircraft as the center, a height of the safe flight height 2ΔH, and a radius of the safe flight horizontal distance ΔR. When it is predicted that the anti-collision areas between the UAVs will not overlap, it is determined that there is no collision between the UAVs. Otherwise, it is determined that there is a collision risk between the UAVs.

[0086] S50, obtaining the forward position P of the other aircraft relative to the heading of the aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z ;

[0087] Specifically, S50 includes:

[0088] S501. Obtain the relative position and relative speed of another machine from the inter-machine link.

[0089] S502, establish the heading coordinate system of the aircraft, with the center of gravity of the aircraft as the coordinate origin, the current speed direction of the aircraft as the x-axis, the vertical horizontal ground upward as the z-axis, and the y-axis determined by the left-hand rule.

[0090] S503, the relative position and relative speed of the other aircraft are transformed into the heading coordinate system of the own aircraft through coordinate transformation, and the forward position P of the other aircraft relative to the own aircraft is obtained. x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z .

[0091] S60, predict the forward speed V of the aircraft 0x _t', lateral speed V 0y_t';

[0092] Specifically, S60 includes:

[0093] S601, obtain the tilt angle of the aircraft n times before the calculation time, and average the tilt angle of the aircraft n times to obtain Among them, the value range of n is [1, ΔT / Δt], ΔT is the data transmission period between machines, and Δt is the local calculation period; obtain the local speed n beats before the calculation time, and average it n beats to get

[0094] S602: Obtain the forward velocity, lateral velocity, and vertical velocity n times before the calculation time, and average them n times to obtain

[0095] S603, according to and The turning angle rate dψ0 of the other aircraft at the predicted time t' is calculated as follows:

[0096]

[0097] Where g is the acceleration due to gravity.

[0098] S604, according to the turning angle rate dψ0 and Calculate the forward speed V of the aircraft at the predicted time t' as follows: 0x _t', lateral speed V 0y _t' are

[0099]

[0100] S70, based on the forward position P of the other aircraft relative to the heading of the aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z , predict the forward speed V of the other aircraft relative to the own aircraft x _t', lateral speed V y _t';

[0101] Specifically, S70 includes:

[0102] S701, obtain the forward position P of the other aircraft relative to the heading of the aircraft n times before the calculation time x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z, and average them by n times to get

[0103] S702: Obtain the tilt angle of the other machine n times before the calculation time through the inter-machine link, and average the tilt angle of the other machine n times before the calculation time.

[0104] S703, obtain the local speed n beats before the calculation time, and average it n beats to obtain

[0105]

[0106] S704, according to and The turn rate of the aircraft at the predicted time t' is calculated as follows:

[0107]

[0108] S705, according to and the turning angle rate dψ0, the forward speed V of the other aircraft relative to the own aircraft at the predicted time t' is calculated as follows: x _t', lateral speed V y _t' are

[0109]

[0110] S80, according to Predict the forward speed V of the other aircraft relative to the own aircraft at time t' x _t'River lateral speed V y _t', predict the relative position of the other aircraft to this aircraft S_t';

[0111] Specifically, S80 includes:

[0112] S801, calculate the average speed of the other machine relative to the machine in three axes at the predicted time t'

[0113]

[0114] S802. Calculate the position S_t of the other machine relative to the local machine at the predicted time t' as follows:

[0115]

[0116] S90, predict and determine the collision based on the relative position of the other aircraft to the aircraft itself, St', and the cylindrical anti-collision area.

[0117] Specifically, S90 includes:

[0118] S901, in the time range [0t max] to find the predicted time t' of the other machine with the closest distance to the machine CAP At this time, the horizontal distance S_Hor and the height difference S_Ver of the other aircraft relative to the local aircraft are respectively

[0119]

[0120] Among them, t max The upper limit of the collision prediction time is set.

[0121] S902, if S_Hor<2ΔR and S_Ver<2ΔH, then determine that the other machine and the local machine will be at t' CAP If the collision occurs after the predicted time, otherwise, it is determined that there is no risk of collision between the other aircraft and this aircraft within the predicted time range.

[0122] Embodiment 1

[0123] like Figure 1 As shown, the present application provides a method for predicting collisions between drones in formation flight, comprising:

[0124] S101, UAV start collision avoidance prediction condition determination:

[0125] S101A, obtain the status of the own aircraft's positioning system, the status of the inter-machine link, and the flight phase; S101 B, the status of the own aircraft's positioning system is normal, the status of the inter-machine link is normal, and the own aircraft is in the formation assembly flight phase, and perform collision prediction for the own aircraft:

[0126] S102, Safe flight altitude design:

[0127] S102A, obtain the absolute value of the steady-state error of the altitude control of the UAV from the UAV performance library. H_error is 0.1m, the fuselage length L is 2m, and the maximum climb track angle γ max The vertical spacing distance of the formation units, Formation_H, is 30o, and is 20m as obtained from the formation performance database.

[0128] S102B, the safe flight altitude of the UAV is designed to be 2ΔH. The range of ΔH [H_min,H_max] is calculated as [1.1,9.9] according to the following formula:

[0129]

[0130] H_min=sin(γ max )·L+H_error

[0131] Set ΔH to 3m.

[0132] S103, Safe flight horizontal distance design:

[0133] S103A, obtain the wingspan length b of the drone from the drone performance library as 2.2 m, obtain the forward separation distance Formation_X of the formation unit as 30 m, and the lateral separation distance Formation_Y of the formation unit as 20 m from the formation performance library.

[0134] S103B, design the safe flight horizontal distance of the UAV to be ΔR, according to R_max and The range of ΔR is calculated by the rule that R_min is the larger value in L and R_max is the smaller value in b, and ΔR is set to 5m.

[0135] S104, establishing a cylindrical anti-collision area with a height of 2ΔH and a radius of ΔR, with the center of gravity of the aircraft as the center. When it is predicted that the anti-collision areas between the UAVs will not overlap, it is determined that there is no collision between the UAVs. Otherwise, it is determined that there is a collision risk between the UAVs.

[0136] S105, obtaining the position and speed of the other aircraft relative to the heading of the own aircraft:

[0137] S105A, obtain the relative position and relative speed of the other machine from the inter-machine link.

[0138] S105B, establish the heading coordinate system of the aircraft, with the center of gravity of the aircraft as the coordinate origin, the current speed direction of the aircraft as the x-axis, the vertical horizontal ground upward as the z-axis, and the y-axis determined by the left-hand rule.

[0139] S105C, transform the relative position and relative speed of the other aircraft into the heading coordinate system of the own aircraft through coordinate transformation, and obtain the forward position P of the other aircraft relative to the own aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z .

[0140] S106, local speed prediction:

[0141] S106A, it is known that the data transmission cycle between machines is 0.1s, and Δt is the calculation cycle of the local machine is 0.01s. Therefore, the local machine tilt angle of 5 beats before the calculation time is obtained, and the average of the 5 beats is obtained.

[0142] S106B, obtain the forward speed, lateral speed, and vertical speed of the five beats before the calculation time, and average them for the five beats to obtain

[0143] S106C, calculate the turning angle rate dψ0 of the other aircraft at the predicted time t' as follows:

[0144]

[0145] Where g is the acceleration due to gravity.

[0146] S106D, calculate the forward speed V of the aircraft at the predicted time t' according to the following formula 0x _t', lateral speed V 0y _t' are

[0147]

[0148] S107, prediction of the speed of other aircraft relative to this aircraft:

[0149] S107A, take P 5 beats before the calculation time x , P y , P z 、V x 、V y 、V z , and average them by n times to get

[0150] S107B, obtain the tilt angle of the other machine 5 beats before the calculation time through the inter-machine link, and average the 5 beats to obtain

[0151] S107C, obtain the local tempo of the 5 beats before the calculation time, and average the 5 beats to obtain

[0152] S107D, calculate the turning angle rate of the aircraft at the predicted time t' as follows

[0153]

[0154] S107E, calculate the forward speed V of the other aircraft relative to the own aircraft at the predicted time t' according to the following formula x _t', lateral speed V y _t' are

[0155]

[0156] S108. Prediction of other aircraft's relative position to this aircraft:

[0157] S108A, calculate the average speed of the other machine relative to the machine in three axes at the predicted time t'

[0158]

[0159]

[0160] S108B, calculate the position S_t of the other machine relative to the machine at the predicted time t' as follows:

[0161]

[0162] S109: Preliminary collision prediction and determination:

[0163] S109A, in the time range [0t max ] to find the predicted time t' of the other machine with the closest distance to the machine CAP At this time, the horizontal distance S_Hor and the height difference S_Ver of the other aircraft relative to the local aircraft are respectively

[0164]

[0165] Among them, t max The upper limit of the collision prediction time is set to 1s.

[0166] S109B, before the simulation time 179.21s, S_Hor<2ΔR and S_Ver<2ΔH are not satisfied, it is determined that there is no risk of collision between the other aircraft and the own aircraft, and within the simulation time 175.76s to 180.34s, S_Hor<2ΔR and S_Ver<2ΔH are satisfied, it is determined that after t' CAP There will be collisions between time drones.

[0167] Embodiment 2

[0168] like Figure 2 As shown, the present application provides a method for predicting collisions between drones in formation flight, comprising:

[0169] S101, UAV start collision avoidance prediction condition determination:

[0170] S101A, obtain the status of the own aircraft's positioning system, the status of the inter-machine link, and the flight phase; S101B, the status of the own aircraft's positioning system is normal, the status of the inter-machine link is normal, and the own aircraft is in the formation change phase, and perform the own aircraft collision prediction:

[0171] S102, Safe flight altitude design:

[0172] S102A, obtain the absolute value of the steady-state error of the altitude control of the UAV from the UAV performance library. H_error is 0.1m, the fuselage length L is 2m, and the maximum climb track angle γ max The vertical spacing distance of the formation units, Formation_H, is 30o, and is 20m as obtained from the formation performance database.

[0173] S102B, the safe flight altitude of the UAV is designed to be 2ΔH. The range of ΔH [H_min,H_max] is calculated as [1.1,9.9] according to the following formula:

[0174]

[0175] H_min=sin(γ max )·L+H_error

[0176] Set ΔH to 1.5m.

[0177] S103, Safe flight horizontal distance design:

[0178] S103A, obtain the wingspan length b of the drone from the drone performance library as 2.2 m, obtain the forward separation distance Formation_X of the formation unit as 30 m, and the lateral separation distance Formation_Y of the formation unit as 20 m from the formation performance library.

[0179] S103B, design the safe flight horizontal distance of the UAV to be ΔR, according to R_max and The range of ΔR is calculated by the rule that R_min is the larger value in L and R_max is the smaller value in b, and ΔR is set to 4m.

[0180] S104, establishing a cylindrical anti-collision area with a height of 2ΔH and a radius of ΔR, with the center of gravity of the aircraft as the center. When it is predicted that the anti-collision areas between the UAVs will not overlap, it is determined that there is no collision between the UAVs. Otherwise, it is determined that there is a collision risk between the UAVs.

[0181] S105, obtaining the position and speed of the other aircraft relative to the heading of the own aircraft:

[0182] S105A, obtain the relative position and relative speed of the other machine from the inter-machine link.

[0183] S105B, establish the heading coordinate system of the aircraft, with the center of gravity of the aircraft as the coordinate origin, the current speed direction of the aircraft as the x-axis, the vertical horizontal ground upward as the z-axis, and the y-axis determined by the left-hand rule.

[0184] S105C, transform the relative position and relative speed of the other aircraft into the heading coordinate system of the own aircraft through coordinate transformation, and obtain the forward position P of the other aircraft relative to the own aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z .

[0185] S106, local speed prediction:

[0186] S106A, it is known that the data transmission cycle between machines is 0.1s, and Δt is the calculation cycle of the local machine is 0.01s. Therefore, the local machine tilt angle of 5 beats before the calculation time is obtained, and the average of the 5 beats is obtained.

[0187] S106B, obtain the forward speed, lateral speed, and vertical speed of the five beats before the calculation time, and average them for the five beats to obtain

[0188] S106C, calculate the turning angle rate dψ0 of the other aircraft at the predicted time t' as follows:

[0189]

[0190] Where g is the acceleration due to gravity.

[0191] S106D, calculate the forward speed V of the aircraft at the predicted time t' according to the following formula 0x _t', lateral speed V 0y _t' are

[0192]

[0193] S107, prediction of the speed of other aircraft relative to this aircraft:

[0194] S107A, take P 5 beats before the calculation time x , P y , P z 、V x 、V y 、V z , and average them by n times to get

[0195] S107B, obtain the tilt angle of the other machine 5 beats before the calculation time through the inter-machine link, and average the 5 beats to obtain

[0196] S107C, obtain the local tempo of the 5 beats before the calculation time, and average the 5 beats to obtain

[0197] S107D, calculate the turning angle rate of the aircraft at the predicted time t' as follows

[0198]

[0199] S107E, calculate the forward speed V of the other aircraft relative to the own aircraft at the predicted time t' according to the following formula x _t', lateral speed V y_t' are

[0200]

[0201] S108. Prediction of other aircraft's relative position to this aircraft:

[0202] S108A, calculate the average speed of the other machine relative to the machine in three axes at the predicted time t'

[0203]

[0204]

[0205] S108B, calculate the position S_t of the other machine relative to the machine at the predicted time t' as follows:

[0206]

[0207] S109, collision prediction and determination:

[0208] S109A, in the time range [0t max ] to find the predicted time t' of the other machine with the closest distance to the machine CAP At this time, the horizontal distance S_Hor and the height difference S_Ver of the other aircraft relative to the local aircraft are respectively

[0209]

[0210] Among them, t max The upper limit of the collision prediction time is set to 1s.

[0211] S109B, before the simulation time 325.76s, S_Hor<2ΔR and S_Ver<2ΔH are not satisfied, it is determined that there is no risk of collision between the other aircraft and the own aircraft, and within the simulation time 325.76s to 335.72s, S_Hor<2ΔR and S_Ver<2ΔH are satisfied, it is determined that after t' CAP There will be collisions between time drones.

Claims

1. A method for predicting collisions between drones in formation flight, characterized in that: include: S10, judging whether to perform a collision prediction of the drone according to the pre-set UAV startup collision avoidance prediction conditions; S20, calculating the safe flight altitude 2ΔH; S30, calculating the safe flight horizontal distance ΔR; S40, establishing a cylindrical anti-collision area with the center of gravity of the aircraft as the center, a height of 2ΔH being the safe flight height, and a radius of ΔR being the safe flight horizontal distance. When it is predicted that the anti-collision areas between the UAVs will not overlap, it is determined that there is no collision between the UAVs. Otherwise, it is determined that there is a collision risk between the UAVs. S50, obtaining the forward position P of the other aircraft relative to the heading of the aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z ; S60, predict the forward speed V of the aircraft 0x _t', lateral speed V 0y _t'; S70, based on the forward position P of the other aircraft relative to the heading of the aircraft x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z , predict the forward speed V of the other aircraft relative to the own aircraft x _t', lateral speed V y _t'; S80, according to Predict the forward speed V of the other aircraft relative to the own aircraft at time t' x _t'River lateral speed V y _t', predict the relative position of the other aircraft to this aircraft S_t'; S90, predict and determine the collision based on the relative position of the other aircraft to the aircraft itself, St', and the cylindrical anti-collision area.

2. The method for predicting collision between machines according to claim 1, characterized in that: S10 includes: S101, obtaining the status of the aircraft's positioning system, the status of the inter-aircraft link, and the flight phase; S102: When one of the following conditions is met, the collision prediction of the local computer is not performed; otherwise, the collision prediction of the local computer is performed: 1) The machine's positioning system status is faulty; 2) The link status between the local machines is faulty; 3) The aircraft is in the automatic flight stage in the air.

3. The method for predicting collision between machines according to claim 1, characterized in that: The S20 includes: S201. Obtain the absolute value H_error of the steady-state error of the altitude control of the UAV, the fuselage length L, and the maximum climbing track angle γ from the UAV performance library. max , obtain the longitudinal separation distance Formation_H of the formation units from the formation performance library; S202, based on the absolute value H_error, the fuselage length L, and the maximum climb track angle γ max The vertical separation distance Formation_H of the formation unit is used to calculate the safe flight altitude 2ΔH, where the value range of ΔH is [H_min,H_max]. H_min=sin(γ max )·L+H_error.

4. The method for predicting collision between machines according to claim 1, characterized in that: S30 includes: S301, obtaining the wingspan length b of the drone from the drone performance library, and obtaining the forward separation distance Formation_X and the lateral separation distance Formation_Y of the formation units from the formation performance library; S302, according to the wingspan length b of the UAV, the forward separation distance Formation_X of the formation unit and the lateral separation distance Formation_Y of the formation unit, the safe flight horizontal distance of the UAV is calculated as ΔR, and the value range of ΔR is (R_min, R_max], where, R_max is and The large value in R_min is the smaller value of L and b.

5. The method for predicting collision between machines according to claim 1, characterized in that: S50 includes: S501, obtaining the relative position and relative speed of the other machine from the inter-machine link; S502, establish the heading coordinate system of the aircraft, with the center of gravity of the aircraft as the coordinate origin, the current speed direction of the aircraft as the x-axis, the vertical horizontal ground upward as the z-axis, and the y-axis determined by the left-hand rule; S503, the relative position and relative speed of the other aircraft are transformed into the heading coordinate system of the own aircraft through coordinate transformation, and the forward position P of the other aircraft relative to the own aircraft is obtained. x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z .

6. The method for predicting collision between machines according to claim 1, characterized in that: S60 includes: S601, obtain the tilt angle of the aircraft n times before the calculation time, and average the tilt angle of the aircraft n times to obtain Among them, the value range of n is [1, ΔT / Δt], ΔT is the data transmission period between machines, and Δt is the local calculation period; obtain the local speed n beats before the calculation time, and average it n beats to get S602: Obtain the forward velocity, lateral velocity, and vertical velocity n times before the calculation time, and average them n times to obtain S603, according to and The turning angle rate dψ0 of the other aircraft at the predicted time t' is calculated as follows: Where g is the acceleration due to gravity; S604, according to the turning angle rate dψ0 and Calculate the forward speed V of the aircraft at the predicted time t' as follows: 0x _t', lateral speed V 0y _t' are 7. The method for predicting collision between machines according to claim 1, characterized in that: S70 includes: S701, obtain the forward position P of the other aircraft relative to the heading of the aircraft n times before the calculation time x , lateral position P y , vertical position P z , forward speed V x , lateral speed V y , vertical speed V z , and average them by n times to get S702: Obtain the tilt angle of the other machine n times before the calculation time through the inter-machine link, and average the tilt angle of the other machine n times before the calculation time. S703, obtain the local speed n beats before the calculation time, and average it n beats to obtain S704, according to and The turn rate of the aircraft at the predicted time t' is calculated as follows: S705, according to and the turning angle rate dψ0, the forward speed V of the other aircraft relative to the own aircraft at the predicted time t' is calculated as follows: x _t', lateral speed V y _t' are 8. The method for predicting collision between machines according to claim 1, characterized in that: S80 includes: S801, calculate the average speed of the other machine relative to the machine in three axes at the predicted time t' S802, calculate the position S_t' of the other machine relative to the machine at the predicted time t' as follows:

9. The method for predicting collision between machines according to claim 1, characterized in that: S90 includes: S901, in the time range [0t max ] to find the predicted time t' of the other machine with the closest distance to the machine CAP At this time, the horizontal distance S_Hor and the height difference S_Ver of the other aircraft relative to the local aircraft are respectively Among them, t max The upper limit of the collision prediction time is set; S902, if S_Hor<2ΔR and S_Ver<2ΔH, then determine that the other machine and the local machine will be at t' CAP If the collision occurs after the predicted time, otherwise, it is determined that there is no risk of collision between the other aircraft and this aircraft within the predicted time range.

10. A device for predicting collisions between drones in formation flight, characterized in that: The device is used to implement the method for predicting collisions between drones in formation flight of drones as described in claim 1.

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