CN115542933A - Optimization method of full-duplex fixed-wing unmanned aerial vehicle relay system under circular track - Google Patents
Optimization method of full-duplex fixed-wing unmanned aerial vehicle relay system under circular track Download PDFInfo
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Abstract
The invention discloses an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system under a circular track, which is characterized in that the optimization method utilizes position information of a source node and a destination node, carries out optimization adjustment on the flight radius, the flight speed and the flight time of an unmanned aerial vehicle according to the size of data volume which needs to be sent to the destination node by the source node, and minimizes the flight energy consumption of the unmanned aerial vehicle under the conditions of meeting the flight speed limit and the horizontal turning inclination angle limit of the unmanned aerial vehicle and meeting the data volume sending requirement of the system. Simulation experiments show that the optimization method has advantages in energy consumption.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system under a circular track.
Background
In recent years, unmanned aerial vehicle cooperative communication technology has become a hot spot of research in the field of wireless communication. Compared with the traditional ground communication, the unmanned aerial vehicle cooperative communication is easy to realize distribution as required, so that higher communication efficiency is achieved; the unmanned aerial vehicle has high mobility, so that the unmanned aerial vehicle is more flexible and rapid to deploy; unmanned aerial vehicle is mostly the line of sight link with the channel link of ground terminal, can provide better channel environment. Therefore, the unmanned aerial vehicle will play an extremely important role in the future wireless communication field, and its application mainly includes: (1) as a temporary base station; (2) as a mobile relay; and (3) the system is used for the Internet of things.
At present, a great deal of literature researches optimization problems of the capacity and the spectrum efficiency of a relay communication system when an unmanned aerial vehicle is used as a mobile relay. Indeed, drones have limited onboard energy, and energy efficiency issues are considered as key issues for drone communication. At present, for unmanned aerial vehicle relay communication, decoding forwarding relay communication form is mostly considered in research, and the research on the adoption of amplification forwarding relay by an unmanned aerial vehicle is less, especially amplification forwarding unmanned aerial vehicle relay communication in a full-duplex mode is not considered yet, and the research is worth. On the other hand, the problem that the turning radius of the fixed-wing drone is related to the flying speed and the horizontal inclination angle of the drone under a circular track is generally ignored in the past and needs further research.
Disclosure of Invention
In order to solve the defects and shortcomings of the prior art, the invention aims to provide an optimization method of a full-duplex fixed-wing unmanned aerial vehicle relay system under a circular track.
The optimization method is realized in such a way that the optimization method of the full-duplex fixed-wing unmanned aerial vehicle relay system under the circular track is characterized in that the optimization method utilizes the position information of a source node and a destination node, optimizes and adjusts the flight radius, the flight speed and the flight time of the unmanned aerial vehicle according to the data volume which needs to be sent to the destination node by the source node, and minimizes the flight energy consumption of the unmanned aerial vehicle under the conditions of meeting the flight speed limit and the horizontal turning inclination angle limit of the unmanned aerial vehicle and meeting the data volume sending requirement of the system.
Preferably, the optimal adjustment formula of the flight radius is as follows:
where Q is the amount of data that the source node S has to send to the destination node D, β represents the channel gain reference value at 1m distance, P S Is the transmit power of S, P R Is the transmission power of R, H is the flight height of the UAV relay R, R is the circular flight path radius of the UAV relay R, L is the distance between S and D, and σ is 2 Is the variance of white Gaussian noise at the R and D nodes, g represents the acceleration of gravity, V min Is the minimum flying speed of the unmanned aerial vehicle, e is a natural constant, c 1 ＝ηC D0 B/2、c 2 ＝2W 2 /[(πe 0 A R )ηB]Eta represents air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is the span efficiency, W represents the overall weight of the drone, A R Representing the aspect ratio of the unmanned wing;
the formula is solved by a golden section one-dimensional search algorithm.
Preferably, the optimal adjustment formula of the flying speed is as follows:
wherein v is the flight speed of the UAV relay R, R is the circular flight path radius of the UAV relay R, g represents the gravitational acceleration, c 1 ＝ηC D0 B/2、c 2 ＝2W 2 /[(πe 0 A R )ηB]Eta represents the air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is the span efficiency, W represents the overall weight of the drone, A R Representing the aspect ratio of the unmanned aerial vehicle wing.
Preferably, the optimal adjustment formula of the flight time is as follows:
wherein Q is the data volume that the source node S needs to send to the destination node D, T is the time for completing the Q data volume forwarding, beta represents the channel gain reference value under the condition of 1m distance, P S Is the transmit power of S, P R Is the transmission power of R, H is the flight height of the UAV relay R, R is the circular flight path radius of the UAV relay R, L is the distance between S and D, and σ is 2 Is the variance of white gaussian noise at the R and D nodes, and e is a natural constant.
Preferably, the optimization method comprises the following steps:
s1, solving an optimization adjustment formula of the flight radius by using a one-dimensional search algorithm to obtain the optimal flight radius r of the unmanned aerial vehicle * ；
S2, mixing r * Respectively substituting the optimal adjustment formula of the flying speed and the optimal adjustment formula of the flying time to obtain the optimal flying speed v of the unmanned aerial vehicle * And the optimal flight time T of the unmanned plane * ；；
S3, optimizing and adjusting the optimal flight speed v of the unmanned aerial vehicle * With minimum flying speed V of unmanned aerial vehicle min And a maximum flying speed V max Comparing; wherein, if V min ≤v * ≤V max Jumping to the following step S7;
s4, if v * ＜V min Then modify the optimal flight speed, let v * ＝V min Then, jumping to the following step S6;
s5, if v * ＞V max And then, the optimum flying speed is modified,let v * ＝V max ；
S6, mixing v * Substituting the v into the following formula to obtain the modified optimal flight radius r * ：
The modified optimal flight radius r * Substituting the r into the optimal adjustment formula of the flight time to obtain the modified optimal flight time T * ；
S7, outputting the optimal flight speed v * Optimum flight radius r * And an optimum time of flight T * 。
The invention overcomes the defects of the prior art and provides an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system under a circular track.
For a full-duplex fixed wing unmanned aerial vehicle relay communication system under a circular track, a source node S on the ground needs to send Q data volume to a destination node D, the distance between the S and the D is assumed to be L, and a direct link does not exist due to the fact that the S and the D are far away from each other, the data needs to be forwarded by means of a fixed wing unmanned aerial vehicle relay R flying at the height of H, the unmanned aerial vehicle relay R works in a full-duplex mode (receiving and transmitting signals are carried out at the same frequency band at the same time), and an amplification-and-Forward (AF) relay protocol is adopted; the relay R of the unmanned aerial vehicle takes the midpoint of the connecting line of the source node S and the destination node D as the circle center, takes R as the radius and takes uniform speed v to carry out circular flight motion, wherein the flight radius R not only needs to meet the horizontal turning inclination angle limitation of the unmanned aerial vehicle, but also needs to meet the requirement of meeting the requirement of the horizontal turning inclination angle limitation of the unmanned aerial vehicle
Assuming that S to R and R to D are both line of Sight (LoS) links, the S to R channel can be written as:
the R to D channels can be written as:
where alpha is the fading factor of the wireless channel,
being the distance from the source node S to the relay R,
for the distance from the relay R to the destination node D, t represents time, β represents a channel gain reference value in the case of a distance of 1m, and θ represents a central angle corresponding to the flight arc length of the relay R of the UAV, where it is assumed that the position of the source node S is (0, 0), the position of the destination node D is (L, 0), and the starting point of the UAV flight is (L, 0)
It should be noted that: the value of the wireless channel fading factor α is usually 2 to 4, and since the channel between the unmanned aerial vehicle and the ground node is formed by the LoS link, α is 2, and at this time, the channel from the node S to the relay R can be written as:
the channel relayed R to node D is:
because unmanned aerial vehicle relay R works in a full-duplex mode, at the moment, a wireless signal transmitted by an unmanned aerial vehicle transmitting antenna is received by an unmanned aerial vehicle receiving antenna, so that the unmanned aerial vehicle needs to adopt a Loop Interference Cancellation (LIC) technology to eliminate Loop Interference generated in the full-duplex mode, and according to a LoS channel and a Loop Interference hypothesis, a signal expression received by the unmanned aerial vehicle relay R can be given:
wherein P is S Is the transmit power of S; x is the number of S A transmit signal of S (assuming power of 1); p R Is the transmit power of R; x is the number of R A transmit signal of R (assuming power of 1); h is LI Is residual loop interference after LIC; z is a radical of formula R Is white Gaussian noise received by R (assuming mean 0 and variance σ 2 ) The unmanned plane will receive signal y R Multiplying by the amplification factor p becomes the transmitted signal, i.e. x R ＝ρy R Here, the
Suppose that the drone relays R to receive signal y R Without any delay, the signal received by the node D is:
wherein z is D Is D white Gaussian noise received (assuming mean 0 and variance σ) 2 )；
Will be provided with
Substituted into formula (4), and can be obtained by mathematical operation
The received signal-to-noise ratio of the D node can be obtained from equation (5), which can be specifically written as:
wherein
Thus, the amount of data that can be received by the destination node at time t is:
according to the above analysis, the problem of optimizing the energy consumption of the unmanned aerial vehicle to the minimum can be written as
s.t.Q-Q D (T)≤0 (8b)
V min ≤v≤V max (8c)
Here, T is the time to complete the Q data volume forwarding,
the power consumption of the fixed-wing unmanned aerial vehicle flying in a circular track with constant speed v and radius r, wherein g represents the gravity acceleration, and c represents the power consumption 1 ＝ηC D0 B/2、c 2 ＝2W 2 /[(πe 0 A R )ηB]Eta represents air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is span efficiency, W means noneWeight of the entire human-machine body, A R Aspect ratio, V, of the unmanned wing max And V min The maximum flight speed and the minimum flight speed of the unmanned aerial vehicle are respectively, the constraint condition formula (8D) shows that the horizontal turning inclination angle of the unmanned aerial vehicle is less than or equal to 45 degrees, and the constraint condition formula (8 e) shows that the projection of the flight path of the unmanned aerial vehicle on the ground is positioned within the connection line between S and D;
it should be noted that: the flying speed v and the flying radius r of the fixed-wing unmanned aerial vehicle under the circular track are satisfied
Wherein phi is the horizontal turning inclination angle of the unmanned aerial vehicle, and the horizontal turning inclination angle satisfies 0 < phi < 45 degrees, therefore, the requirement of the fixed wing unmanned aerial vehicle when flying in a circular track is satisfied
Otherwise, the unmanned aerial vehicle cannot make horizontal turning;
to understand the optimization problem (8), i.e., the optimization problem composed of the formula (8 a), the formula (8 b), the formula (8 c), the formula (8 d), and the formula (8 e), the constraint formula (8 b) is simplified; for this purpose, log is first given 2 (1+γ D ) The lower bound of (c) can be specifically written as:
then according to the inequality
And formula (9), log can be found further 2 (1+γ D ) Can be written specifically as:
because of
Therefore, it is not only easy to use
If it is true, log is obtained according to the formula (10) 2 (1+γ D ) Specifically, can be written as;
from equations (7) and (11), the lower bound of the amount of data that can be received by the destination node D at time t can be obtained
Wherein
Q obtained by the following formula (12) D Lower boundary of (t)
To replace Q D (t), then the drone energy consumption minimum optimization problem, i.e., problem (8) may translate into
V min ≤v≤V max (14c)
It should be noted that: when the lower bound of the data which can be received by the destination node D is greater than or equal to Q, the data which can be actually received by the destination node D is definitely greater than or equal to Q;
to solve the problem (14), i.e., the optimization problem composed of the equations (14 a), (14 b), (14 c) and (14 d), first, ignoring the constraints of the equations (14 b), (14 c) and (14 d), we obtain the partial derivative of v for the equation (14 a) and make the partial derivative be 0, and we can obtain:
observing equation (15), it is found that v is an increasing function of r, that is, r is increased, and v is also increased, and vice versa; therefore, when v and r satisfy expression (15), and let r go to infinity, v goes to
That is, when v and r satisfy the formula (15), the maximum value of v is
Thus, according to the formula (15),
further, when v and r satisfy the formula (15),
it is certainly true that, when v and r satisfy the expression (15), the constraint condition expression (14 d) is rewritable to
Substituting equation (16) into (14 a), the objective function of the optimization problem (14) can be written as:
in addition, due to
Is an increasing function of T and a decreasing function of r, when the problem (14) has an optimal solution, the constraint conditional expression (14 b) will take equal sign, because if the constraint conditional expression (14 b) takes a smaller sign, the T can be decreased or r can be increased to make the problem have equal sign
Decreasing, and thus lowering, the value of the objective function (14 a), so when the problem (14) has an optimal solution, the constraint equation (14 b) will take the equal sign;
according to equation (13), when constraint equation (14 b) is to take an equal sign:
from the above analysis, the question (14) can be rewritten as:
the optimization problem (19), namely the optimization problem composed of the formula (19 a) and the formula (19 b), can obtain the optimal radius of the unmanned aerial vehicle in flight through one-dimensional search, and then the solution of the problem (19) is substituted into the formula (15) and the formula (18) respectively to obtain the optimal flight speed and flight time of the unmanned aerial vehicle; next, whether the obtained optimal flying speed of the unmanned aerial vehicle can be greater than or equal to V needs to be checked min And is not more than V max If yes, outputting the optimal solution, and if less than V min The optimal flying speed of the unmanned aerial vehicle is modified to be V min If greater than V max Then, the optimal flying speed of the unmanned aerial vehicle is modified into V max Then, substituting the modified optimal flying speed of the unmanned aerial vehicle into a formula (16) to obtain the modified optimal flying radius of the unmanned aerial vehicle, and finally substituting the obtained modified optimal flying radius of the unmanned aerial vehicle into a formula (18) to obtain the modified optimal flying time;
compared with the defects and shortcomings of the prior art, the invention has the following beneficial effects: according to the method, the flight speed, the flight radius and the flight time of the unmanned aerial vehicle are optimally adjusted by utilizing the position information of the source node and the destination node according to the maximum and minimum flight speed limit of the unmanned aerial vehicle, the horizontal turning inclination angle limit of the unmanned aerial vehicle and the data volume which needs to be sent to the destination node by the source node. The method can realize the minimization of the flight energy consumption of the unmanned aerial vehicle under the condition of meeting the requirement of the system for sending data volume; simulation experiments show that the optimization method has advantages in energy consumption.
Drawings
FIG. 1 is a schematic view of a coordinate system of the unmanned aerial vehicle of the present invention;
FIG. 2 is a comparison of energy consumption using an optimization method with minimum and maximum flight speeds of the UAV at different Q values;
FIG. 3 shows the actual data volume received by the destination node at the minimum and maximum flight speeds of the unmanned aerial vehicle and the optimization method used under different Q values;
FIG. 4 is a graph of flight times at minimum and maximum flight speeds of the UAV using the optimization method at different Q values;
FIG. 5 is a comparison of energy consumption using an optimization method with minimum and maximum flight speeds of the UAV under different loop disturbances;
fig. 6 shows the actual data volume received by the destination node under different loop interferences and using the optimization method and the minimum and maximum flight speeds of the drone.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the invention discloses an optimization method of a full-duplex fixed wing unmanned aerial vehicle relay system under a circular track, which is characterized in that the optimization method utilizes position information of a source node and a destination node, carries out optimization adjustment on the flight radius, the flight speed and the flight time of an unmanned aerial vehicle according to the size of data volume which needs to be sent to the destination node by the source node, and minimizes the flight energy consumption of the unmanned aerial vehicle under the conditions of meeting the flight speed limit and the horizontal turning inclination angle limit of the unmanned aerial vehicle and meeting the requirement of data volume sent by the system.
As shown in fig. 1, the unmanned aerial vehicle relay R always flies at a height H, the projection of the flight trajectory on the ground plane is circular, the circle uses the midpoint of the connecting line between the source node S and the destination node as the center of circle, R is the radius, the projection of the starting point of the unmanned aerial vehicle on the ground plane is that the midpoint of the connecting line between the source node S and the destination node deviates from the direction of the node S, and the linear velocity of the flight of the unmanned aerial vehicle relay R is v. And the unmanned aerial vehicle R forwards a message to the destination node while receiving the S sending signal. The unmanned aerial vehicle receives signals and forwards messages at the same time on the same frequency band, namely, the unmanned aerial vehicle works in a full duplex mode, and an AF protocol is adopted for relay forwarding.
The optimization method comprises the following specific steps:
s1, solving a formula (19) by utilizing a golden cutting one-dimensional search algorithm to obtain the optimal flight radius r of the unmanned aerial vehicle *
In the step S1, solving the problem (19) by using a one-dimensional search algorithm to obtain the optimal flight radius r of the unmanned aerial vehicle * ；
S2, mixing r * Respectively substituting into formula (15) and formula (18) to obtain the optimal flying speed v of the unmanned aerial vehicle * And the optimal flight time T of the unmanned plane * ；
In step S2, r is added * Obtaining the optimal flying speed v of the unmanned plane by respectively substituting r into formula (15) and formula (18) * And the optimal flight time T of the unmanned plane * ；；
S3, optimizing and adjusting optimal flying speed v of unmanned aerial vehicle * With minimum flying speed V of unmanned aerial vehicle min And a maximum flying speed V max Carrying out comparison; wherein, if V min ≤v * ≤V max It jumps to the following step S7
S4, if v * ＜V min Then modify the optimal flight speed, let v * ＝V min Then, jumping to the following step S6;
s5, if v * ＞V max Then modify the optimal flight speed, let v * ＝V max ；
S6, mixing v * Substituting into formula (16) as v to obtain the modified optimal flight radius r * ：
The modified optimal flight radius r * Substituting equation (18) as r to obtain the modified optimal time of flight T * ：
S7, outputting the optimal flight speed v * Optimum flight radius r * And an optimal time of flight T * 。
For the aboveThe optimization method carries out simulation experiments, and compares the system power consumption with the system power consumption of the unmanned aerial vehicle flying at the minimum speed and the maximum speed, and the experimental environment is the Matlab environment. Assuming that the distance L =5000m between the source node S and the destination node, the minimum and maximum speeds of flight of the unmanned aerial vehicle are V respectively min ＝5m/s、V max =50m/s, the signal transmission power of the unmanned aerial vehicle flying at a fixed height H =200m, S and R nodes is P S ＝P R = -20dBm, variance σ of white Gaussian noise in the environment 2 = 110dBm, unit distance channel gain β =1,c 1 ＝9.26×10 -4 ，c 2 ＝2250。
Fig. 2, fig. 3 and fig. 4 show the energy consumption comparison, the actual data receiving amount of the destination node and the flight time of the unmanned aerial vehicle at the minimum and maximum flight speeds of the unmanned aerial vehicle by using the optimization method, respectively. Here, assume loop interference | h LI | 2 ＝10 -6 (ii) a "minimum speed flight" and "maximum speed flight" mean that the drone flies at minimum and maximum flight speeds, respectively, but the flight radius and flight time are both optimized, and the "proposed algorithm" is to use the proposed optimization method, that is, to use the combined adjustment algorithm of the flight speed, flight radius and flight time of the drone.
Fig. 2 shows the energy consumption comparison between the optimization method and the minimum and maximum flight speeds of the drone at different Q values. As can be seen from fig. 2, the proposed optimization algorithm provides a significant power saving compared to "minimum speed flight" and "maximum speed flight". Fig. 3 shows the actual data volume received by the destination node using the optimization method and the minimum and maximum flight speeds of the drone under different Q values. Fig. 3 shows that, in the three methods, the destination node can receive data with a quantity larger than the set Q value, which illustrates the correctness of the proposed optimization method. Fig. 4 shows the flight times at the minimum and maximum flight speeds of the drone and the optimization method used for different Q values. As can be seen from fig. 4, the flight times of the three are close to each other, and the flight time of the proposed algorithm is located in the middle, the flight time of the "maximum speed flight" is slightly longer, and the flight time of the "minimum speed flight" is slightly shorter. It should be noted that, under the parameters adopted in fig. 2, fig. 3, and fig. 4, the flight radii of the proposed optimization algorithm, "minimum speed flight" and "maximum speed flight" are respectively: 241.8m, 27.57m and 371.4m; the flying speeds are respectively: 27.42m/s, 5m/s and 50m/s.
Fig. 5 and fig. 6 show the energy consumption comparison and the actual data receiving amount of the destination node under different loop interferences by using the optimization method and the minimum and maximum flight speeds of the drone, respectively. Here, it is assumed that the data amount Q =100. As can be seen from fig. 5, the proposed optimization algorithm provides a significant power saving compared to "minimum speed flight" and "maximum speed flight". Fig. 6 shows the actual data volume received by the destination node under different loop interferences and using the optimization method and the minimum and maximum flight speeds of the drone. Fig. 6 shows that, under the three methods, the amount of data that can be received by the destination node is larger than the set Q value, further explaining the correctness of the proposed optimization method. It should be noted that, under the parameters adopted in fig. 5 and fig. 6, the flight radii of the proposed optimization algorithm, "minimum speed flight" and "maximum speed flight" are respectively: 241.8m, 27.57m and 371.4m; the flying speeds are respectively: 27.42m/s, 5m/s and 50m/s; the flight times are respectively: 213.7s, 187.1s and 231.7s.
The above description is intended to be illustrative of the preferred embodiment of the present invention and should not be taken as limiting the invention, but rather, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (5)
1. The optimization method is characterized in that the optimization method utilizes position information of a source node and a destination node, carries out optimization adjustment on the flight radius, the flight speed and the flight time of the unmanned aerial vehicle according to the size of data volume which needs to be sent to the destination node by the source node, and minimizes the flight energy consumption of the unmanned aerial vehicle under the conditions of meeting the flight speed limit and the horizontal turning inclination angle limit of the unmanned aerial vehicle and meeting the requirement of the data volume sent by the system.
2. The optimization method according to claim 1, wherein the optimization adjustment formula of the flight radius is:
where Q is the amount of data that the source node S has to send to the destination node D, β represents the channel gain reference value at 1m distance, P S Is the transmit power of S, P R Is the transmission power of R, H is the flight height of the UAV relay R, R is the circular flight path radius of the UAV relay R, L is the distance between S and D, and σ is 2 Is the variance of white Gaussian noise at the R and D nodes, g represents the acceleration of gravity, V min Is the minimum flying speed of the unmanned aerial vehicle, e is a natural constant, c 1 ＝ηC D0 B/2、c 2 ＝2W 2 /[(πe 0 A R )ηB]Eta represents air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is the wingspan efficiency, W represents the overall weight of the drone, A R Represents the aspect ratio of the unmanned wing;
the formula is solved by a golden section one-dimensional search algorithm.
3. The optimization method according to claim 1, wherein the optimization adjustment formula of the flying speed is as follows:
wherein v is the flight speed of the UAV relay R, R is the circular flight path radius of the UAV relay R, g represents the gravitational acceleration, c 1 ＝ηC D0 B/2、c 2 ＝2W 2 /[(πe 0 A R )ηB]Eta represents air density, C D0 Denotes the zero lift drag coefficient, B denotes the wing area, e 0 Is the wingspan efficiency, W represents the overall weight of the drone, A R Representing the aspect ratio of the unmanned wing.
4. The optimization method according to claim 1, wherein the optimization adjustment formula of the flight time is:
wherein Q is the data volume that the source node S needs to send to the destination node D, T is the time for completing the Q data volume forwarding, beta represents the channel gain reference value under the condition of 1m distance, P S Is the transmit power of S, P R Is the transmission power of R, H is the flight height of the UAV relay R, R is the circular flight path radius of the UAV relay R, L is the distance between S and D, and σ is 2 Is the variance of white gaussian noise at the R and D nodes, and e is a natural constant.
5. An optimization method according to any one of claims 2 to 4, characterized in that it comprises the following steps:
s1, solving an optimization adjustment formula of the flight radius by using a one-dimensional search algorithm to obtain the optimal flight radius r of the unmanned aerial vehicle * ；
S2, mixing r * Respectively substituting the optimal adjustment formula of the flying speed and the optimal adjustment formula of the flying time to obtain the optimal flying speed v of the unmanned aerial vehicle * And the optimal flight time T of the unmanned plane * ；
S3, optimizing and adjusting optimal flying speed v of unmanned aerial vehicle * With minimum flying speed V of unmanned aerial vehicle min And a maximum flying speed V max Comparing; wherein, if V min ≤v * ≤V max Jumping to the following step S7;
s4, if v * ＜V min Then modify the optimal flight speed, let v * ＝V min Then, howeverThen jumping to the following step S6;
s5, if v * ＞V max Then modify the optimal flight speed, let v * ＝V max ；
S6, mixing v * Substituting the v into the following formula to obtain the modified optimal flight radius r * ：
The modified optimal flight radius r * Substituting r into the optimal adjustment formula of the flight time to obtain the modified optimal flight time T * ；
S7, outputting the optimal flight speed v * Optimum flight radius r * And an optimum time of flight T * 。
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