Communication power and flight power distribution method suitable for return flight of unmanned aerial vehicle

Abstract

The invention provides a communication power and flight power distribution method suitable for return flight of an unmanned aerial vehicle. The method comprises the following steps: dividing the whole process of returning the unmanned aerial vehicle from a return flight point to a landing point into a plurality of continuous time periods; establishing a game model taking the output power of the unmanned aerial vehicle as a leader and taking the communication power of the unmanned aerial vehicle and the flight power of the unmanned aerial vehicle as followers, and maximizing a utility function representing the benefits of the leader and maximizing a utility function representing the benefits of the followers through game actions in the kth time period, obtaining the optimal unit power price in the kth time period; according to the optimal unit power pricing in the kth time period, the optimal communication power and the optimal flight power in the kth time period are determined, and the optimal flight distance of the unmanned aerial vehicle in the kth time period is determined, so that the position of the unmanned aerial vehicle at the end of the kth time period is obtained; k is made to be equal to k + 1, and the steps are executed repeatedly till the unmanned aerial vehicle lands to the E point.

Description

Technical Field

[0001] The present invention belongs to the technical field of UAV communication and attitude adjustment in wireless communication, and specifically relates to a method for allocating communication power and flight power suitable for UAV return flight. Background Art

[0002] The allocation of UAV communication power and flight power is an important part of the development of UAV technology. When a UAV executes a mission, it is necessary to ensure a stable communication link and reasonable flight energy consumption. Communication power affects the data transmission distance and quality between the UAV and the ground station or other UAVs, while flight power is directly related to the endurance and flight efficiency of the UAV.

[0003] With the expansion of UAV application scenarios, higher requirements are put forward for the allocation of UAV communication power and flight power. Optimizing the power allocation strategy can not only improve the reliability and efficiency of data transmission, but also extend the flight time of the UAV and reduce energy consumption. Therefore, studying the reasonable allocation of UAV communication power and flight power is of great significance for improving the overall performance of UAVs and broadening the application fields. Summary of the Invention

[0004] Object of the Invention: To solve the problems of how to effectively allocate communication power and flight power under the premise of limited output power of the UAV and how to reasonably plan the return route of the UAV, the present invention proposes a method for allocating communication power and flight power suitable for UAV return flight.

[0005] Technical Solution: A method for allocating communication power and flight power suitable for UAV return flight includes the following steps: Step 1: Assume that the return point of the UAV is point O and the landing point is at point E. Take point O as the origin (0, 0, 0) of the spatial Cartesian coordinate system, and the coordinates of point E are ( x E , y E , z E ). Divide the entire process of the UAV returning from point O to point E into multiple consecutive time periods with a duration of Δt. Assume that within this time period, the channel gain from the UAV to point E remains unchanged; Step 2: Establish a game model with the output power of the UAV as the leader and the communication power and flight power of the UAV as followers with a competitive relationship. In the k-th time period, maximize the utility function representing the leader's interests and the utility function representing the followers' interests through game actions to obtain the optimal unit power pricing in the k-th time period; determine the optimal communication power and optimal flight power in the k-th time period according to the optimal unit power pricing in the k-th time period; Step 3: Determine the optimal flight distance of the UAV in the k-th time period based on the optimal flight power in the k-th time period and the position where the UAV is located at the beginning of the k-th time period, so as to obtain the position where the UAV is located at the end of the k-th time period; Step 4: Let k = k + 1, use the position where the UAV is located at the end of the k-th time period as the position where the UAV is located at the beginning of the (k + 1)-th time period, and repeat Steps 2 and 3 until the UAV lands at point E.

[0006] Furthermore, the utility function that maximizes the interests of the leader is expressed as: ; s.t. ; where s.t. represents constraints, represents the flight power of the UAV in the k-th time period, represents the communication power of the UAV in the k-th time period, represents the unit power pricing; represents the maximum value of the output power of the UAV, represents determining a unit power pricing to make maximum.

[0007] Furthermore, the utility function that maximizes the interests of the follower is expressed as: For the communication power, the utility function that maximizes the interests of the follower is expressed as: ; In the formula, represents the communication power of the UAV in the k-th time period, is the signal receiver noise, B is the communication bandwidth, represents the channel gain between the position of the UAV in the k-th time period and point E, represents the unit power pricing; For the flight power, the utility function that maximizes the interests of the follower is expressed as: ; s.t. ; In the formula, s.t. represents constraints, W represents the UAV weight, g represents the gravitational acceleration, represents the air density, and n represent the area and number of the blades respectively, It represents the relationship function of the flight power of the UAV with respect to the gravitational acceleration, air density, area and number of propeller blades. L ( k -1) represents the position of the UAV at the end of the (k - 1)-th time period, which is also the position of the UAV at the start of the k-th time period. E represents the coordinates of point E. It represents the flight power of the UAV within the k-th time period. It represents the Euclidean distance.

[0008] Furthermore, based on the optimal flight power within the k-th time period and the position of the UAV at the start of the k-th time period, determine the optimal flight distance of the UAV within the k-th time period, which is expressed as: ; In the formula, W represents the weight of the UAV. g represents the gravitational acceleration. represents the air density. and n represent the area and number of propeller blades respectively. It represents the relationship function of the flight power of the UAV with respect to the gravitational acceleration, air density, area and number of propeller blades. represents the optimal flight power within the k-th time period.

[0009] Furthermore, in step 3, the position of the UAV at the end of the k-th time period is obtained according to the following steps: The position of the UAV at the end of the k-th time period is on the sphere with the position at the start of the k-th time period as the origin and the optimal flight distance of the UAV as the radius. The equation of this sphere is: ; wherein, is the coordinate of any point on the sphere; Select the point where the line connecting the point and point E intersects the sphere as the position of the UAV at the end of the k-th time period .

[0010] Furthermore, when there are no obstacles on the line connecting the point and point E, the above-mentioned selection of the point where the line connecting the point and point E intersects the sphere as the position of the UAV at the end of the k-th time period specifically includes: Since the intersection point is on the line connecting the point and point E, it also satisfies: ; ; ; Among them, t is a variable with a value range of 0 to 1; By combining the above equations, we have: ; Furthermore, the coordinates of the position where the drone is located at the end of the k-th time period are: ; ; .

[0011] Furthermore, when there is an obstacle on the line connecting to point E, the point where the line connecting to point E intersects the sphere is selected as the position where the drone is located at the end of the k-th time period , specifically including: Assume that the coordinate of the obstacle in the vertical direction is , and the equation of the circular plane formed by the horizontal plane it forms and the sphere with the starting position of the k-th time period as the origin and the optimal flight distance of the drone as the radius is: ; Since the point is also on this plane, the tangent equation of the circle passing through the point can be obtained as: ; The straight line equation passing through the point and point E is: ; Since the tangent of the circle passing through the point is perpendicular to the straight line connecting the point and point E, we can obtain: ; Also, since the point is on the circle, we have: ; By combining the above two equations, the coordinates of the point can be obtained as: ; ; ; wherein, the plus or minus sign is determined by point and the coordinates of point E.

[0012] Beneficial effects: Compared with the prior art, the method of the present invention solves the problem of how to effectively allocate communication power and flight power for an unmanned aerial vehicle (UAV) under the premise of limited output power, and calculates the return route of the UAV after obtaining the optimal flight power, which physically conforms to the realistic application scenario and can be effectively applied to engineering practice. Description of the Drawings

[0013] Figure 1 is the flight route planning diagram of the UAV without obstacles; Figure 2 is the flight route planning diagram of the UAV with obstacles; Figure 3 is the flowchart of a method for allocating communication power and flight power applicable to the return of a UAV proposed by the present invention. Specific Embodiments

[0014] The technical solution of the present invention will be further described below in conjunction with the drawings and embodiments.

[0015] As Figure 3 shown, this embodiment proposes a method for allocating communication power and flight power applicable to the return of a UAV, which mainly includes the following steps: Step 1: Assume that the return point of the UAV is point O and the landing point is at point E. Take point O as the origin (0, 0, 0) of the spatial Cartesian coordinate system, and the coordinates of point E are ( x E , y E , z E ). Divide the entire process of the UAV returning from point O to point E into multiple consecutive time periods with a duration of Δt. During each time period, since the UAV runs a short distance, it can be assumed that the channel gain from the UAV to point E remains unchanged during this time period.

[0016] The following introduces a conventional channel gain calculation step. This embodiment can adopt this channel gain calculation step, but is not limited to this channel gain calculation step.

[0017] The path loss of the wireless transmission from the UAV to the return point depends on the distance-based fading and the line-of-sight (LoS) probability-based fading. The LoS occurrence probability of the additional path loss between nodes p and q is given by the following formula:

[0018] wherein, c 0 and d0 depends on environmental variables, which are constants; is the elevation angle of the air-to-ground wireless transmission link, h is the vertical height of the UAV relative to the control remote sensing, is the horizontal distance between nodes p and q.

[0019] Therefore, the channel gain between nodes p and q is defined as: ; wherein, is the known unit channel gain value; and are the probabilities of occurrence of line-of-sight LoS and non-line-of-sight NLoS (Non Line of Sight) of the additional path loss between the known nodes p and q, respectively, and there is ; and represent the additional path losses of the known LoS and NLoS links, respectively, and satisfy ; is the distance between p and q.

[0020] Step 2: Establish a game where the output power of the UAV is the leader, and the communication power and flight power of the UAV are the followers with a competing relationship. In each time period, through game actions, maximize the utility function representing the leader's interests and the utility function representing the followers' interests to obtain the optimal unit power pricing; according to the optimal unit power pricing, determine the optimal communication power and optimal flight power for the current time period.

[0021] Now, a further explanation of Step 2 is given.

[0022] In this embodiment, since the magnitude of the UAV output power is constant and its power can be used for signal transmission and flight, there is a competing relationship between the power components for different purposes, that is, the communication power and flight power of the UAV have a competing relationship.

[0023] The communication power problem is formulated as: Assuming that in the k-th time period, the communication power of the UAV is used to send data to the control remote sensing at point E, so its utility function is expressed as: ; wherein, is the communication power of the UAV in the k-th time period, is the controller receiver noise, B is the communication bandwidth, is the channel gain between the UAV at point O and point E in the k-th time period, is the channel gain from point O to point E. represents the position of the UAV at the beginning of the k-th time period to the distance of point E and there is , represents the Euclidean distance. Then it represents the data transmission rate within the k-th time period, which is its revenue. is the unit power pricing. Then it represents the cost function that the UAV pays for the communication power and pays.

[0024] As the communication power increases, the data transmission rate it obtains also increases, but its cost function will also increase. For the follower in the game model, its goal is to obtain the highest revenue at the lowest cost in the game behavior, that is, to maximize its own utility function. Therefore, for the communication power in the k-th time period, there is: ; The flight power problem is described as: Assuming that within the k-th time period, the flight distance of the UAV is expressed as , then its flight power can be expressed as: ; In the formula, W represents the weight of the UAV. g represents the acceleration due to gravity. represents the air density. and n respectively represent the area and number of the propeller blades. represents the relationship function between the flight power of the UAV and the acceleration due to gravity, air density, area and number of the propeller blades, for example .

[0025] The flight power of the UAV is used for it to fly towards point E. Therefore, the utility function within the k-th time period can be expressed as: ; Among them, represents the distance from the UAV to point E at the end of the k-th time period. The smaller its value, the closer the distance. Therefore, the purpose of the game of the flight power of the UAV is to fly close to point E and achieve a return flight. The game revenue is defined as , then it represents the cost function that the UAV pays for the flight power and pays.

[0026] As flight power increases, it approaches point E, but its cost function also increases. For followers in the game model, their goal is to obtain the highest benefit at the lowest cost, that is, to maximize their own utility function. Therefore, for the flight power in the kth time period, we have: ; st ; Among them, the constraint condition is that within the kth time period, the drone can fly to point E at most.

[0027] Since the output power of the UAV is limited, the optimization problem at the leader level in the game in the kth time period is expressed as: ; st ; in, The maximum output power of the drone. Indicates the determination of the price of one unit of power make maximum.

[0028] The optimization problem of the followers in the above game and the optimization problem of the leader in the game together constitute the Stackelberg game. The final Stackelberg equilibrium can be obtained by the leaders and followers of the game taking game actions according to certain rules. That is, the optimal unit power pricing is obtained by maximizing the utility function representing the interests of the leader and the followers in a competitive relationship. Then, the optimal communication power in this time period is and flight power Can be decided based on.

[0029] In the kth time period, the optimal distance flown by the drone is expressed as: ; According to the initial coordinates of the k+1th time period calculate and , and then the optimal unit power pricing in the k+1th time period is obtained through the proposed game method , optimal communication power and flight power as well as , and then get the final coordinates of the k+1th time period , which is also the initial coordinate of the k+2th time period.

[0030] Step 3: Based on the initial coordinates of the k+1th time period The optimal unit power pricing in the k+1th time period is obtained by the game model , optimal communication power and flight power And the optimal distance the drone flies in the k+1th time period , and then get the final coordinates of the k+1th time period , which is also the initial coordinate of the k+2th time period. In the continuous time period, the above operation is performed to obtain a series of optimal communication power , flight power And the coordinates of the drone's flight nodes until the drone lands at point E, and the algorithm ends. The specific operations include: If the flight power is given , then the position of the UAV at the end of the kth time period is Should be located at the beginning of the kth time period As the origin, the optimal distance the drone flies On a sphere with a radius of , the equation of the sphere is: ; in, are the coordinates of any point on the sphere.

[0031] is the coordinate of point O, Since this embodiment studies the return of the UAV, the point The point where the line connecting point E intersects the sphere is the position of the drone at the end of the kth time period. .

[0032] Therefore, we have: ; Next, the coordinates of the drone at the end of the kth time period are Follow the points Calculation is performed based on whether there are any obstructions on the line connecting point E: 1) When When there is no obstruction on the line connecting point E, and because the intersection exist and point E, so it also satisfies: ; ; ; Here, t is a variable with a value ranging from 0 to 1.

[0033] Combining the above formulas, we have: ; Furthermore, the intersection The coordinates are; ; ; .

[0034] 2) When When there is an obstruction on the line connecting point E: Select the highest plane or point of the occluder The point where the line connecting point E intersects the surface perpendicular to the sphere is ,like Figure 2 shown.

[0035] Assume that the vertical coordinates of the occluder are , the horizontal plane formed by it is the same as the position at the beginning of the kth time period As the origin and the optimal flight distance of the drone The equation of a circular plane formed by a sphere of radius is: ; Because of the point is also on the plane, so we can find the circle passing through the point The tangent equation is: ; past The equation of the line connecting point E is: ; Because of the past The tangent line of the circle The line from point E to point E is perpendicular, so we have: ; Because of the point On the circle, we have: ; Combining the above two equations, we can get The coordinates are: ; ; ; The positive and negative signs are indicated by the dot and the coordinates of point E.

[0036] In a series of consecutive time periods, the above operations are all executed to obtain a series of optimal communication powers, flight powers, and UAV flight node coordinates until the UAV lands at point E and the algorithm ends.

Claims

1. A method for allocating communication power and flight power applicable to the return of an unmanned aerial vehicle, characterized in that: Including the following steps: Step 1: Assume that the return point of the drone is point O and the landing point is at point E. Take point O as the origin (0, 0, 0) of the spatial Cartesian coordinate system, and the coordinates of point E are ( x E , y E , z E ). Divide the entire process of the drone returning from point O to point E into multiple consecutive time periods with a duration of Δt. Assume that within this time period, the channel gain of the drone to point E remains unchanged; Step 2: Establish a game model with the output power of the UAV as the leader and the communication power and flight power of the UAV as followers with a competitive relationship. In the k-th time period, through game actions, maximize the utility function representing the leader's interests and the utility function representing the followers' interests to obtain the optimal unit power pricing in the k-th time period; According to the optimal unit power pricing in the k-th time period, determine the optimal communication power and optimal flight power in the k-th time period; Step 3: According to the optimal flight power in the k-th time period and the position where the UAV is located at the beginning of the k-th time period, determine the optimal flight distance of the UAV in the k-th time period, and thus obtain the position where the UAV is located at the end of the k-th time period; Step 4: Let k = k + 1, take the position where the UAV is located at the end of the k-th time period as the position where the UAV is located at the beginning of the (k + 1)-th time period, and repeat Steps 2 and 3 until the UAV lands at point E.

2. The communication power and flight power allocation method applicable to the return flight of an unmanned aerial vehicle according to claim 1, wherein: The maximization of the utility function representing the leader's interests is expressed as: ； s.t. ; Among them, s.t. represents a constraint, represents the flight power of the UAV in the k-th time period, represents the communication power of the UAV in the k-th time period, represents the unit power pricing; represents the maximum value of the output power of the UAV, represents determining a unit power pricing such that is maximized.

3. A method for allocating communication power and flight power applicable to the return of an unmanned aerial vehicle according to claim 1, characterized in that: The maximization of the utility function representing the followers' interests is expressed as: For the communication power, the maximization of the utility function representing the followers' interests is expressed as: ； wherein, represents the communication power of the UAV in the k-th time period, is the signal receiver noise, B is the communication bandwidth, represents the channel gain between the position of the UAV and point E in the k-th time period, represents the unit power pricing; For the flight power, the maximization of the utility function representing the followers' interests is expressed as: ； s.t. ; In the formula, s.t. represents constraints, W represents the weight of the UAV, g represents the acceleration due to gravity, represents the air density, and n respectively represent the area and number of the propeller blades, represents the relationship function of the flight power of the UAV with the acceleration due to gravity, air density, area and number of the propeller blades, L ( k -1) represents the position of the UAV at the end of the (k - 1)-th time period, which is also the position of the UAV at the start of the k-th time period. E represents the coordinates of point E, represents the flight power of the UAV within the k-th time period, represents the Euclidean distance.

4. A method for allocating communication power and flight power applicable to the return of an unmanned aerial vehicle according to claim 1, characterized in that: The determination of the optimal flight distance of the UAV in the k-th time period according to the optimal flight power in the k-th time period and the position where the UAV is located at the beginning of the k-th time period is expressed as: ； Wherein, W represents the weight of the drone, g represents the acceleration due to gravity, represents the air density, and n respectively represent the area and number of the blades, represents the relationship function of the flight power of the drone with the acceleration due to gravity, air density, area and number of the blades, represents the optimal flight power within the k-th time period.

5. A method for allocating communication power and flight power applicable to the return flight of a drone, characterized in that: In Step 3, the position where the UAV is located at the end of the k-th time period is obtained according to the following steps: The position of the UAV at the end of the k-th time period Taking the position where the k-th time period starts as the origin and the optimal flight distance of the UAV as the radius, on the spherical surface, the equation of the spherical surface is: ； Among them, are the coordinates of any point on the spherical surface; Selected point Use the point where the line connecting the selected point and point E intersects the sphere as the position where the drone is located at the end of the k-th time period .

6. A method for allocating communication power and flight power applicable to the return of an unmanned aerial vehicle according to claim 5, characterized in that: When there is no obstruction on the line connecting to point E, the selected point and the point where the line connecting to point E intersects the sphere are used as the position where the drone ends in the k-th time period , specifically including: Due to the intersection point on the line connecting to point E, the following is also satisfied: ； ； ； where t is a variable with a value range from 0 to 1; Combining the above equations, we have: ； Furthermore, the coordinates of the position where the drone is located at the end of the k-th time period are as follows: ； ； 。 7. A method for allocating communication power and flight power applicable to the return of an unmanned aerial vehicle according to claim 5, characterized in that: When there is an obstacle on the line connecting to point E, the selected point and the point where the line connecting to point E intersects the sphere are used as the position where the drone ends in the k-th time period , specifically including: Assume that the coordinate of the occluder in the vertical direction is , and the horizontal plane formed by it and the position where the k-th time period starts as the origin and the optimal flight distance of the drone as the radius forms a circular plane equation: ； Since the point is also on this plane, the tangent equation of the circle passing through the point can be obtained as follows: ； The straight line passing through the point and point E is: ； Since the tangent to the circle passing through the point is perpendicular to the line passing through the point and point E, we can obtain: ； Also, since the point is on the circle, we have: ； By combining the above two equations, the coordinates of point can be obtained as follows: ； ； ； Among them, the plus or minus sign is determined by the point and the coordinates of point E.

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