A UAV data acquisition system, control method, device, equipment and medium

Abstract

The present invention discloses a drone data acquisition system, control method, device, equipment and medium, the system comprising: a drone body, a supply station and at least one ground station; the ground station comprises a plurality of ground nodes, all ground nodes in each ground station are used to use the energy collected from the drone body to send data to the drone body through distributed beamforming technology; the drone body is used to transmit electric energy to all ground nodes of each ground station through radio frequency wireless energy transmission technology, and collect data from each ground station; the supply station is used to transmit electric energy to the drone body when the drone body is located at the electric energy supply point. The present invention can not only improve the energy efficiency of ground nodes and expand the communication range, but also improve the sustainability of data acquisition and drone work.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles, and in particular to a data acquisition system, control method, device, equipment and medium for unmanned aerial vehicles. Background Art

[0002] Distributed beamforming is a unique energy-saving technology that uses cooperative communication to allow two or more information sources to transmit the same message at the same time and control the phase of their transmission so that the signals can be effectively combined at the predetermined destination. Moreover, due to the mobility of drones, they can quickly fly close to the target device, thereby reducing the propagation distance of the transceiver. Therefore, a distributed data acquisition system based on drone assistance came into being.

[0003] As a wireless energy supply technology, RF wireless energy transmission technology provides energy for low-power wireless devices in a controllable and portable way. Wireless energy transmission, as a type of RF transmission, can be combined with wireless communication systems. Through joint design, wireless energy transmission technology and wireless communication technology can be integrated to form a wireless energy supply communication network. The characteristics of the wireless energy supply communication network make it very suitable for solving the energy supply and data collection problems of the Internet of Things. Moreover, due to its mobility and flexibility, drones can shorten the propagation distance of the transceiver by quickly approaching the target device, thereby improving the efficiency of RF wireless energy transmission and expanding the power supply coverage. Therefore, a wireless energy supply communication network assisted by drones was proposed.

[0004] In the existing distributed data acquisition system assisted by drones, drones are fixed and suspended in the air as data centers. There is no research on the flight trajectory of drones. The system performance is poor and it fails to provide energy to ground nodes to improve the sustainability of the system. In the existing wireless power supply communication network assisted by drones, ground devices send data to drones independently, making the communication range of each device relatively small. Moreover, the above two wireless data acquisition systems do not take into account the energy consumption and replenishment of the drone itself. Therefore, in view of the above shortcomings, it is urgent to make innovative improvements to the existing data acquisition system assisted by drones. Summary of the invention

[0005] The present invention provides a UAV data acquisition system, control method, device, equipment and medium to solve the technical problems of poor sustainability and limited communication range of existing UAV data acquisition systems. By designing a UAV data acquisition system that can charge the UAV body and designing a control method that can optimize the trajectory of the UAV and the configuration of ground wireless resources, not only the energy efficiency of ground nodes can be improved and the communication range can be expanded, but also the sustainability of data acquisition and UAV work can be improved, thereby promoting the intelligent control process of the UAV data acquisition system.

[0006] In order to solve the above technical problems, an embodiment of the present invention provides a UAV data acquisition system, including a UAV body, a supply station and at least one set of ground stations;

[0007] The ground station includes a plurality of ground nodes, and all the ground nodes in each group of the ground stations are used to utilize the energy collected from the drone body to send data to the drone body through distributed beamforming technology;

[0008] The drone body is used to transmit electric energy to all the ground nodes of each group of ground stations through radio frequency wireless energy transmission technology, and to collect data from each group of ground stations;

[0009] The supply station is used to transmit electric energy to the drone body when the drone body is located at the electric energy supply point.

[0010] As one of the preferred solutions, the supply station is a laser charger.

[0011] Another embodiment of the present invention provides a control method for a drone data acquisition system, which is applied to the drone data acquisition system as described above. The control method for the drone data acquisition system includes:

[0012] When the drone body flies to a preset altitude, position information and energy constraint information sent by each of the ground nodes are obtained, wherein the energy constraint information is a constraint condition that the energy consumption of the ground node sending data does not exceed the energy collected from the drone body;

[0013] The position information and the energy constraint information are processed based on a preset hovering point search algorithm to obtain a plurality of hovering point information of the drone body and power allocation information of each ground node under an ideal state, wherein the ideal state is to ignore the energy consumption of the drone body and the flight time of the drone body from one position to another, and each of the hovering point information includes a hovering point and a hovering time;

[0014] Based on the hovering point, the flight start and end points of the drone body and the power supply point of the drone body, a traveling salesman algorithm is used to obtain the shortest flight path of the drone body;

[0015] Determining a target flight path of the drone body based at least on the hovering time and the shortest flight path, wherein the target flight path includes the hovering time of the drone body at each of the hovering points and the power supply points;

[0016] At least based on the shortest flight path and the total mission duration of the UAV body, obtain the data transmission time of each group of the ground stations by using discretization processing;

[0017] At least based on the target flight path and the data transmission time, using a continuous convex approximation method to obtain actual power allocation information of all the ground nodes at each moment;

[0018] During the process of the UAV body performing the task, the flight control of the UAV body is performed based on the target flight path, and the power control of the ground node is performed based on the actual power allocation information.

[0019] As one of the preferred solutions, the data transmission time of each group of the ground stations is obtained by using discretization processing based at least on the shortest flight path and the total mission duration of the UAV body, including:

[0020] Determining a total hovering time of the drone body based on the shortest flight path, the total mission time of the drone body, and the maximum flight speed of the drone body;

[0021] The total duration of the mission is discretized, and based on the discretization result and the total hovering duration, the data transmission time of each group of the ground stations is obtained.

[0022] As one of the preferred solutions, the actual power allocation information of all the ground nodes at each moment is obtained by using a continuous convex approximation method based at least on the target flight path and the data transmission time, including:

[0023] At least based on the discretization result, the target flight path and the data transmission time of each group of the ground stations, construct a power allocation equation with the power allocation information of each ground node and the energy lower limit value received by each group of the ground stations from the drone body as decision variables, wherein the power allocation information is the main variable and the energy lower limit value is the auxiliary variable;

[0024] The power allocation equation is optimized and solved by using a continuous convex approximation method to obtain actual power allocation information of all the ground nodes at each moment.

[0025] Another embodiment of the present invention provides a control device for a drone data acquisition system, which is applied to the drone data acquisition system as described above. The control device for the drone data acquisition system includes:

[0026] An information acquisition module, used to acquire the position information and energy constraint information sent by each of the ground nodes when the drone body flies to a preset altitude, wherein the energy constraint information is a constraint condition that the energy consumption of the ground node sending data does not exceed the energy collected from the drone body;

[0027] A hovering point finding algorithm module, used to process the position information and the energy constraint information based on a preset hovering point finding algorithm, and obtain a plurality of hovering point information of the drone body and power allocation information of each ground node under an ideal state, wherein the ideal state is to ignore the energy consumption of the drone body and the flight time of the drone body from one position to another, and each of the hovering point information includes a hovering point and a hovering time;

[0028] A traveling salesman algorithm module, used to obtain the shortest flight path of the drone body by using a traveling salesman algorithm based on the hovering point, the flight start and end points of the drone body and the power supply point of the drone body;

[0029] a target flight path determination module, configured to determine a target flight path of the UAV body based at least on the hovering time and the shortest flight path, wherein the target flight path includes a hovering time of the UAV body at each of the hovering points and the power supply point;

[0030] A data transmission time determination module, configured to obtain the data transmission time of each group of the ground stations by using discretization processing based at least on the shortest flight path and the total mission duration of the UAV body;

[0031] A continuous convex optimization module, configured to obtain actual power allocation information of all the ground nodes at each moment by using a continuous convex approximation method based at least on the target flight path and the data transmission time;

[0032] The flight control module is used to perform flight control on the drone body based on the target flight path and to perform power control on the ground node based on the actual power allocation information during the drone body's mission execution.

[0033] As one of the preferred solutions, the data transmission time determination module includes:

[0034] A total hovering duration determining unit, configured to determine a total hovering duration of the drone body based on the shortest flight path, the total mission duration of the drone body, and the maximum flight speed of the drone body;

[0035] The discretization processing unit is used to discretize the total duration of the task, and obtain the data transmission time of each group of ground stations based on the result of the discretization processing and the total hovering duration.

[0036] As one of the preferred solutions, the continuous convex optimization module includes:

[0037] An equation construction unit, configured to construct a power allocation equation with power allocation information of each ground node and a lower limit value of energy received by each group of ground stations from the drone body as decision variables, based at least on the result of the discretization processing, the target flight path and the data transmission time of each group of ground stations, wherein the power allocation information is a main variable and the lower limit value of energy is an auxiliary variable;

[0038] The optimization solving unit is used to optimize and solve the power allocation equation by using a continuous convex approximation method to obtain the actual power allocation information of all the ground nodes at each moment.

[0039] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the control method of the drone data acquisition system as described above is implemented.

[0040] Yet another embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the control method of the drone data acquisition system as described above is implemented.

[0041] Compared with the prior art, the embodiments of the present invention have the following advantages:

[0042] (1) A new UAV data acquisition system was designed, including a UAV body, a refueling station, and at least one group of ground stations. In terms of energy, the UAV body can transmit downlink RF energy to the ground nodes in each group of ground stations, and the refueling station can transmit energy to the UAV body, thus forming a complete energy transmission chain to ensure the performance of the UAV body and the ground nodes. In terms of communication, multiple ground nodes transmit data uplink to the UAV body based on distributed beamforming technology, thereby ensuring sustainability while further improving the comprehensiveness of data acquisition.

[0043] (2) According to the characteristics of the above-mentioned UAV data acquisition system, a corresponding control method is designed, which comprehensively considers the three dimensions of factors of the UAV body, ground nodes and supply stations, and optimizes the control of the UAV to achieve optimized control of the UAV's flight trajectory, optimized control of the UAV's data acquisition, and optimized control of the ground wireless resources. This can not only improve the energy efficiency of the ground nodes and expand the communication range, but also improve the sustainability of data acquisition and UAV work, and promote the intelligent control process of the UAV data acquisition system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] FIG1 is a schematic diagram of the structure of a UAV data acquisition system in one embodiment of the present invention;

[0045] FIG2 is a schematic flow chart of a control method of a drone data acquisition system in one embodiment of the present invention;

[0046] FIG3 is a schematic diagram of a simulation of the trajectory of a drone body in one embodiment of the present invention;

[0047] FIG4 is a structural block diagram of a control device of a UAV data acquisition system in one embodiment of the present invention;

[0048] FIG5 is a structural block diagram of a terminal device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] In the description of this application, unless otherwise specified, "plurality" means two or more. The terms "vertical", "horizontal", "left", "right", "upper", "lower" and similar expressions used herein are for illustrative purposes only, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0051] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the art. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood by specific circumstances.

[0052] An embodiment of the present invention provides a drone data collection system. Specifically, please refer to Figure 1, which is a schematic diagram of the structure of a drone data collection system in one embodiment of the present invention, which includes a drone body, a supply station and at least one set of ground stations.

[0053] The ground station includes multiple ground nodes. All ground nodes in each group of ground stations are used to utilize the energy collected from the drone body to send data to the drone body through distributed beamforming technology.

[0054] The drone body is used to transmit power to all ground nodes of each group of ground stations through radio frequency wireless energy transmission technology, and to collect data from each group of ground stations.

[0055] The supply station is used to transmit electric energy to the drone body when the drone body is located at the electric energy supply point.

[0056] In the above embodiment, there is data flow transmission and energy flow transmission between the drone body and the ground node. For ease of understanding, each group of ground stations is also referred to as each cluster of ground stations, and ground nodes from different clusters represent ground nodes from different groups of ground stations. In addition, the function of the supply station is to provide electrical energy (laser flow) to the drone body, and a laser charger is preferably used in the figure. Of course, other types of chargers or terminal devices with energy interaction functions can also be used to power the drone body.

[0057] Specifically, a drone body equipped with a single antenna in the embodiment of the present invention uses wireless energy transmission technology to charge M groups of ground stations equipped with single antennas. Subsequently, each ground node uses the collected energy to send data to the drone body on the uplink through distributed beamforming technology. In order to ensure that the drone body always maintains sufficient energy, a laser charger is equipped in the working area, which is specifically used to charge the drone. It should be noted that since the energy of the laser is very concentrated, it may have potential lethality. Therefore, in the embodiment of the present invention, it is set that the supply station will only be started when the drone body is directly above the supply station, that is, the power supply point. In addition, in order to simplify the derivation process, this embodiment preliminarily sets each group of ground stations to include K ground nodes. Of course, the number of ground stations and ground nodes is determined by the scene design requirements of the actual drone data acquisition system, and is not specifically limited in the embodiment of the present invention.

[0058] The drone itself can achieve full-duplex mode, that is, wireless energy transmission and information transmission are performed at different frequencies. In this embodiment, the drone can receive information and send energy at the same time, and the ground nodes can also collect energy and send information at the same time. At the same time, the ground nodes in each set are regarded as a cluster, that is, a group of ground stations. They send common information to the drone through distributed beamforming, while nodes in different groups transmit different data. Considering the hardware limitations of the drone, the drone can only receive information sent by one group of ground nodes at the same time.

[0059] The goal of the UAV data acquisition system design in this embodiment is to maximize the minimum average data rate throughput among all groups by jointly optimizing the timing of data transmission in the entire mission, the flight trajectory of the UAV, the charging time of the UAV and the transmission power of all ground nodes, while satisfying the constraints of the UAV flight speed, the initial point and end point constraints of the UAV, the charging trajectory constraints of the UAV, the energy neutrality constraints of each ground node and the energy constraints of the UAV, thereby improving the sustainability of the system.

[0060] Another embodiment of the present invention provides a control method of a drone data acquisition system, which is applied to the drone data acquisition system described above. Specifically, please refer to FIG. 2 , which is a flow chart of a control method of a drone data acquisition system in one embodiment of the present invention, which includes steps S1 to S7:

[0061] S1. When the drone body flies to a preset altitude, obtain the location information and energy constraint information sent by each ground node;

[0062] Specifically, the energy constraint information is a constraint condition that the energy consumption of the ground node sending data does not exceed the energy collected from the drone body.

[0063] S2. Processing the position information and energy constraint information based on a preset hovering point search algorithm to obtain multiple hovering point information of the UAV body and power allocation information of each group of ground nodes under an ideal state;

[0064] Specifically, the ideal state is to ignore the energy consumption of the drone body and the flight time of the drone body from one position to another, and each hovering point information includes the hovering point and the hovering time.

[0065] S3, based on the hovering point, the flight start and end points of the drone body and the power supply point of the drone body, the traveling salesman algorithm is used to obtain the shortest flight path of the drone body;

[0066] S4. determining a target flight path of the UAV body based at least on the hovering time and the shortest flight path;

[0067] Specifically, the target flight path includes the hovering time of the drone body at each hovering point and power supply point.

[0068] S5. Based on at least the shortest flight path and the total mission duration of the UAV, obtain the data transmission time of each group of ground stations by using discretization processing;

[0069] Specifically, the total hovering time of the UAV body is determined based on the shortest flight path, the total mission time of the UAV body and the maximum flight speed of the UAV body. The total mission time is discretized, and the data transmission time of each group of ground stations is obtained based on the discretization result and the total hovering time.

[0070] S6. Based on at least the target flight path and the data transmission time, a continuous convex approximation method is used to obtain the actual power allocation information of all ground nodes at each moment;

[0071] Specifically, based at least on the results of discretization processing, the target flight path and the data transmission time of each group of ground stations, a power allocation equation is constructed with the power allocation information of each ground node and the lower limit of energy received by each group of ground stations from the UAV body as decision variables, wherein the power allocation information is the main variable and the lower limit of energy is the auxiliary variable; the continuous convex approximation method is used to optimize and solve the power allocation equation to obtain the actual power allocation information of all ground nodes at each moment.

[0072] S7. When the UAV is performing a mission, the flight of the UAV is controlled based on the target flight path, and the power of the ground node is controlled based on the actual power allocation information.

[0073] The following is a principle description of the control method of the drone data acquisition system in the embodiment of the present invention, and a unified description of the parameters involved in the following text:

[0074] represents a finite duty cycle; Indicates that the ground station Ground nodes in (use denoted by the horizontal coordinate of ); Indicates the horizontal coordinate of the laser charger; and They represent the fixed working altitude and horizontal position of the UAV respectively; and Respectively and about The first derivative of ; Indicates the flight speed of the drone; and They represent the initial and end points of the UAV’s level respectively; Indicates the maximum flight speed of the drone; Indicates time slot superior Channel phase shift to the drone; Indicates the fixed transmission power of the drone for wireless energy transmission; Indicates the conversion efficiency of radio frequency to direct current; and Represents ground nodes The transmission power and signal phase of Indicates the drone charging time; represents the charging power of the drone. Therefore, the following expression can be constructed:

[0075] (1)

[0076] (2)

[0077] In the above-mentioned UAV data acquisition system, the energy transmission of the downlink is considered first. Above, drones and ground nodes The distance is:

[0078] (3)

[0079] This embodiment considers the line-of-sight path loss channel between the ground and the air, and its phase changes randomly. The channel coefficient between is:

[0080] (4)

[0081] in represents the signal road loss index, Indicates the reference distance The power gain at m, is an imaginary unit. In particular, at the beginning of each time slot, the ground node can listen to the pilot signal sent by the drone to perform channel estimation. Therefore, the distance from the drone to the ground node is The power gain is:

[0082] (5)

[0083] It can be obtained that the ground node The energy collected at any time is:

[0084] (6)

[0085] In the above UAV system, the second consideration is the wireless information transmission of ground nodes on the uplink. All ground nodes in each group transmit a common message .in, is a cyclically symmetric complex Gaussian random variable with mean zero and variance 1, that is . First, IoT devices near the ground (such as monitoring sensors) will generate messages (such as physical phenomena) and then transmit them to nearby ground nodes. After that, the ground nodes will summarize and process the received messages as common messages. Or the ground nodes can directly generate common messages (such as video recording) by themselves. After the common messages are generated, they will be shared with other ground nodes through device-to-device communication technology. In this embodiment, a time division multiple access (TDMA) transmission protocol is considered, that is, although the uplink data transmission of all groups is transmitted in the same frequency band, the transmission time is orthogonal. In any time slot On, use To indicate the All ground nodes of the group ground station at time For uplink data transmission, To express the All ground nodes of the group ground station at time No uplink data transmission is performed.

[0086] Since the drone can only receive data from one set of ground stations at a time, and The drone receives a message from The signal of the group ground station can be expressed as:

[0087] (7)

[0088] Since the UAV can estimate the phase shift of the channel online, the design in this embodiment Make the signal received by the drone the strongest. Therefore, at any time The drone receives the The signal-to-noise ratio of the group ground station is:

[0089] (8)

[0090] in represents the noise power. Therefore, from The data rate throughput (bps / Hz) from the ground node of the group ground station to the UAV can be given as:

[0091] (9)

[0092] To maintain the intelligent operation of the system, the total energy consumption of data transmission of each ground node during each mission should not exceed the total energy of wireless energy transmission from the UAV. In this embodiment, the following energy neutrality constraints, i.e., energy constraint information, are present:

[0093] (10)

[0094] According to (9), from The average data rate throughput (bps / Hz) from the ground nodes of the group ground station to the UAV can be given as:

[0095] (11)

[0096] In the above-mentioned drone data collection system, the energy consumption and supply of drones are finally considered. Since the drone needs to fly to the laser charging station for a long time Charging, so there is

[0097] (12)

[0098] According to the prior art, the commonly used power consumption function of rotary wing UAV is:

[0099] (13)

[0100] in and are the blade profile power and induced power in the hovering state, and are the rotor blade tip speed and the average induced speed in hovering state, and are the fuselage drag ratio and rotor strength, and are air density and rotor disc area respectively. In order to maintain the sustainability of the drone, the energy of drone charging must be greater than the energy consumed for flight and downlink power supply. Therefore, the following expression is set in the embodiment of the present invention:

[0101] (14)

[0102] In order to improve the quality of service of communication, the data transmission schedule in the entire mission is jointly optimized under the premise of satisfying the constraints of the UAV flight speed (1), the initial and terminal points of the UAV (2), the charging trajectory of the UAV (12), the energy neutrality constraint of each ground node (10) and the energy constraint of the UAV (14). , the flight trajectory of the drone and the transmission power of all ground nodes , thereby maximizing the minimum average data rate throughput among all groups. Therefore, the problem can be expressed as:

[0103]

[0104] (15)

[0105] (16)

[0106] (1),(2),(10), (12)and(14).

[0107] From the above, it can be seen that the power consumption function of the rotorcraft is about The expression for data rate throughput is a complex function of , and The complex function, constraint (14) and objective function are not convex. In addition, is a discrete binary variable. Finally, the problem involves an infinite number of optimization variables in continuous time. For the above reasons, the problem is not convex and it is difficult to find the optimal solution.

[0108] In order to efficiently solve the above problems, the present invention first relaxes the problem and uses the algorithm to obtain the hovering point that is conducive to wireless power supply communication, the corresponding ground node allocation power and hovering time. Then, the traveling salesman algorithm is used to connect the flight start and end points, hovering points and power supply points of the drone in series. The drone’s route is designed by flying at high speed and continuously “flying-stopping”. Finally, the duration of the hovering point and the power supply point is designed according to the actual situation, so as to design an efficient drone flight trajectory.

[0109] The embodiment of the present invention optimizes the UAV data acquisition system from three dimensions: flight control, data acquisition control, and power control. For ease of understanding, the following are explained one by one:

[0110] When the UAV body flies to a preset altitude, the position information and energy constraint information sent by each ground node are obtained; the position information and energy constraint information are processed based on a preset hovering point search algorithm to obtain multiple hovering point information of the UAV body and power allocation information of each ground node under ideal conditions.

[0111] The specific contents of the above preset hovering point finding algorithm are as follows:

[0112] Ignoring the energy consumption of the drone, the above drone data collection system only considers wireless power supply communication (downlink energy supply for the drone and uplink data transmission of the ground node), and then assumes that the mission time of the drone is very long (for example ), so that the time it takes for the drone to fly from one location to another can be ignored. Therefore, constraints (1), (2), (12) and (14) can be ignored. In the embodiment of the present invention, an auxiliary variable is also introduced ,in, is the lower bound of the average data rate throughput of all ground stations. Then the problem can be equivalently relaxed as:

[0113]

[0114]

[0115] (10), (15), and (16).

[0116] Although the above problem (P1) is still non-convex, it satisfies the time-sharing condition. Therefore, problem (P1) has strong duality with its Lagrangian dual problem. Therefore, this embodiment uses the Lagrangian dual method to optimally solve problem (P1). Assume and denote the dual variables of the mth constraint and the (k, m)th constraint in (15) and (10), respectively. For the convenience of description, we define ,

[0117] and The partial Lagrangian function of problem P1 can be expressed as:

[0118]

[0119] The dual function is:

[0120] (17)

[0121] st(15) and (16).

[0122] In order to ensure the dual function The range of has an upper bound (e.g. ), it is necessary to ensure that there is Therefore, the dual problem of problem (P1) can be given as:

[0123]

[0124] Next, we first solve problem (17) to obtain the dual function , and then solve the dual problem (D1) to solve problem (P1).

[0125] First, given and Solve problem (P1) to obtain the dual function Among them, the given and must be a feasible value of the dual problem (D1). Therefore, problem (17) can be decomposed into the following sub-problems.

[0126] (18)

[0127] (19)

[0128] st(15) and (16).

[0129] Here, problem (19) has infinitely many time It is worth noting that due to , the optimal function value of problem (18) is zero. Therefore, the optimal solution of problem (18) can be any real number. Therefore, we only need to focus on problem (19). Since the subproblems of problem (19) are the same at different time points, this embodiment can remove the index For convenience.

[0130] For problem (19), according to constraints (15) and (16), we know A total of Next, we will The solution to solve problem (19) is to obtain the optimal solution for each solution. and Then compare the objective function values ​​of each solution and find the largest corresponding solution as the solution to problem (19).

[0131] First, given ,have . Therefore, problem (19) can be expressed as:

[0132] (20)

[0133] To solve problem (20), first Optimize under the premise of , and then find the optimal For the convenience of expression, let and Respectively represent The distributed beamforming vectors and synthetic channel vectors of the group of ground nodes. After that, problem (20) can be simplified to:

[0134] (twenty one)

[0135] in, . Generally there are ,otherwise It is the Supreme Realm. and After that, problem (21) can be transformed into:

[0136] (twenty two)

[0137] It is worth noting that question (22) must be Therefore, problem (22) can be transformed into:

[0138] (twenty three)

[0139] Problem (23) is convex. Therefore, by observing the first-order derivative of the objective function, this embodiment can obtain the optimal solution of problem (23) as:

[0140] (twenty four)

[0141] in, This form indicates About , , Correspondingly, the optimal solution to problem (24) is:

[0142] (25)

[0143] So, The first The optimal power allocation for ground nodes is:

[0144] (26)

[0145] in Indicates that the vector except the The first element is 1, and the rest are 0. After substituting into (20), we can find the optimal position of problem (20) by searching in two dimensions in the working area according to the following formula (27): .

[0146] (27)

[0147] In solving this After the above situation, the solution corresponding to the maximum objective function value is selected as the optimal solution of problem (17). , ,and , so that the dual function can be obtained It is worth noting that when the optimal solution of problem (17) is not unique, we can arbitrarily choose one to obtain the dual function .

[0148] After obtaining the dual function, this embodiment solves the dual problem (D1) by minimizing the dual function. The method used is an ellipsoid method based on the sub-gradient descent method, where the sub-gradient is:

[0149] (29)

[0150] So we can get the optimal solution to problem (D1) and The specific process is as follows:

[0151] Initialization: Setup , The initial value of and the convergence conditions of the ellipsoid method;

[0152] (1) Loop:

[0153] (2) In the given , Under this condition, according to formulas (26) and (27), the optimal solution of problem (17) is obtained. ;

[0154] (3) Update using the ellipsoid method according to the subgradient (29) , ;

[0155] (4) Termination: reaching the convergence condition;

[0156] Output: Settings , , output This is the optimal solution to problem (P1).

[0157] Although the above can obtain the ground node power allocation at each optimal hovering point, it is still necessary to determine the specific hovering time to construct the optimal solution to the original problem (P1) and . Solving problem (19) considers The situation and The objective function values ​​of problem (19) obtained under the above conditions must be equal, otherwise the objective function value of problem (P1) cannot reach the maximum minimum average rate throughput among all groups, so problem (P1) has The optimal hovering point. Indicates hovering over Next, this embodiment needs to solve the following problem to obtain the optimal time-sharing hovering time.

[0158]

[0159]

[0160]

[0161]

[0162] Since the above problem is a linear problem, the optimal hovering time at each position can be solved by the CVX tool. So far, problem (P1) has been optimally solved. From the above solution process, we can get the optimal drone trajectory for problem (P1) The structure of the optimal hovering point is obtained, and the wireless power supply communication of the original problem is obtained. Hover Points , corresponding ground node allocation power and hover time .

[0163] Afterwards, based on the hovering point, the flight start and end points of the drone body, and the power supply point of the drone body, the traveling salesman algorithm is used to process and obtain the shortest flight path of the drone body. Specifically, please refer to Figure 3, which shows a simulation schematic diagram of the trajectory of the drone body in one embodiment of the present invention. Among them, the horizontal axis represents the horizontal coordinate of the horizontal position of the drone body, and the vertical axis represents the vertical coordinate of the horizontal position of the drone body. Furthermore, in order to allow the drone to have more hovering time, the flight path of the drone must be minimized. The drone starts from the starting point, passes through all hovering hotspots (hovering points) and laser charging stations (power supply points), and finally flies to the end point. This is a typical traveling salesman problem. This problem can be solved by exhaustive method, that is, calculating the length of all paths (a total of There are many paths), take the shortest one as the optimal flight path for the drone, assuming the length is .

[0164] Next, the target flight path of the drone body is determined based at least on the hovering time and the shortest flight path. Specifically, since the maximum flight speed is , so the total hovering time is The power consumed is Each time from flying to stopping, or from stopping to flying, the speed is in a very short time (relative to can be ignored) by to 0 or from 0 to In this embodiment, it is assumed that the energy consumption of these acceleration and deceleration is a fixed value. ,common Second-rate.

[0165] In order to meet constraint (14), it should be ensured that the total energy consumed by acceleration, deceleration, hovering and flight should not exceed the laser charging energy: In order to allow the drone to hover over the hotspot more time, , and the specific hovering time of each hovering hotspot is: At this point, the drone track The design is completed (including flight trajectory information, the hovering time of the drone at each hovering point and power supply point). That is, during the drone's mission, the drone can Control the flight of the drone.

[0166] The optimization control of data transmission dimension is as follows:

[0167] After designing the data transmission arrangement at the hovering point, that is, the total hovering time, only the remaining time except the hovering point remains. Preferably, this embodiment uses a low-complexity method: first, the entire task time Discretize into finite time slots, using the collection Represented by, and the length of each time slot is , and assuming is large enough so that within each time slot, the position of the drone can be assumed to remain unchanged. The time slots are alternately allocated to all ground stations to transmit data. (that is, the data transmission time for each ground station) design is completed.

[0168] The optimization control of power distribution dimension is as follows:

[0169] The entire task time After discretization, given the above designed efficient flight trajectory (target flight path) and data transmission arrangements (data transmission time of each ground station), the lower limit of energy received by each ground station from the drone body is introduced This auxiliary variable constructs the power allocation equation with the power allocation information of each ground node and the lower limit of energy received by each ground station from the drone body as the decision variable, as follows:

[0170]

[0171]

[0172] (30)

[0173]

[0174] Due to the existence of non-convex constraint (30), problem (P2) is still not convex. In order to deal with non-convex constraint (30), this embodiment adopts continuous convex approximation method to approximate non-convex problem to convex problem, and continuously updates and iterates. .let Indicates The local point after iterations. After that, since the first-order Taylor expansion of all convex functions at any point is the global lower bound of this point, we have The lower limits are as follows:

[0175]

[0176] At each given local point In the iteration, we use The lower bound To replace them. Therefore, this trajectory optimization problem becomes a convex optimization problem, which can be solved using the CVX tool. The design of the actual power allocation information of all ground nodes at each moment is completed. When the UAV is performing its mission, the power of each ground node is controlled by the actual power allocation information.

[0177] Based on the above content, the drone body flies according to the corresponding trajectory, hovers according to the corresponding hovering point, is charged by the laser charger, and the ground node sends data to the drone body. During the entire mission cycle, the drone can perform carrier synchronization, time synchronization and channel estimation with the ground node to ensure the stability of distributed beamforming. Finally, the drone body completes data collection and reaches the end point, ending the workflow of the entire drone data collection system.

[0178] Another embodiment of the present invention provides a control device for a drone data acquisition system, which is used in the drone data acquisition system described above. Specifically, please refer to FIG. 4 , which shows a structural block diagram of a control device for a drone data acquisition system in one embodiment of the present invention, and the control device for the drone data acquisition system includes:

[0179] The information acquisition module 1 is used to acquire the position information and energy constraint information sent by each ground node when the drone body flies to a preset altitude, wherein the energy constraint information is a constraint condition that the energy consumption of the ground node sending data does not exceed the energy collected from the drone body;

[0180] The hovering point finding algorithm module 2 is used to process the position information and the energy constraint information based on the preset hovering point finding algorithm to obtain multiple hovering point information of the drone body and the power allocation information of each ground node under an ideal state, wherein the ideal state is to ignore the energy consumption of the drone body and the flight time of the drone body from one position to another, and each hovering point information includes the hovering point and the hovering time;

[0181] Traveling salesman algorithm module 3, used to obtain the shortest flight path of the drone body by using the traveling salesman algorithm based on the hovering point, the flight start and end points of the drone body and the power supply point of the drone body;

[0182] A target flight path determination module 4 is used to determine the target flight path of the drone body based at least on the hovering time and the shortest flight path, wherein the target flight path includes the hovering time of the drone body at each hovering point and the power supply point;

[0183] The data transmission time determination module 5 is used to obtain the data transmission time of each ground station by using discretization processing based on at least the shortest flight path and the total mission duration of the UAV body;

[0184] A continuous convex optimization module 6 is used to obtain actual power allocation information of all ground nodes at each moment by using a continuous convex approximation method based at least on a target flight path and a data transmission time;

[0185] The flight control module 7 is used to perform flight control on the drone body based on the target flight path and to perform power control on the ground node based on the actual power allocation information when the drone body performs the mission.

[0186] Furthermore, in the above embodiment, the data transmission time determination module 5 includes:

[0187] A total hovering time determination unit, used to determine the total hovering time of the drone body based on the shortest flight path, the total mission time of the drone body and the maximum flight speed of the drone body;

[0188] The discretization processing unit is used to discretize the total mission duration, and obtain the data transmission time of each ground station based on the discretization result and the total hovering duration.

[0189] Furthermore, in the above embodiment, the continuous convex optimization module 6 includes:

[0190] An equation construction unit is used to construct a power allocation equation with power allocation information of each ground node and a lower limit value of energy received by each ground station from the UAV body as decision variables based on at least the discretization result, the target flight path and the data transmission time of each ground station, wherein the power allocation information is a main variable and the lower limit value of energy is an auxiliary variable;

[0191] The optimization solving unit is used to optimize and solve the power allocation equation by using a continuous convex approximation method to obtain the actual power allocation information of all ground nodes at each moment.

[0192] It should be noted that each module in the control device of the above-mentioned unmanned aerial vehicle data acquisition system can be fully or partially implemented by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. For the specific definition of the control device of an unmanned aerial vehicle data acquisition system, please refer to the definition of the control method of an unmanned aerial vehicle data acquisition system above. The two have the same functions and effects, which will not be repeated here.

[0193] An embodiment of the present invention further provides a terminal device, the terminal device comprising:

[0194] processor, memory, and bus;

[0195] The bus is used to connect the processor and the memory;

[0196] The memory is used to store operation instructions;

[0197] The processor is used to call the operation instruction, and the executable instruction enables the processor to perform the operation corresponding to the control method of the drone data acquisition system as described above in the present invention.

[0198] In an optional embodiment, a terminal device is provided, as shown in FIG5 , and the terminal device 5000 shown in FIG5 includes: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are connected, such as through a bus 5002. Optionally, the terminal device 5000 may also include a transceiver 5004. It should be noted that in actual applications, the transceiver 5004 is not limited to one, and the structure of the terminal device 5000 does not constitute a limitation on the embodiment of the present invention.

[0199] Processor 5001 may be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 5001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0200] The bus 5002 may include a path to transmit information between the above components. The bus 5002 may be a PCI bus or an EISA bus, etc. The bus 5002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in FIG. 5 , but it does not mean that there is only one bus or one type of bus.

[0201] The memory 5003 may be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an EEPROM, a CD-ROM or other optical disk storage, an optical disk storage (including a compressed optical disk, a laser disk, an optical disk, a digital versatile disk, a Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0202] The memory 5003 is used to store application code for executing the solution of the present invention, and the execution is controlled by the processor 5001. The processor 5001 is used to execute the application code stored in the memory 5003 to implement the content shown in any of the above method embodiments.

[0203] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the control method of the above-mentioned drone data acquisition system of the present invention is implemented.

[0204] Yet another embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed on a computer, enables the computer to execute the corresponding contents of the aforementioned method embodiments.

[0205] In addition, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented.

[0206] The embodiments of the present invention provide a drone data acquisition system, control method, device, equipment, and medium, the beneficial effects of which are at least one of the following:

[0207] (1) A new UAV data acquisition system was designed, including a UAV body, a refueling station, and at least one group of ground stations. In terms of energy, the UAV body can transmit downlink RF energy to the ground nodes in each group of ground stations, and the refueling station can transmit energy to the UAV body, thus forming a complete energy transmission chain to ensure the performance of the UAV body and the ground nodes. In terms of communication, multiple ground nodes transmit data uplink to the UAV body based on distributed beamforming technology, thereby ensuring sustainability while further improving the comprehensiveness of data acquisition.

[0208] (2) According to the characteristics of the above-mentioned UAV data acquisition system, a corresponding control method is designed, which comprehensively considers the three dimensions of factors of the UAV body, ground nodes and supply stations, and optimizes the control of the UAV to achieve optimized control of the UAV's flight trajectory, optimized control of the UAV's data acquisition, and optimized control of the ground wireless resources. This can not only improve the energy efficiency of the ground nodes and expand the communication range, but also improve the sustainability of data acquisition and UAV work, and promote the intelligent control process of the UAV data acquisition system.

[0209] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A control method for a drone data collection system, applied to a drone data collection system, characterized in that: The UAV data acquisition system includes a UAV body, a supply station and at least one set of ground stations; The ground station includes a plurality of ground nodes, and all the ground nodes in each group of the ground stations are used to utilize the energy collected from the drone body to send data to the drone body through distributed beamforming technology; The drone body is used to transmit electric energy to all the ground nodes of each group of ground stations through radio frequency wireless energy transmission technology, and to collect data from each group of ground stations; The supply station is used to transmit electric energy to the drone body when the drone body is located at the electric energy supply point; The supply station is a laser charger; The control method of the UAV data acquisition system includes: When the drone body flies to a preset altitude, position information and energy constraint information sent by each of the ground nodes are obtained, wherein the energy constraint information is a constraint condition that the energy consumption of the ground node sending data does not exceed the energy collected from the drone body; The position information and the energy constraint information are processed based on a preset hovering point search algorithm to obtain a plurality of hovering point information of the drone body and power allocation information of each ground node under an ideal state, wherein the ideal state is to ignore the energy consumption of the drone body and the flight time of the drone body from one position to another, and each of the hovering point information includes a hovering point and a hovering time; Based on the hovering point, the flight start and end points of the drone body and the power supply point of the drone body, a traveling salesman algorithm is used to obtain the shortest flight path of the drone body; Determining a target flight path of the drone body based at least on the hovering time and the shortest flight path, wherein the target flight path includes the hovering time of the drone body at each of the hovering points and the power supply points; At least based on the shortest flight path and the total mission duration of the UAV body, obtain the data transmission time of each group of the ground stations by using discretization processing; At least based on the target flight path and the data transmission time, using a continuous convex approximation method to obtain actual power allocation information of all the ground nodes at each moment; During the process of the UAV body performing the task, the flight control of the UAV body is performed based on the target flight path, and the power control of the ground node is performed based on the actual power allocation information.

2. The control method of the UAV data acquisition system according to claim 1, characterized in that: The method of obtaining the data transmission time of each group of the ground stations by using discretization processing based at least on the shortest flight path and the total mission duration of the drone body comprises: Determining a total hovering time of the drone body based on the shortest flight path, the total mission time of the drone body, and the maximum flight speed of the drone body; The total duration of the mission is discretized, and based on the discretization result and the total hovering duration, the data transmission time of each group of the ground stations is obtained.

3. The control method of the UAV data acquisition system according to claim 2, characterized in that: The method of obtaining actual power allocation information of all the ground nodes at each moment by using a continuous convex approximation method based at least on the target flight path and the data transmission time includes: At least based on the discretization result, the target flight path and the data transmission time of each group of the ground stations, construct a power allocation equation with the power allocation information of each ground node and the energy lower limit value received by each group of the ground stations from the drone body as decision variables, wherein the power allocation information is the main variable and the energy lower limit value is the auxiliary variable; The power allocation equation is optimized and solved by using a continuous convex approximation method to obtain actual power allocation information of all the ground nodes at each moment.

4. A control device for a drone data collection system, applied to a drone data collection system, characterized in that: The UAV data acquisition system includes a UAV body, a supply station and at least one set of ground stations; The ground station includes a plurality of ground nodes, and all the ground nodes in each group of the ground stations are used to utilize the energy collected from the drone body to send data to the drone body through distributed beamforming technology; The drone body is used to transmit electric energy to all the ground nodes of each group of ground stations through radio frequency wireless energy transmission technology, and to collect data from each group of ground stations; The supply station is used to transmit electric energy to the drone body when the drone body is located at the electric energy supply point; The supply station is a laser charger; The control device of the UAV data acquisition system includes: An information acquisition module, used to acquire the position information and energy constraint information sent by each of the ground nodes when the drone body flies to a preset altitude, wherein the energy constraint information is a constraint condition that the energy consumption of the ground node sending data does not exceed the energy collected from the drone body; A hovering point finding algorithm module, used to process the position information and the energy constraint information based on a preset hovering point finding algorithm, and obtain a plurality of hovering point information of the drone body and power allocation information of each ground node under an ideal state, wherein the ideal state is to ignore the energy consumption of the drone body and the flight time of the drone body from one position to another, and each of the hovering point information includes a hovering point and a hovering time; A traveling salesman algorithm module, used to obtain the shortest flight path of the drone body by using a traveling salesman algorithm based on the hovering point, the flight start and end points of the drone body and the power supply point of the drone body; a target flight path determination module, configured to determine a target flight path of the UAV body based at least on the hovering time and the shortest flight path, wherein the target flight path includes a hovering time of the UAV body at each of the hovering points and the power supply point; A data transmission time determination module, configured to obtain the data transmission time of each group of the ground stations by using discretization processing based at least on the shortest flight path and the total mission duration of the UAV body; A continuous convex optimization module, configured to obtain actual power allocation information of all the ground nodes at each moment by using a continuous convex approximation method based at least on the target flight path and the data transmission time; The flight control module is used to perform flight control on the drone body based on the target flight path and to perform power control on the ground node based on the actual power allocation information during the drone body's mission execution.

5. The control device of the UAV data acquisition system according to claim 4, characterized in that: The data transmission time determination module comprises: A total hovering duration determining unit, configured to determine a total hovering duration of the drone body based on the shortest flight path, the total mission duration of the drone body, and the maximum flight speed of the drone body; The discretization processing unit is used to discretize the total duration of the task, and obtain the data transmission time of each group of ground stations based on the result of the discretization processing and the total hovering duration.

6. The control device of the UAV data acquisition system according to claim 5, characterized in that: The continuous convex optimization module comprises: An equation construction unit, configured to construct a power allocation equation with power allocation information of each ground node and a lower limit value of energy received by each group of ground stations from the drone body as decision variables, based at least on the result of the discretization processing, the target flight path and the data transmission time of each group of ground stations, wherein the power allocation information is a main variable and the lower limit value of energy is an auxiliary variable; The optimization solving unit is used to optimize and solve the power allocation equation by using a continuous convex approximation method to obtain the actual power allocation information of all the ground nodes at each moment.

7. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the control method of the unmanned aerial vehicle data acquisition system as described in any one of claims 1 to 3 when executing the computer program.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the control method of the drone data acquisition system according to any one of claims 1 to 3 is implemented.

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