Data-driven heterogeneous unmanned aerial vehicle group assisted wireless sensor data collection method

Abstract

The invention relates to the technical field of crossing of unmanned aerial vehicles and wireless sensor network technologies, in particular to a data-driven heterogeneous unmanned aerial vehicle group assisted wireless sensor data collection method, which comprises the following steps of: 1, constructing a heterogeneous unmanned aerial vehicle formation layered data collection system; 2, determining the communication coverage range of the data collection unmanned aerial vehicle to the wireless sensor network; step 3, performing a first round of regular hexagon coverage; step 4, carrying out a second round of regular hexagon coverage; 5, optimizing the initial flight path of the communication unmanned aerial vehicle; step 6, determining center coordinate information of a task area of the data collection unmanned aerial vehicle; 7, performing data unmanned aerial vehicle formation dynamic task allocation; 8, performing data collection and unmanned aerial vehicle position adjustment; step 9, the communication unmanned aerial vehicle performs dynamic position adjustment; step S10, judging whether data collection of the wireless sensor nodes is completed or not, if so, circulating the steps S7 to S10, and performing the next round of task; if not, the task is ended.

Description

Technical Field

[0001] The present invention relates to the technical field of intersection of unmanned aerial vehicle (UAV) and wireless sensor network technologies, and in particular to a data-driven heterogeneous UAV swarm-assisted wireless sensor data collection method. Background Art

[0002] Since the birth of wireless sensor networks, due to its flexible node deployment and diverse network structure, this technology has been widely used in the fields of industry, agriculture and environmental monitoring, and has shown a trend of increasing node scale, wide distribution range and complex application environment. Especially in the field environment, building a large-scale wireless sensor network faces many challenges, such as node deployment, positioning and data transmission reliability in complex environments.

[0003] In recent years, the rapid advancement of drone technology has brought new solutions to these challenges. With their flexibility, mobility and autonomy, drones have become an important tool for data transmission and network maintenance in wireless sensor networks. However, as the scale of sensor networks expands, a single drone can no longer meet the needs of fast data collection in large-scale networks. Therefore, designing a reasonable heterogeneous drone formation coordination mechanism to optimize data collection efficiency and extend network life, while considering the energy consumption characteristics and data volume of different nodes, has become a key issue in current research. Summary of the invention

[0004] In order to solve the problem that the existing single UAV can hardly meet the demand for rapid data collection in a large-scale network, the present invention provides a data-driven heterogeneous UAV swarm-assisted wireless sensor data collection method.

[0005] The present invention proposes a data-driven heterogeneous UAV swarm-assisted wireless sensor data collection method, which is a method for data collection of large-scale wireless sensor networks assisted by a data-driven heterogeneous UAV formation. The method adopts a hierarchical network architecture, and a UAV formation composed of two types works collaboratively. Through dynamic task allocation and data perception strategies, efficient collection of large-scale sensor node data and energy balance are achieved.

[0006] The core innovation of the present invention is to introduce a heterogeneous UAV formation, dynamically adjust the task allocation and flight path of the UAV according to the data distribution and residual energy of the sensor nodes, so as to minimize the energy consumption of data transmission, improve the data transmission rate, and extend the operation time of the entire network; the specific technical solutions of the present invention are as follows:

[0007] A data-driven heterogeneous drone swarm-assisted wireless sensor data collection method, the method comprising the following steps:

[0008] Step S1: Determine the distribution area and range of wireless sensor nodes, and build a hierarchical data collection system for heterogeneous UAV formations, including data collection UAVs and communication drones ;

[0009] Step S2: Identify the data collection drone Communication coverage of wireless sensor nodes;

[0010] Step S3: According to the communication coverage obtained in step S2, the distribution area of ​​the wireless sensor nodes is divided into the first round of regular hexagonal coverage to form the first layer of cellular coverage structure, i.e., cellular coverage 1, and the center coordinates of all regular hexagonal areas are obtained. , as the mission area for data collection drones;

[0011] Step S4: Calculate the communication range between the communication UAV and the data collection UAV, further divide the distribution area of ​​the wireless sensor nodes into a second round of regular hexagonal coverage, establish the second layer of cellular coverage structure, i.e., cellular coverage 2, and obtain the initial track point of the communication UAV ;

[0012] Step S5: Set the initial track point of the communication drone As input, the initial flight path of the communication UAV is optimized to obtain the optimized communication UAV track matrix ;

[0013] Step S6: According to the track matrix The sequence of internal track points determines each communicating drone one by one The center coordinate information of the data collection UAV mission area contained in the communication coverage area;

[0014] Step S7: According to the track matrix of the communication drone , to carry out dynamic task allocation of data drone formation under the guidance of communication drone;

[0015] Step S8: The data collection drone enters the corresponding mission area, senses the amount of data carried by the wireless sensor nodes, and performs data-driven data collection position adjustment to reduce the energy consumption of the wireless sensor nodes;

[0016] Step S9: the communication UAV dynamically adjusts its position according to the position of the data collection UAV formation to improve the data transmission rate;

[0017] Step S10: Determine whether data collection of all wireless sensor nodes is completed; if so, loop through steps S7 to S10 to perform the next round of tasks; if not, end the task.

[0018] Furthermore, the step S1: determining the distribution area and range of the wireless sensor nodes, constructing a heterogeneous UAV formation hierarchical data collection system, including data collection UAVs and communication drones ; The details are as follows:

[0019] Step S1.1: Construct a heterogeneous UAV data collection and transmission network; the heterogeneous UAV data collection and transmission network includes two types of UAVs and wireless sensor nodes: the two types of UAVs are Data collection drone And 1 communication drone ; The data collection drone number is ; The number of wireless sensor nodes is , numbered ;

[0020] Step S1.2: The heterogeneous UAV data collection and transmission network is divided into three layers; the first layer is the wireless sensor node layer, which is responsible for data collection; the second layer is the data collection UAV layer, which is responsible for the collection of sensor data in the specified mission area; the third layer is the communication UAV layer, which is responsible for the UAV formation mission planning and acts as a relay, using the airborne radio to transmit the data collected by the data collection UAV to the cloud or base station by amplifying and forwarding.

[0021] Furthermore, the step S2: determining the data collection drone The communication coverage of wireless sensor nodes is as follows:

[0022] Step S2.1: Calculate the time t when the wireless sensor node With data collection drones Distance , expressed as:

[0023] ;Formula (1);

[0024] in, Represents a data collection drone Height, , For wireless sensor nodes With data collection drones The coordinates of in two-dimensional space;

[0025] Step S2.2: Calculate data collection drone With wireless sensor nodes The channel power gain between , expressed as:

[0026] ;Formula (2);

[0027] in, represents the channel power gain at 1m;

[0028] Step S2.3: Based on the channel power gain Find wireless sensor nodes Uplink transmission rate , expressed as:

[0029] ;Formula (3);

[0030] in, is the channel bandwidth, For wireless sensor nodes The transmission power, Represents a data collection drone Gaussian white noise power at the receiving end;

[0031] Step S2.4: During the data collection process, the wireless sensor nodes Uplink transmission rate Must be greater than or equal to the minimum data transfer rate , that is, satisfy ;

[0032] Step S2.5: According to formula (3), the minimum data transmission rate The constraint is transformed into a distance constraint, expressed as:

[0033] ;Formula (4);

[0034] ;Formula (5);

[0035] in, To meet the uplink transmission rate Under the constraints, wireless sensor nodes With data collection drones The maximum distance between

[0036] Step S2.6: Data Collection Drone The half beam width is used to Directional antennas for wireless sensor nodes For communication, the directional antenna radiates vertically toward the ground;

[0037] Step S2.7: Calculate data collection drone Communication coverage radius and maximum flight altitude , expressed as:

[0038] ;Formula (6);

[0039] ;Formula (7).

[0040] Furthermore, in step S3, according to the communication coverage obtained in step S2, the distribution area of ​​the wireless sensor nodes is divided into a first round of regular hexagonal coverage to form a first layer of cellular coverage structure, i.e., cellular coverage 1, and the center coordinates of all regular hexagonal areas are obtained. , as the mission area for data collection drones; details are as follows:

[0041] Step S3.1: Wireless sensor nodes The distribution area size is x km×y km, and a Cartesian coordinate system is established with the origin at , based on data collection drones Communication coverage radius , calculate the center coordinates of each regular hexagon:

[0042] ;Formula (8);

[0043] Step S3.2: Create a matrix , used to save the center coordinates of each regular hexagon ,but:

[0044] ;Formula (9);

[0045] in, Respectively represent the wireless sensor nodes The distribution area is divided into A regular hexagonal area, Represent the row and column indices of each hexagonal area respectively;

[0046] Step S3.3: According to the center coordinates of the regular hexagon , using data collection drones Communication coverage radius The length of the regular hexagon is calculated, and the vertex coordinates of each regular hexagon are calculated to complete the regular hexagon coverage of the mission area. Each regular hexagon area is a data collection drone. mission area.

[0047] Furthermore, the step S4: calculates the communication range between the communication drone and the data collection drone, further performs a second round of regular hexagonal coverage division on the distribution area of ​​the wireless sensor nodes, establishes a second layer of cellular coverage structure, i.e., cellular coverage 2, and obtains the initial track point of the communication drone ; The details are as follows:

[0048] Step S4.1: Input data collection drone Maximum transmit power , communication drones Gaussian white noise power at the receiving end , refer to step S2, formula (1) to formula (5), calculate to ensure the minimum data transmission rate Based on the communication drone With data collection drones Maximum distance , when the communication drone and data collection drones The distance is greater than When the communication connection is lost;

[0049] Step S4.2: Communicate with the drone and data collection drones Independent frequency bands are used between them, and independent omnidirectional antennas are equipped for communication. Coverage radius , and communication drones and data collection drones The maximum height difference between the two is related to the communication between the UAVs. and all data collection drones When the flight altitude is consistent, the communication drone Coverage reaches the maximum, that is, ;

[0050] Step S4.3: Referring to step S3, according to the communication drone Coverage radius , for wireless sensor nodes The distribution area of ​​​​the second round of regular hexagonal coverage is obtained, and the number is A regular hexagonal area, corresponding to the regular hexagon center coordinates , ;

[0051] Step S4.4: Create a matrix , used to save the center coordinates of each regular hexagon obtained from the second round of regular hexagon coverage ,but:

[0052] ;Formula (10);

[0053] Step S4.5: Transform the matrix The center coordinates of each regular hexagon in As a communication drone The initial track point.

[0054] Furthermore, in step S5, the initial track point of the communication drone is As input, the initial flight path of the communication UAV is optimized to obtain the optimized communication UAV track matrix ; The details are as follows:

[0055] Step S5.1: Transform the matrix Flatten by columns Matrix of size ;

[0056] Step S5.2: Communicate with the UAV The flight path is optimized and the following optimization model is established:

[0057] ;Formula (11);

[0058] ;Formula (12);

[0059] in, Used to mark whether the line between any two initial track points is planned to the communication drone within the flight path of Represents the Kth initial track point and the Lth initial track point Link is planned as a communication drone flight path, otherwise ; Formula (11) and Formula (12) represent the matrix Sort the centers of the inner regular hexagons to get a new matrix , communication drone The new matrix The initial track point in the path is taken as the path point, and the new matrix When flying in sequence, the total flight distance is the shortest.

[0060] Furthermore, the step S6: according to the track matrix The sequence of internal track points determines each communicating drone one by one The center coordinate information of the data collection drone mission area contained in the communication coverage area is as follows:

[0061] Step S6.1: The data transmission power of the UAV is usually several times or even dozens of times that of the wireless sensor node, so the communication UAV Coverage radius Bigger than a data collection drone Communication coverage radius ,but Therefore, in the communication drone The corresponding coordinates of the center of the regular hexagon A regular hexagon centered It includes multiple data collection drones Coverage area divided by regular hexagon center coordinates A regular hexagon centered ;

[0062] Step S6.2: Follow the communication drone The flight sequence of the flight path points, i.e. the track matrix , determine the communication drone No. mission area Data collection drones included Coverage area divided by regular hexagon center coordinates A regular hexagon centered , and create the matrix ,storage The corresponding regular hexagon center coordinates .

[0063] Furthermore, in step S7: according to the track matrix of the communication drone , to carry out dynamic task allocation of data drone formation under the guidance of communication drone; the details are as follows:

[0064] Step S7.1: Introduce the concept of task rounds and initialize task rounds ; Data collection drone formation completes wireless sensor nodes in the specified area Data is collected once, ;

[0065] Step S7.2: Create a task library matrix , used to save the During the mission, the data collection drone Optional task area center coordinates, initialize the task library matrix is an empty set; among them, the task library matrix It changes dynamically. In each round of tasks, the task library matrix The number of internal mission points needs to be greater than or equal to the number of data collection drones The number of; if the task library matrix The dimension is , then it is necessary to satisfy ; After the corresponding task point is selected, from the task library matrix Delete in; when , indicating that a new task point needs to be added, that is, ;

[0066] Step S7.3: Establish the Round data collection UAV formation task allocation model; that is, in the task library matrix Inside, based on data collection drones ( )'s current location , for each data collection drone Find a mission point , Drones for data collection The flight altitude is set to minimize the flight distance of the data collection UAV formation in the next round of missions. The model is as follows:

[0067] ;Formula (13);

[0068] ;Formula (14);

[0069] in, , is the penalty variable, It ensures that the task point is only selected once. When you first select , when you select again ;

[0070] Step S7.4: Get the data collection drone After the initial position, the data collection drone formation coordinated to reach the corresponding mission area by adjusting the flight speed.

[0071] Furthermore, the step S8: the data collection drone enters the corresponding mission area, senses the amount of data carried by the wireless sensor node, and performs data-driven data collection position adjustment to reduce the energy consumption of the wireless sensor node; specifically as follows:

[0072] Step S8.1: Data collection drone data perception: Get each data collection drone After the mission area information, data collection drone Fly to the designated mission area center ; Broadcast its own location information, wireless sensor nodes After receiving the broadcast, its location information, remaining energy and the amount of data that needs to be sent Packed and sent to data collection drone , data collection drone The number of wireless sensor nodes in the area is recorded as ;

[0073] Step S8.2: When the data collection drone and wireless sensor nodes The distance between When the communication energy consumption The calculation is as follows:

[0074] ;Formula (15);

[0075] in, Respectively represent the energy consumption of data sending and data receiving; Represents a wireless sensor node The amount of data; Indicates the working energy consumption of the communication module, Aggregate energy consumption for data; They represent the energy consumption required to amplify the signal, which depends on the transmission and reception distance and the bit error rate;

[0076] Step S8.3: Wireless sensor nodes The remaining energy and communication energy consumption are normalized to obtain the normalized remaining energy And normalized communication energy consumption Values:

[0077] ;Formula (16);

[0078] in, ; , , , Respectively Wireless sensor network nodes The highest remaining energy value, the lowest remaining energy value, the highest communication energy consumption, and the lowest communication energy consumption;

[0079] Step S8.4: Establish During the mission, data collection drones In the communication coverage area, the number of When collecting data from wireless sensor nodes, the total cost for:

[0080] ;Formula (17);

[0081] Data collection drones The optimization adjustment of data collection location is attributed to the wireless sensor node The amount of data carried and its distribution to find an optimal data collection location , so that the sum of the residual energy values ​​of all wireless sensor nodes in the area is maximized. The objective function and constraints are as follows:

[0082] ;Formula (18);

[0083] ;Formula (19);

[0084] Among them, formula (19) ensures that the data collection drone After the position adjustment, it can still ensure that all wireless sensor nodes in the area Coverage; Formula (18) and Formula (19) are linear programming problems, which can be Convert it into a minimization problem;

[0085] Step S8.5: Get the optimal data collection position After that, the data collection drone Make position adjustments and start data collection.

[0086] Furthermore, in step S9, the communication UAV dynamically adjusts its position according to the position of the data collection UAV formation to improve the data transmission rate;

[0087] Step S9.1: Data Collection Drone Calculate the optimal data collection location Afterwards, the communication drone Upload the corresponding coordinates;

[0088] Step S9.2: Set up a communication drone In the The coordinates in the round task are , at this coordinate, the data collection drone formation to the communication drone The data transmission rate reaches the maximum; Combine formula (1)-formula (3) to obtain the total data transmission reachability rate of the system for:

[0089] ;Formula (20);

[0090] in, , , , Represents data collection drones Maximum transmit power, communication drone and data collection drones Communication channel bandwidth and communication drones Gaussian white noise power at the receiving end; Indicates the reference channel power gain at 1m.

[0091] Step S9.3: Communicate with the drone The optimal location optimization model is:

[0092] ;Formula (21);

[0093] ;Formula (22);

[0094] Formula (21) and Formula (22) represent the search for communication drones. The best location , enabling data collection drones to form a fleet of communication drones The overall data throughput is maximized; the constraints ensure that the communication drone and data collection drones Communication connection;

[0095] Step S9.4: Solve formula (21) and formula (22) to convert the maximized overall data throughput problem into a minimization problem, that is: , the upper and lower bounds of the solution range and the constraints do not change.

[0096] Compared with the prior art, the present invention proposes a data-driven heterogeneous drone swarm-assisted wireless sensor data collection method, which has the following advantages:

[0097] 1. Hierarchical network architecture: A hierarchical network is constructed by using heterogeneous drone formations, including data collection drones and communication drones. The hierarchical design improves data collection efficiency and network coverage. Through relay and amplification and forwarding mechanisms, it ensures stable and efficient transmission of data in large-scale wireless sensor networks.

[0098] 2. Flexible data collection strategy: Based on the differences in location, data volume and energy of wireless sensor nodes, an intelligent data collection strategy is formulated to reduce the energy consumption of node information transmission, balance the energy of network nodes, and extend the service life of the sensor network.

[0099] 3. Dynamic multi-UAV formation collaborative operation allocation strategy: Through collaborative work and reasonable scheduling between UAVs, the problem that a single UAV cannot cope with large-scale wireless sensor networks is solved, and the timeliness and energy efficiency of data collection tasks are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] Figure 1 It is a schematic diagram of the system framework of the present invention.

[0101] Figure 2 It is an implementation flow chart of the present invention.

[0102] Figure 3 It is a schematic diagram of the division of two rounds of task areas based on regular hexagonal coverage according to the present invention.

[0103] Figure 4 It is a schematic diagram of the initial trajectory and track point sequence planning of the communication UAV of the present invention.

[0104] Figure 5 The data collected by the present invention collects the flight routes of the UAV formation and the dynamic adjustment of the positions of the UAVs. DETAILED DESCRIPTION

[0105] The present invention designs a data-driven heterogeneous drone swarm-assisted wireless sensor data collection method, which uses heterogeneous drone formations to realize an efficient hierarchical data collection system. This method optimizes the data collection process of large-scale wireless sensor networks through the hierarchical structure of drone formations, solving the problem that a single drone cannot meet the requirements of large-scale and efficient data collection.

[0106] A data-driven heterogeneous drone swarm-assisted wireless sensor data collection method, as shown in the attached Figure 2 As shown, the method comprises the following steps:

[0107] Step S1: Determine the distribution area and range of wireless sensor nodes, and build a hierarchical data collection system for heterogeneous UAV formations, including data collection UAVs and communication drones ; The details are as follows:

[0108] Step S1.1: Construct a heterogeneous UAV data collection and transmission network; the heterogeneous UAV data collection and transmission network includes two types of UAVs and wireless sensor nodes: the two types of UAVs are Data collection drone And 1 communication drone ; The data collection drone number is ; The number of wireless sensor nodes is , numbered ;

[0109] Step S1.2: The heterogeneous UAV data collection and transmission network is divided into three layers; the first layer is the wireless sensor node layer, which is responsible for data collection; the second layer is the data collection UAV layer, which is responsible for the collection of sensor data in the specified mission area; the third layer is the communication UAV layer, which is responsible for the UAV formation mission planning and acts as a relay, using the airborne radio to transmit the data collected by the data collection UAV to the cloud or base station by amplifying and forwarding.

[0110] Step S2: Identify the data collection drone The communication coverage of wireless sensor nodes is as follows:

[0111] Step S2.1: Calculate the time t when the wireless sensor node With data collection drones Distance , expressed as:

[0112] ;Formula (1);

[0113] in, Represents a data collection drone Height, , For wireless sensor nodes With data collection drones The coordinates of in two-dimensional space;

[0114] Step S2.2: Calculate data collection drone With wireless sensor nodes The channel power gain between , expressed as:

[0115] ;Formula (2);

[0116] in, represents the channel power gain at 1m;

[0117] Step S2.3: Based on the channel power gain Find wireless sensor nodes Uplink transmission rate , expressed as:

[0118] ;Formula (3);

[0119] in, is the channel bandwidth, For wireless sensor nodes The transmission power, Represents a data collection drone Gaussian white noise power at the receiving end;

[0120] Step S2.4: During the data collection process, the wireless sensor nodes Uplink transmission rate Must be greater than or equal to the minimum data transfer rate , that is, satisfy ;

[0121] Step S2.5: According to formula (3), the minimum data transmission rate The constraint is transformed into a distance constraint, expressed as:

[0122] ;Formula (4);

[0123] ;Formula (5);

[0124] in, To meet the uplink transmission rate Constrained wireless sensor nodes With data collection drones The maximum distance between

[0125] Step S2.6: Data Collection Drone The half beam width is used to Directional antennas for wireless sensor nodes For communication, the directional antenna radiates vertically toward the ground;

[0126] Step S2.7: Calculate data collection drone Communication coverage radius and maximum flight altitude , expressed as:

[0127] ;Formula (6);

[0128] ;Formula (7).

[0129] Step S3: According to the communication coverage obtained in step S2, the distribution area of ​​the wireless sensor nodes is divided into the first round of regular hexagonal coverage to form the first layer of cellular coverage structure, i.e., cellular coverage 1, and the center coordinates of all regular hexagonal areas are obtained. , as the mission area of ​​the data collection drone; in the drone-assisted wireless data transmission network, the cellular coverage affects the communication quality and transmission efficiency, as follows:

[0130] Step S3.1: Wireless sensor nodes The distribution area size is x km×y km, and a Cartesian coordinate system is established with the origin at , based on data collection drones Communication coverage radius , calculate the center coordinates of each regular hexagon:

[0131] ;Formula (8);

[0132] Step S3.2: Create a matrix , used to save the center coordinates of each regular hexagon ,but:

[0133] ;Formula (9);

[0134] in, Respectively represent the wireless sensor nodes The distribution area is divided into A regular hexagonal area, Represent the row and column indices of each hexagonal area respectively;

[0135] Step S3.3: According to the center coordinates of the regular hexagon , using data collection drones Communication coverage radius The length of the regular hexagon is calculated, and the vertex coordinates of each regular hexagon are calculated to complete the regular hexagon coverage of the mission area. Each regular hexagon area is a data collection drone. mission area.

[0136] Step S4: Calculate the communication range between the communication UAV and the data collection UAV, further divide the distribution area of ​​the wireless sensor nodes into a second round of regular hexagonal coverage, establish the second layer of cellular coverage structure, i.e., cellular coverage 2, and obtain the initial track point of the communication UAV ; The details are as follows:

[0137] Step S4.1: Input data collection drone Maximum transmit power , communication drones Gaussian white noise power at the receiving end , refer to step S2, formula (1) to formula (5), calculate to ensure the minimum data transmission rate Based on the communication drone With data collection drones Maximum distance , when the communication drone and data collection drones The distance is greater than When the communication connection is lost;

[0138] Step S4.2: Communicate with the drone and data collection drones Independent frequency bands are used between them, and independent omnidirectional antennas are equipped for communication. Coverage radius , and communication drones and data collection drones The maximum height difference between the two is related to the communication between the UAVs. and all data collection drones When the flight altitude is consistent, the communication drone Coverage reaches the maximum, that is, ;

[0139] Step S4.3: Referring to step S3, according to the communication drone Coverage radius , for wireless sensor nodes The distribution area of ​​​​the second round of regular hexagonal coverage is obtained, and the number is A regular hexagonal area, corresponding to the regular hexagon center coordinates , ;

[0140] Step S4.4: Create a matrix , used to save the center coordinates of each regular hexagon obtained from the second round of regular hexagon coverage ,but:

[0141] ;Formula (10);

[0142] Step S4.5: Transform the matrix The center coordinates of each regular hexagon in As a communication drone The initial track point.

[0143] Step S5: Set the initial track point of the communication drone As input, the initial flight path of the communication UAV is optimized to obtain the optimized communication UAV track matrix ; The details are as follows:

[0144] Step S5.1: Transform the matrix Flatten by columns Matrix of size ;

[0145] Step S5.2: Communicate with the UAV The flight path is optimized and the following optimization model is established:

[0146] ;Formula (11);

[0147] ;Formula (12);

[0148] in, Used to mark whether the line between any two initial track points is planned to the communication drone within the flight path of Represents the Kth initial track point and the Lth initial track point Link is planned as a communication drone flight path, otherwise ; Formula (11) and Formula (12) represent the matrix Sort the centers of the inner regular hexagons to get a new matrix , communication drone The new matrix The initial track point in the path is taken as the path point, and the new matrix When flying in sequence, the total flight distance is the shortest.

[0149] Step S6: According to the track matrix The sequence of internal track points determines each communicating drone one by one The center coordinate information of the data collection drone mission area contained in the communication coverage area is as follows:

[0150] Step S6.1: The data transmission power of the UAV is usually several times or even dozens of times that of the wireless sensor node, so the communication UAV Coverage radius Bigger than a data collection drone Communication coverage radius ,but Therefore, in the communication drone The corresponding coordinates of the center of the regular hexagon A regular hexagon centered It includes multiple data collection drones Coverage area divided by regular hexagon center coordinates A regular hexagon centered ;

[0151] Step S6.2: Follow the communication drone The flight sequence of the flight path points, i.e. the track matrix , determine the communication drone No. mission area Data collection drones included Coverage area divided by regular hexagon center coordinates A regular hexagon centered , and create the matrix ,storage The corresponding regular hexagon center coordinates .

[0152] Step S7: According to the track matrix of the communication drone , to carry out dynamic task allocation of data drone formation under the guidance of communication drone; the details are as follows:

[0153] Step S7.1: Introduce the concept of task rounds and initialize task rounds ; Data collection drone formation completes wireless sensor nodes in the specified area Data is collected once, ;

[0154] Step S7.2: Create a task library matrix , used to save the During the mission, the data collection drone Optional task area center coordinates, initialize the task library matrix is an empty set; among them, the task library matrix It changes dynamically. In each round of tasks, the task library matrix The number of internal mission points needs to be greater than or equal to the number of data collection drones The number of; if the task library matrix The dimension is , then it is necessary to satisfy ; After the corresponding task point is selected, from the task library matrix Delete in; when , indicating that a new task point needs to be added, that is, ;

[0155] Step S7.3: Establish the Round data collection UAV formation task allocation model; that is, in the task library matrix Inside, based on data collection drones ( )'s current location , for each data collection drone Find a mission point , Drones for data collection The flight altitude is set to minimize the flight distance of the data collection UAV formation in the next round of missions. The model is as follows:

[0156] ;Formula (13);

[0157] ;Formula (14);

[0158] in, , is the penalty variable, It ensures that the task point is only selected once. When you first select , when you select again ;

[0159] Step S7.4: Get the data collection drone After the initial position, the data collection drone formation coordinated to reach the corresponding mission area by adjusting the flight speed.

[0160] Step S8: The data collection drone enters the corresponding mission area, senses the amount of data carried by the wireless sensor nodes, and performs data-driven data collection position adjustment to reduce the energy consumption of the wireless sensor nodes; the details are as follows:

[0161] Step S8.1: Data collection drone data perception: Get each data collection drone After the mission area information, data collection drone Fly to the designated mission area center ; Broadcast its own location information, wireless sensor nodes After receiving the broadcast, its location information, remaining energy and the amount of data that needs to be sent Packed and sent to data collection drone , data collection drone The number of wireless sensor nodes in the area is recorded as ;

[0162] Step S8.2: When the data collection drone and wireless sensor nodes The distance between When the communication energy consumption The calculation is as follows:

[0163] ;Formula (15);

[0164] in, Respectively represent the energy consumption of data sending and data receiving; Represents a wireless sensor node The amount of data; Indicates the working energy consumption of the communication module, Aggregate energy consumption for data; They represent the energy consumption required to amplify the signal, which depends on the transmission and reception distance and the bit error rate;

[0165] Step S8.3: Wireless sensor nodes The remaining energy and communication energy consumption are normalized to obtain the normalized remaining energy And normalized communication energy consumption Values:

[0166] ;Formula (16);

[0167] in, ; , , , Respectively Wireless sensor network nodes The highest remaining energy value, the lowest remaining energy value, the highest communication energy consumption, and the lowest communication energy consumption;

[0168] Step S8.4: Establish During the mission, data collection drones In the communication coverage area, the number of When collecting data from wireless sensor nodes, the total cost for:

[0169] ;Formula (17);

[0170] Data collection drones The optimization adjustment of data collection location is attributed to the wireless sensor node The amount of data carried and its distribution to find an optimal data collection location , so that the sum of the residual energy values ​​of all wireless sensor nodes in the area is maximized. The objective function and constraints are as follows:

[0171] ;Formula (18);

[0172] ;Formula (19);

[0173] Among them, formula (19) ensures that the data collection drone After the position adjustment, it can still ensure that all wireless sensor nodes in the area Coverage; Formula (18) and Formula (19) are linear programming problems, which can be Convert it into a minimization problem;

[0174] Step S8.5: Get the optimal data collection position After that, the data collection drone Make position adjustments and start data collection.

[0175] Step S9: the communication UAV dynamically adjusts its position according to the position of the data collection UAV formation to improve the data transmission rate;

[0176] Step S9.1: Data Collection Drone Calculate the optimal data collection location Afterwards, the communication drone Upload the corresponding coordinates;

[0177] Step S9.2: Set up a communication drone In the The coordinates in the round task are , at this coordinate, the data collection drone formation to the communication drone The data transmission rate reaches the maximum; Combine formula (1)-formula (3) to obtain the total data transmission reachability rate of the system for:

[0178] ;Formula (20);

[0179] in, , , , Represents data collection drones Maximum transmit power, communication drone and data collection drones Communication channel bandwidth and communication drones Gaussian white noise power at the receiving end; Indicates the reference channel power gain at 1m.

[0180] Step S9.3: Communicate with the drone The optimal location optimization model is:

[0181] ;Formula (21);

[0182] ;Formula (22);

[0183] Formula (21) and Formula (22) represent the search for communication drones. The best location , enabling data collection drones to form a fleet of communication drones The overall data throughput is maximized; the constraints ensure that the communication drone and data collection drones Communication connection;

[0184] Step S9.4: Solve formula (21) and formula (22) to convert the maximized overall data throughput problem into a minimization problem, that is: , the upper and lower bounds of the solution range and the constraints do not change.

[0185] Step S10: Determine whether the data collection of all wireless sensor nodes is completed. If so, loop through steps S7 to S10 to perform the next round of tasks; if not, end the task.

[0186] Example

[0187] The present invention is simulated and verified as follows:

[0188] A simulation of a data-driven heterogeneous drone swarm-assisted wireless sensor data collection method includes the following steps:

[0189] Step S1: Input relevant parameters, determine the distribution area and range of wireless sensor nodes, and build a hierarchical data collection system for heterogeneous UAV formations. Specifically, randomly generate 400 wireless sensor nodes within a range of 1km×1km, randomly generate the size of the data packet for each wireless sensor node, set the maximum transmission power of the wireless sensor node and the UAV communication module to 30dBm and 33dBm respectively, the noise power of the receiving end to -110dBm, the flight altitude range of the UAV to [10,300] / m, the communication bandwidth to 1MHz, and the working energy consumption of the communication module to , data aggregation energy consumption The energy consumption required to amplify the signal is , , interior point algorithm convergence parameter ,The number of data collection drones is 3;

[0190] Step S2: Identify the data collection drone Communication coverage of wireless sensor nodes;

[0191] Step S3: According to the communication coverage obtained in step S2, the first round of regular hexagonal coverage is performed on the distribution area of ​​the wireless sensor nodes to obtain the center coordinates of all regular hexagonal areas. , as the mission area for data collection drones;

[0192] Step S4: Calculate the communication range between the communication UAV and the data collection UAV, and further perform a second round of regular hexagonal coverage on the distribution area of ​​the wireless sensor nodes to obtain the initial track point of the communication UAV ;

[0193] Step S5: Connect the communication drone The initial track point As input, the communication drone The initial flight path is optimized to obtain the optimized communication UAV track matrix ;

[0194] Step S6: According to the track matrix The sequence of internal track points determines each communicating drone one by one The center coordinate information of the data collection UAV mission area contained in the communication coverage area;

[0195] Step S7: According to the track matrix of the communication drone , to carry out dynamic task allocation of data drone formation under the guidance of communication drone;

[0196] Step S8: Data Collection Drone Enter the corresponding task area, sense the amount of data carried by the wireless sensor nodes, and adjust the data collection position under data-driven conditions to reduce the energy consumption of the wireless sensor nodes;

[0197] Step S9: the communication UAV dynamically adjusts its position according to the position of the data collection UAV formation to improve the data transmission rate;

[0198] Step S10: Determine whether the data collection of all wireless sensor nodes is completed. If so, loop through steps S7 to S10 to perform the next round of tasks; if not, end the task.

[0199] According to the above steps, the flight trajectories of the communication UAV and the data collection UAV formation, as well as the changes in the data collection position are obtained as shown in the attached figure. Figure 5 shown.

[0200] From the above results, it can be seen that the method of the present invention can realize the optimization of task allocation and data collection location of heterogeneous UAV formations, which is of great significance for large-scale sensor network data collection, reducing the energy consumption of wireless sensor nodes, and improving the life of wireless sensor nodes.

[0201] In the description of the present invention, it is necessary to understand that the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0202] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A data-driven heterogeneous drone swarm assisted wireless sensor data collection method, characterized by: The method comprises the following steps: Step S1: Determine the distribution area and range of wireless sensor nodes, and build a hierarchical data collection system for heterogeneous UAV formations, including data collection UAVs and communication drones ; Step S2: Identify the data collection drone Communication coverage of wireless sensor nodes; Step S3: According to the communication coverage obtained in step S2, the distribution area of ​​the wireless sensor nodes is divided into the first round of regular hexagonal coverage to form the first layer of cellular coverage structure, i.e., cellular coverage 1, and the center coordinates of all regular hexagonal areas are obtained. , as the mission area for data collection drones; Step S4: Calculate the communication range between the communication UAV and the data collection UAV, further divide the distribution area of ​​the wireless sensor nodes into a second round of regular hexagonal coverage, establish the second layer of cellular coverage structure, i.e., cellular coverage 2, and obtain the initial track point of the communication UAV ; Step S5: Set the initial track point of the communication drone As input, the initial flight path of the communication UAV is optimized to obtain the optimized communication UAV track matrix ; Step S6: According to the track matrix The sequence of internal track points determines each communicating drone one by one The center coordinate information of the data collection UAV mission area contained in the communication coverage area; Step S7: According to the track matrix of the communication drone , to carry out dynamic task allocation of data drone formation under the guidance of communication drone; Step S8: The data collection drone enters the corresponding mission area, senses the amount of data carried by the wireless sensor nodes, and performs data-driven data collection position adjustment to reduce the energy consumption of the wireless sensor nodes; Step S9: the communication UAV dynamically adjusts its position according to the position of the data collection UAV formation to improve the data transmission rate; Step S10: Determine whether data collection of all wireless sensor nodes is completed; if so, loop through steps S7 to S10 to perform the next round of tasks; if not, end the task.

2. According to claim 1, a data-driven heterogeneous drone swarm assisted wireless sensor data collection method is characterized by: Step S1: Determine the distribution area and range of wireless sensor nodes, and construct a hierarchical data collection system for heterogeneous UAV formations, including data collection UAVs and communication drones ; The details are as follows: Step S1.1: Construct a heterogeneous UAV data collection and transmission network; the heterogeneous UAV data collection and transmission network includes two types of UAVs and wireless sensor nodes: the two types of UAVs are Data collection drone And 1 communication drone ; The data collection drone is numbered ; The number of wireless sensor nodes is , numbered ; Step S1.2: The heterogeneous UAV data collection and transmission network is divided into three layers; the first layer is the wireless sensor node layer, which is responsible for data collection; The second layer is the data collection drone layer, which is responsible for collecting sensor data in the designated mission area; the third layer is the communication drone layer, which is responsible for drone formation mission planning and also acts as a relay, using the onboard radio to transmit the data collected by the data collection drone to the cloud or base station by amplifying and forwarding.

3. The data-driven heterogeneous drone swarm-assisted wireless sensor data collection method according to claim 2 is characterized by: Step S2: Determine the data collection drone The communication coverage of wireless sensor nodes is as follows: Step S2.1: Calculate the time t when the wireless sensor node With data collection drones Distance , expressed as: Formula (1) in, Represents a data collection drone Height, , For wireless sensor nodes With data collection drones The coordinates of in two-dimensional space; Step S2.2: Calculate data collection drone With wireless sensor nodes The channel power gain between , expressed as: Formula (2) in, represents the channel power gain at 1m; Step S2.3: Based on the channel power gain Find wireless sensor nodes Uplink transmission rate , expressed as: Formula (3) in, is the channel bandwidth, For wireless sensor nodes The transmission power, Represents a data collection drone Gaussian white noise power at the receiving end; Step S2.4: During the data collection process, the wireless sensor nodes Uplink transmission rate Must be greater than or equal to the minimum data transfer rate , that is, satisfy ; Step S2.5: According to formula (3), the minimum data transmission rate The constraint is transformed into a distance constraint, expressed as: Formula (4) Formula (5) in, To meet the uplink transmission rate Constrained wireless sensor nodes With data collection drones The maximum distance between Step S2.6: Data Collection Drone The half beam width is used to Directional antennas for wireless sensor nodes For communication, the directional antenna radiates vertically toward the ground; Step S2.7: Calculate data collection drone Communication coverage radius and maximum flight altitude , expressed as: Formula (6) ;Official(7).

4. The data-driven heterogeneous drone swarm assisted wireless sensor data collection method according to claim 3 is characterized by: Step S3: According to the communication coverage obtained in step S2, the distribution area of ​​the wireless sensor nodes is divided into the first round of regular hexagonal coverage to form the first layer of cellular coverage structure, i.e., cellular coverage 1, and the center coordinates of all regular hexagonal areas are obtained. , as the mission area for data collection drones; details are as follows: Step S3.1: Wireless sensor nodes The distribution area size is x km×y km, and a Cartesian coordinate system is established with the origin at , based on data collection drones Communication coverage radius , calculate the coordinates of the center of each regular hexagon: Formula (8) Step S3.2: Create a matrix , used to save the center coordinates of each regular hexagon ,but: Formula (9) in, Respectively represent the wireless sensor nodes The distribution area is divided into A regular hexagonal area, Represent the row index and column index of each hexagonal area respectively; Step S3.3: According to the center coordinates of the regular hexagon , using data collection drones Communication coverage radius The length of the regular hexagon is calculated, and the vertex coordinates of each regular hexagon are calculated to complete the regular hexagon coverage of the mission area. Each regular hexagon area is a data collection drone. mission area.

5. The data-driven heterogeneous drone swarm assisted wireless sensor data collection method according to claim 4 is characterized by: Step S4: Calculate the communication range between the communication UAV and the data collection UAV, further divide the distribution area of ​​the wireless sensor nodes into a second round of regular hexagonal coverage, establish a second layer of cellular coverage structure, i.e., cellular coverage 2, and obtain the initial track point of the communication UAV ; The details are as follows: Step S4.1: Input data collection drone Maximum transmit power , communication drones Gaussian white noise power at the receiving end , refer to step S2, formula (1) to formula (5), calculate to ensure the minimum data transmission rate Based on the communication drone With data collection drones Maximum distance , when the communication drone and data collection drones The distance is greater than When the communication connection is lost; Step S4.2: Communicate with the drone and data collection drones Independent frequency bands are used between them, and independent omnidirectional antennas are equipped for communication. Coverage radius , and communication drones and data collection drones When the communication UAV and all data collection drones When the flight altitude is consistent, the communication drone Coverage reaches the maximum, that is, ; Step S4.3: Referring to step S3, according to the communication drone Coverage radius , for wireless sensor nodes The distribution area of ​​​​the second round of regular hexagonal coverage is obtained, and the number is A regular hexagonal area, corresponding to the regular hexagon center coordinates , ; Step S4.4: Create a matrix , used to save the center coordinates of each regular hexagon obtained from the second round of regular hexagon coverage ,but: Formula (10) Step S4.5: Transform the matrix The center coordinates of each regular hexagon in As a communication drone The initial track point.

6. The data-driven heterogeneous drone swarm assisted wireless sensor data collection method according to claim 5, characterized in that: Step S5: Set the initial track point of the communication drone As input, the initial flight path of the communication UAV is optimized to obtain the optimized communication UAV track matrix ; The details are as follows: Step S5.1: Transform the matrix Flatten by columns Matrix of size ; Step S5.2: Communicate with the UAV The flight path is optimized and the following optimization model is established: ;Formula (11); ;Formula (12); in, Used to mark whether the line between any two initial track points is planned to the communication drone within the flight path of Represents the Kth initial track point and the Lth initial track point Link is planned as a communication drone flight path, otherwise ; Formula (11) and Formula (12) represent the matrix Sort the centers of the inner regular hexagons to get a new matrix , communication drone The new matrix The initial track point in the path is taken as the path point, and the new matrix When flying in sequence, the total flight distance is the shortest.

7. The data-driven heterogeneous drone swarm assisted wireless sensor data collection method according to claim 6, characterized in that: Step S6: according to the track matrix The sequence of internal track points determines each communicating drone one by one The center coordinate information of the data collection drone mission area contained in the communication coverage area is as follows: Step S6.1: The data transmission power of the UAV is usually several times or even dozens of times that of the wireless sensor node, so the communication UAV Coverage radius Bigger than a data collection drone Communication coverage radius ,but ; Therefore, in communication drones The corresponding coordinates of the center of the regular hexagon A regular hexagon centered It includes multiple data collection drones Coverage area divided by regular hexagon center coordinates A regular hexagon centered ; Step S6.2: Follow the communication drone The flight sequence of the flight path points, i.e. the track matrix , determine the communication drone No. mission area Data collection drones included Coverage area divided by regular hexagon center coordinates A regular hexagon centered , and create the matrix ,storage The corresponding regular hexagon center coordinates .

8. The data-driven heterogeneous drone swarm assisted wireless sensor data collection method according to claim 7, characterized in that: Step S7: according to the track matrix of the communication drone , to carry out dynamic task allocation of data drone formation under the guidance of communication drone; the details are as follows: Step S7.1: Introduce the concept of task rounds and initialize task rounds ; Data collection drone formation completes wireless sensor nodes in the specified area Data is collected once, ; Step S7.2: Create a task library matrix , used to save the During the mission, the data collection drone Optional task area center coordinates, initialize the task library matrix is an empty set; among them, the task library matrix It changes dynamically. In each round of tasks, the task library matrix The number of internal mission points needs to be greater than or equal to the number of data collection drones The number of; if the task library matrix The dimension is , then it is necessary to satisfy ; After the corresponding task point is selected, from the task library matrix Delete in; when , indicating that a new task point needs to be added, that is, ; Step S7.3: Establish the Round data collection UAV formation task allocation model; that is, in the task library matrix Inside, based on data collection drones ( )'s current location , for each data collection drone Find a mission point , Drones for data collection The flight altitude is set to minimize the flight distance of the data collection UAV formation in the next round of missions. The model is as follows: ;Formula (13); ;Formula (14) ; in, , is the penalty variable, It ensures that the task point is only selected once. When you first select , when selected again ; Step S7.4: Get the data collection drone After the initial position, the data collection drone formation coordinated to reach the corresponding mission area by adjusting the flight speed.

9. The data-driven heterogeneous drone swarm assisted wireless sensor data collection method according to claim 8, characterized in that: The step S8: the data collection drone enters the corresponding task area, senses the amount of data carried by the wireless sensor node, and adjusts the data collection position under data drive to reduce the energy consumption of the wireless sensor node; the details are as follows: Step S8.1: Data collection drone data perception: Get each data collection drone After the mission area information, the data is collected by the drone Fly to the designated mission area center ; Wireless sensor nodes broadcast their own location information After receiving the broadcast, its location information, remaining energy and the amount of data that needs to be sent Packaged and sent to data collection drone , data collection drone The number of wireless sensor nodes in the area is recorded as ; Step S8.2: When the data collection drone and wireless sensor nodes The distance between When the communication energy consumption The calculation is as follows: ;Formula (15) ; in, They represent the energy consumption of data sending and data receiving respectively; Represents a wireless sensor node The amount of data; Indicates the working energy consumption of the communication module, Aggregate energy consumption for data; They represent the energy consumption required to amplify the signal, which depends on the transmission and reception distance and the bit error rate; Step S8.3: Wireless sensor nodes The remaining energy and communication energy consumption are normalized to obtain the normalized remaining energy And normalized communication energy consumption Values: ;Formula (16); in, ; , , , Respectively Wireless sensor network nodes The highest remaining energy value, the lowest remaining energy value, the highest communication energy consumption, and the lowest communication energy consumption; Step S8.4: Establish During the mission, data collection drones In the communication coverage area, the number of When collecting data from wireless sensor nodes, the total cost for: ;Formula (17); Data collection drones The optimization adjustment of data collection location is attributed to the wireless sensor node The amount of data carried and its distribution to find an optimal data collection location , so that the sum of the residual energy values ​​of all wireless sensor nodes in the area is maximized. The objective function and constraints are as follows: ;Formula (18); ;Formula (19); Among them, formula (19) ensures that the data collection drone After the position adjustment, it can still ensure that all wireless sensor nodes in the area Coverage; Formula (18) and Formula (19) are linear programming problems, which can be Convert it into a minimization problem; Step S8.5: Obtaining the optimal data collection position After that, the data collection drone Make position adjustments and start data collection.

10. The data-driven heterogeneous drone swarm assisted wireless sensor data collection method according to claim 9, characterized in that: Step S9: the communication drone dynamically adjusts its position according to the position of the data collection drone formation to increase the data transmission rate; Step S9.1: Data Collection Drone Calculate the optimal data collection location Afterwards, the communication drone Upload the corresponding coordinates; Step S9.2: Set up a communication drone In the The coordinates in the round task are , at this coordinate, the data collection drone formation to the communication drone The data transmission rate reaches the maximum; Combine formula (1)-formula (3) to obtain the total data transmission reachability rate of the system for: ;Formula (20); in, , , , Represents data collection drones Maximum transmit power, communication drone and data collection drones Communication channel bandwidth and communication drones Gaussian white noise power at the receiving end; represents the reference channel power gain at 1m; Step S9.3: Communicate with the drone The optimal location optimization model is: ； Formula (21); ;Formula (22); Formula (21) and Formula (22) represent the search for communication drones. The best location , enabling data collection drones to form a fleet of communication drones The overall data throughput is maximized; the constraints ensure that the communication drone and data collection drones Communication connection; Step S9.4: Solve formula (21) and formula (22) to convert the maximized overall data throughput problem into a minimization problem, that is: , the upper and lower bounds of the solution range and the constraints do not change.

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