Communication relay unmanned aerial vehicle dynamic positioning method based on multi-node cooperative labeling

Abstract

The invention particularly relates to a communication relay unmanned aerial vehicle dynamic positioning method based on multi-node cooperative labeling. The method comprises the following steps: S1, constructing a self-organizing network comprising an unmanned aerial vehicle node and a plurality of network nodes; s2, marking candidate landing points on the moving route by the network node; s3, the unmanned aerial vehicle node calculates the distance from the position of each candidate landing point to each one-hop node, and a distance-loss pair is obtained by combining link propagation loss; s4, judging whether to execute lift-off deployment or landing deployment; s5, carrying out lift-off deployment: selecting an air positioning point which can cover all network nodes needing to be covered and meets the air-ground communication distance requirement; s6, landing deployment: screening a landing positioning point which meets a search distance requirement and is combined with a distance-loss pair information table to select a distance-loss pair optimal landing positioning point from all candidate landing points; and S7, alternately realizing lift-off deployment and landing deployment of the unmanned aerial vehicle nodes. According to the invention, the reliability, the real operability and the communication efficiency of the self-organizing network can be improved.

Description

Technical Field

[0001] The present invention relates to the field of self-organizing networks and unmanned aerial vehicle (UAV) relay technologies, and in particular to a method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling. Background Art

[0002] Self-organizing networks (abbreviated as MANETs) are widely used in scenarios without infrastructure and emergency rescue. They have the characteristics of being decentralized, self-organizing, and self-healing. Through wireless packet multi-hop relay forwarding, they enhance the flexibility of network application.

[0003] However, in complex application scenarios, such as urban streets and mountainous terrain, wireless transmission is restricted by terrain and objects, severely impacting link availability. Therefore, the use of drone communication relay nodes in the network significantly improves network connectivity through high-probability line-of-sight air-to-ground transmission. In particular, relay communication nodes based on untethered rotorcraft platforms have attracted widespread attention due to their unique advantages of lightweight, fast mobility, and limited terrain constraints.

[0004] Typical rotary-wing drones are limited by size, weight, and power consumption (SWAP). Generally, their flight time is very short (e.g., within 1 hour), which is insufficient to provide long-term continuous wireless network coverage. They often require manual battery replacement or charging by landing, or rotation among multiple drones. This increases the complexity of drone communication relay applications and limits their application scenarios.

[0005] Furthermore, many researchers have highlighted energy consumption limitations and proposed solutions, such as optimizing drone movement paths and reducing the transmit power of onboard communication equipment. However, these solutions are insufficient for achieving sustainable networking in real-world applications, as the primary energy consumption of drone communication nodes is the power required to support flight. While charging mechanisms such as solar energy, lasers, and wireless power transmission have been proposed, their efficiency and practicality require further study, and their suitability for complex real-world applications remains uncertain.

[0006] In order to solve the problem of sustainable application of drone communication relay nodes in self-organizing network applications in complex scenarios, the applicant came up with the idea of ​​designing a solution that combines intermittent landing deployment and on-demand driven launch deployment to dynamically optimize drone positioning points, and integrate it into the networking protocol design, which has comprehensive advantages in terms of both the efficiency of drone communication relay and sustainable application. Summary of the Invention

[0007] In view of the above-mentioned deficiencies in the existing technology, the technical problem to be solved by the present invention is: how to provide a dynamic positioning method for communication relay drones based on multi-node collaborative labeling, dynamically optimizing landing positioning points through a combination of intermittent landing deployment and on-demand driven aerial deployment, while both the aerial positioning points and the landing positioning points can be dynamically adjusted as the network nodes move, thereby improving the reliability, practical operability and communication efficiency of the self-organizing network.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0009] The dynamic positioning method of communication relay UAV based on multi-node collaborative labeling includes:

[0010] S1: Build a self-organizing network consisting of a drone node and several network nodes;

[0011] S2: Each network node moves as needed and marks candidate landing points on the movement route. Each network node obtains the ID of the one-hop node whose distance from the candidate landing point exceeds the threshold d1 and the corresponding link propagation loss, and generates annotation information.

[0012] S3: The drone node receives the annotation information of all network nodes, calculates the distance from each candidate landing point to each one-hop node, combines the link propagation loss to obtain the distance-loss pair, and constructs the distance-loss pair information table of the candidate landing points;

[0013] S4: Determine whether to perform lift-off deployment or landing deployment based on the network connectivity and service requirements of the self-organizing network: if lift-off deployment is performed, execute step S5; if landing deployment is performed, execute step S6;

[0014] S5: Aerial deployment: Select an aerial positioning point that can cover all the network nodes that need to be covered and meet the air-to-ground communication distance requirements, and control the drone node to move to the aerial positioning point to communicate with the network nodes that need to be covered;

[0015] S6: Landing deployment: Filter all candidate landing points to meet the search distance requirements and select the landing positioning point with the best distance-loss pair based on the distance-loss pair information table, control the UAV node to move to the landing positioning point and communicate with the network node;

[0016] S7: Repeat steps S4 to S6 to alternately implement the launch deployment and landing deployment of the drone node.

[0017] Preferably, in step S3, the drone node modifies the distance-loss pair information table according to the current connected network topology and the connection node location. The specific steps are as follows:

[0018] S301: Obtain the maximum distance D from the distance-loss pair information table of the candidate landing points max ;

[0019] The formula is:

[0020] D max =max{D 1,1 ,D 1,2 ,…,D 2,1 ,D 2,2 ,D 2,3 ,…,D 3,1 ,…};

[0021] S302: Traverse all candidate landing points and determine whether there is a network node P among the non-one-hop nodes of candidate landing point i. j Satisfied: P j The distance to candidate landing point i is D i,j And d1≤D i,j ≤D max If so, then for candidate landing point i, (D i,j ,L th ), where L th is the maximum loss allowed for communication between nodes;

[0022] S303: Complete the update of the distance-loss pair information table.

[0023] Preferably, in step S4, if the network connectivity does not meet the standard, then the lift-off deployment is performed; if the service flow weakens or the node connectivity meets the standard during a specific period, then the landing deployment is performed.

[0024] Preferably, in step S5, when deployed in the air, the network nodes that the drone node needs to cover are P1, P2, ..., P k , then the aerial positioning point is obtained by solving the following first model:

[0025] The formula of the first model is expressed as:

[0026] min|P air -P G |;

[0027] st|P air -P i |≤R0,i=1,2,…,k;

[0028] Where: P air Indicates an aerial positioning point; P G Indicates the current position of the drone node; P i Indicates the network nodes that the drone node needs to cover; R0 indicates the reference value of the air-to-ground communication distance.

[0029] Preferably, in step S5, the air-to-ground communication distance reference value is determined by the following steps:

[0030] S501: Given an initial value r0 of the air-to-ground communication distance reference value R0, set the distance reference weight μ;

[0031] S502: When implementing the zth aerial deployment, if the number of one-hop nodes of the drone node is m, and the distance from the drone node to each one-hop node is Then calculate the distance mean r z ;

[0032] The formula is:

[0033]

[0034] S503: After the zth aerial deployment is completed, the air-to-ground communication distance reference value R0 is updated based on the previous records;

[0035] The formula is:

[0036]

[0037] Preferably, in step S5, if the distance between the aerial positioning point and the current position of the drone node is so great that the drone node cannot travel back and forth, the deployment is abandoned.

[0038] Preferably, in step S6, the landing deployment processing steps include:

[0039] S601: Taking the current aerial positioning point of the UAV node as the origin, obtain a set A of candidate landing points within the search distance S;

[0040] The formula is:

[0041]

[0042] Where: G n Indicates the search for the nth candidate landing point within the distance S;

[0043] S602: If the number of elements in the candidate landing point set A is 1, the corresponding candidate landing point is the landing positioning point; if the number of elements in the candidate landing point set A is greater than 1, execute step S603; if the number of elements in the candidate landing point set A is 0, execute step S604;

[0044] S603: Calculate the distance attenuation factor of each candidate landing point based on the distance-loss pair information table of the candidate landing points, and select the candidate landing point with the smallest distance attenuation factor as the landing positioning point;

[0045] S604: Extend the search distance S=S+Δs, and return to step S601; where Δs represents the exploration step length.

[0046] Preferably, in step S603, the distance attenuation factor of the candidate landing point is calculated by the following steps:

[0047] S6031: For candidate landing point G n ∈A, according to the distance-loss information table (D n,1 ,L n,1 ),(D n,2 ,L n,2 ),…,(D n,p ,L n,p ) ; Convert the distance into logarithmic form and record it as lgD n,1 =g n,1 , then we get (g n,1 ,L n,1 ),(g n,2 ,L n,2 ),…,(g n,p ,L n,p );

[0048] S6032: Assume that the distance attenuation factor of the distance-loss pair is α n , then the candidate landing point G n The corresponding α n The following second model is satisfied;

[0049] The formula of the second model is expressed as:

[0050] min∑ i＝1,2,…,p (g n,i α n -L n,i ) 2 ;

[0051] S6033: Solve the second model to obtain the candidate landing point G n The distance attenuation factor is α n ;

[0052] The formula is:

[0053]

[0054] Preferably, in step S603, the candidate landing point G is updated by the following formula: n Distance decay factor:

[0055]

[0056] Where: α' n Represents the updated distance attenuation factor; α thIndicates the set threshold value.

[0057] Preferably, the updated distance attenuation factor α' n Sort them and use the candidate landing point corresponding to the smallest distance attenuation factor as the landing positioning point.

[0058] Compared with the existing technology, the dynamic positioning method of the communication relay UAV based on multi-node collaborative labeling in the present invention has the following beneficial effects:

[0059] The present invention combines intermittent landing deployment with on-demand driven aerial deployment, which can dynamically optimize landing positioning points (such as the top of a mountain, the top of a building, flat high ground, relatively high points, etc.), supporting the maximum relay communication function when the drone is deployed; when the business or network is urgently needed, through autonomous decision-making or manual control, the drone node is driven to take off immediately and be deployed at the nearest aerial positioning point, changing the traditional continuous hovering deployment method, greatly reducing the energy consumption of the drone platform, and significantly increasing the deployment time of the drone relay communication node.

[0060] The present invention proposes a multi-node collaborative labeling method to construct a set of candidate landing points. Each node determines its current location and calculates the single-hop link distance and loss. It then labels the location where the drone is suitable for landing and shares the location and link information with the drone node. When the drone node needs to land and deploy from an aerial positioning point, it can select the landing point based on the current aerial positioning point and the set of candidate landing points and execute the landing deployment. The drone node's communication equipment can continue to play a communication relay role. At the same time, both the aerial positioning point and the landing positioning point can be dynamically adjusted as the network node moves. The landing positioning point is determined and measured locally by each node and shared interactively through a protocol. Compared with traditional long-distance image recognition landing point recognition in complex scenarios, it has higher reliability and practical operability, while also taking into account communication efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to make the purpose, technical solutions and advantages of the invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings, in which:

[0062] Figure 1 This is a flow chart of the dynamic positioning method of communication relay UAV based on multi-node collaborative labeling.

[0063] Figure 2 This is a schematic diagram of the initial positioning point, air positioning point and landing positioning point.

[0064] Figure 3 This is a structural diagram of the labeled message.

[0065] Figure 4 Schematic diagram of terrain occlusion at candidate landing sites.

[0066] Figure 5 Schematic diagram of aerial deployment. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but only represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0068] It should be noted that similar reference numerals and letters denote similar items in the following figures. Therefore, once an item is defined in one figure, it does not require further definition or explanation in subsequent figures. In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer" indicate positions or relationships based on the positions or relationships shown in the figures, or the positions or relationships in which the inventive product is typically placed when in use. These terms are intended solely to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation, and are therefore not to be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third," etc., are used solely to distinguish descriptions and are not to be construed as indicating or implying relative importance. Furthermore, terms such as "horizontal" and "vertical" do not imply that a component is absolutely horizontal or overhanging, but rather may be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but rather may be slightly tilted. In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0069] The following is a further detailed description through specific implementation methods:

[0070] Example:

[0071] This embodiment discloses a dynamic positioning method for a communication relay drone based on multi-node collaborative labeling.

[0072] like Figure 1 As shown in FIG, a dynamic positioning method for a communication relay UAV based on multi-node collaborative labeling includes:

[0073] S1: Build a self-organizing network consisting of a drone node and several network nodes;

[0074] S2: Each network node moves as needed and marks candidate landing points on the movement route. Each network node obtains the ID of the one-hop node whose distance from the candidate landing point exceeds the threshold d1 and the corresponding link propagation loss, and generates annotation information.

[0075] A one-hop node is a node that is one hop away from the current network node, and its location is the same as the candidate landing point. The one-hop node is determined by the network connection status of the network node providing the annotation point information at the time of the annotation point, i.e., the node directly connected to the network node providing the annotation point information. For a network node, if the transmit power of the directly connected node (i.e., the one-hop node) is known, and the node itself can also detect its received power during reception, the link propagation loss is calculated as 10*log(transmit power / receive power), which is expressed in dB.

[0076] In this embodiment, we believe that nodes that are too close to the candidate landing point (within the threshold) have no reference value for calculating the distance attenuation factor of the candidate landing point and should be excluded.

[0077] S3: The drone node receives the annotation information of all network nodes, calculates the distance from each candidate landing point to each one-hop node, combines the link propagation loss to obtain the distance-loss pair, and constructs the distance-loss pair information table of the candidate landing points;

[0078] S4: Determine whether to perform lift-off deployment or landing deployment based on the network connectivity and service requirements of the self-organizing network: if lift-off deployment is performed, execute step S5; if landing deployment is performed, execute step S6;

[0079] In this embodiment, if the network connectivity does not meet the standard, the lift-off deployment is performed; if the service flow weakens or the node connectivity meets the standard during a specific period of time, the landing deployment is performed.

[0080] S5: Aerial deployment: Select an aerial positioning point that can cover all the network nodes that need to be covered and meet the air-to-ground communication distance requirements, and control the drone node to move to the aerial positioning point to communicate with the network nodes that need to be covered;

[0081] S6: Landing deployment: Filter all candidate landing points to meet the search distance requirements and select the landing positioning point with the best distance-loss pair based on the distance-loss pair information table, control the UAV node to move to the landing positioning point and communicate with the network node;

[0082] S7: Repeat steps S4 to S6 to alternately implement the launch deployment and landing deployment of the drone node.

[0083] The present invention combines intermittent landing deployment with on-demand driven aerial deployment, which can dynamically optimize landing positioning points (such as the top of a mountain, the top of a building, flat high ground, relatively high points, etc.), supporting the maximum relay communication function when the drone is deployed; when the business or network is urgently needed, through autonomous decision-making or manual control, the drone node is driven to take off immediately and be deployed at the nearest aerial positioning point, changing the traditional continuous hovering deployment method, greatly reducing the energy consumption of the drone platform, and significantly increasing the deployment time of the drone relay communication node.

[0084] The present invention proposes a multi-node collaborative labeling method to construct a set of candidate landing points. Each node determines its current location and calculates the single-hop link distance and loss. It then labels the location where the drone is suitable for landing and shares the location and link information with the drone node. When the drone node needs to land and deploy from an aerial positioning point, it can select the landing point based on the current aerial positioning point and the set of candidate landing points and execute the landing deployment. The drone node's communication equipment can continue to play a communication relay role. At the same time, both the aerial positioning point and the landing positioning point can be dynamically adjusted as the network node moves. The landing positioning point is determined and measured locally by each node and shared interactively through a protocol. Compared with traditional long-distance image recognition landing point recognition in complex scenarios, it has higher reliability and practical operability, while also taking into account communication efficiency.

[0085] In order to better introduce the technology of the present invention, this embodiment is described through the following parts.

[0086] 1. Basic Description

[0087] 1. The network technology system is an (air-ground) self-organizing network (hereinafter referred to as the self-organizing network), which is configured with one UAV communication relay node. The UAV communication relay node is composed of a small rotary-wing UAV platform equipped with a self-organizing network device. The self-organizing network device is battery-powered. Under normal circumstances, the battery life T1 of the self-organizing network device is much longer than the continuous hovering time T2 of the UAV platform (for example, T1 = 5h, T2 = 50min).

[0088] 2. The flight route of the UAV platform is vertical take-off and landing and horizontal movement. When the UAV relay communication node is deployed in the air, it is set to a predetermined height H0 (e.g., H0 = 300m).

[0089] 3. Each node in the ad hoc network has integrated satellite positioning function and can know its own location. It adopts active routing protocol (table-driven routing) and periodically exchanges routing control messages between nodes. The routing control messages contain location information, network topology of communication connectivity and routing maintenance. Each node can know the location information of other nodes.

[0090] 4. Each node knows the transmit power of other nodes in advance (ad hoc networks generally set node power in advance and assume that the power settings are equal), and can detect the receive power of the adjacent one-hop node, thereby estimating the one-hop node link propagation loss.

[0091] 5. Assume that all nodes (and their owners) are cooperative and friendly with each other, and have the ability to judge whether the current local location is suitable for the landing of a small rotor drone.

[0092] like Figure 2 As shown in the figure, the UAV relay communication node dynamically adjusts between different positioning points based on autonomous decision-making or human control. There are three types of positioning points: initial positioning point, air positioning point and landing positioning point.

[0093] 2. Initial positioning point (stage)

[0094] Network nodes begin to be deployed in the networking area, and each node moves or stays, gradually dispersing.

[0095] 1. The UAV node is in the ground standby state (the communication equipment is turned on and the UAV platform is on standby on the ground). The standby position is the initial positioning point. At the beginning, the distribution range of network nodes is small. The UAV node can perceive the connectivity topology and the location of its connected nodes through routing control messages. That is, in the connected state, the UAV node can obtain the information shown in Table 1 below.

[0096] Table 1

[0097]

[0098] 2. Other nodes disperse as needed. If a node finds that its current location is suitable for landing of a small rotor UAV on the moving route, it will take it as a candidate landing point, mark the point, and obtain all nodes with a distance greater than d1 (e.g. d1 = 50m) and a one-hop node ID and the corresponding link propagation loss through measurement, and send a marking message to the UAV node. The marking message should contain the following elements: Figure 3 shown.

[0099] 3. The drone node receives the annotation messages from other nodes, calculates the distance from the candidate landing point to each one-hop node, and obtains the distance-loss pair information table of each candidate landing point, as shown in Table 2 below. Note that the number of distance-loss pairs for each candidate landing point may not be the same.

[0100] Table 2

[0101]

[0102] Among them, the drone node corrects the distance-loss pair information table according to the current connected network topology and connection node location. The specific steps are as follows:

[0103] S301: Obtain the maximum distance D from the distance-loss pair information table of the candidate landing points max ;

[0104] The formula is:

[0105] D max =max{D 1,1 ,D 1,2 ,…,D 2,1 ,D 2,2 ,D 2,3 ,…,D 3,1 ,…};

[0106] S302: Traverse all candidate landing points and determine whether there is a network node P among the non-one-hop nodes of candidate landing point i. j Satisfied: P j The distance to candidate landing point i is D i,j And d1≤D i,j ≤D max If so, then for candidate landing point i, (D i,j ,L th ), where L th is the maximum loss allowed for inter-node communication; this operation can more completely characterize the terrain occlusion level of the candidate landing point, such as Figure 4 Show.

[0107] In this embodiment, when each network node sends a labeling message at the location of a candidate landing point, it will inform the IDs of all its one-hop nodes and the corresponding link propagation loss. A one-hop node is determined by the network connection status of the network node providing the labeling point information at the labeling point location. This means that the node is directly connected to the network node providing the labeling point information at the time. A non-one-hop node is a node that is not directly connected to the network node providing the labeling point information under the above conditions.

[0108] S303: Complete the update of the distance-loss pair information table.

[0109] For the correction part, not every candidate landing point exists, as shown in Table 3 below.

[0110] Table 3

[0111]

[0112] 3. Aerial Positioning Point (Phase)

[0113] When the UAV node is currently in the ground landing state and the position is P G , if the network connectivity is insufficient (the drone node can sense this state), the drone node makes autonomous decisions or is manually controlled to take off. Assume that the network nodes that the drone node needs to cover are P1, P2, ..., P k , then the aerial positioning point is obtained by solving the following first model:

[0114] The formula of the first model is expressed as:

[0115] min|P air -P G |;

[0116] st|P air -P i |≤R0,i=1,2,…,k;

[0117] Where: P air Indicates an aerial positioning point; P G Indicates the current position of the drone node; P i Indicates the network nodes that the drone node needs to cover; R0 indicates the reference value of the air-to-ground communication distance.

[0118] The reference value of the air-to-ground communication distance is determined by the following steps:

[0119] S501: Given an initial value r0 of the air-to-ground communication distance reference value R0, set the distance reference weight μ (e.g., μ=0.3);

[0120] S502: When implementing the zth aerial deployment, if the number of one-hop nodes of the drone node is m, and the distance from the drone node to each one-hop node is Then calculate the distance mean r z ;

[0121] The formula is:

[0122]

[0123] S503: After the zth aerial deployment is completed, the air-to-ground communication distance reference value R0 is updated based on the previous records;

[0124] The formula is:

[0125]

[0126] When multiple solutions are obtained by solving the first model, any one of the solutions is selected as the aerial positioning point. There are two default conditions in this model: one is to select all nodes to be covered to meet the minimum covering circle condition (that is, the minimum circle radius covering the selected nodes is not greater than R0); the other is if there is |P air -P G |If the distance value is too large and the current drone power consumption cannot make the round trip, the aerial deployment will be abandoned. Figure 5 Show.

[0127] During the entire operation process, including taking off from the initial positioning point or landing positioning point to the airborne positioning point, and providing communication relay at the airborne positioning point, the drone node still receives annotation messages from other ground nodes and continuously updates the information table of the candidate landing point "distance-loss" pairs based on the annotation information.

[0128] 4. Landing Positioning Point (Phase)

[0129] When (business flow weakens or node connectivity is good enough during a specific period), the drone makes autonomous decisions or is manually controlled, and the drone node enters landing deployment, that is, seeks a landing positioning point to ensure that when the drone platform is stationary, the self-organizing network communication equipment it carries still plays the role of communication relay as much as possible. The landing positioning point is the drone node based on the current air positioning point, and is selected from the candidate landing points.

[0130] Specifically, the landing deployment processing steps include:

[0131] S601: Select candidate landing points as close as possible, set the initial search range, take the current aerial positioning point of the UAV node as the origin, and obtain a set A of candidate landing points within the search distance S;

[0132] The formula is:

[0133] This formula is an operation of traversing all candidate landing points, indicating that all candidate landing points that meet this distance constraint constitute a new set A.

[0134] Where: G n Indicates the search for the nth candidate landing point within the distance S;

[0135] S602: If the number of elements in the candidate landing point set A is 1, the corresponding candidate landing point is the landing positioning point; if the number of elements in the candidate landing point set A is greater than 1, execute step S603; if the number of elements in the candidate landing point set A is 0, execute step S604;

[0136] S603: Calculate the distance attenuation factor of each candidate landing point based on the distance-loss pair information table of the candidate landing points, and select the candidate landing point with the smallest distance attenuation factor as the landing positioning point;

[0137] S604: Extend the search distance S=S+Δs, and return to step S601; where Δs represents the exploration step length.

[0138] The distance attenuation factor of the candidate landing point is calculated through the following steps:

[0139] S6031: For candidate landing point G n ∈A, according to the records in the distance-loss pair information table, we can get (D n,1 ,L n,1 ),(D n,2 ,L n,2 ),…,(D n,p ,L n,p ), where D n,1 and L n,1 They represent the first distance and link propagation loss of the nth candidate landing point, that is, the first distance-loss pair; the distances are converted into logarithmic form and recorded as lgD n,1 =g n,1 , then we get (g n,1 ,L n,1 ),(g n,2 ,L n,2 ),…,(g n,p ,L n,p );

[0140] S6032: Assume that the distance attenuation factor of the distance-loss pair is α n , then the candidate landing point G n The corresponding α n The following second model is satisfied;

[0141] The formula of the second model is expressed as:

[0142] min∑ i＝1,2,…,p (g n,i α n -L n,i ) 2 ;

[0143] S6033: Solve the second model to obtain the candidate landing point G n The distance attenuation factor is α n ;

[0144] The formula is:

[0145]

[0146] The selection of candidate landing points is based on two criteria: first, the distance attenuation factor should be as small as possible; second, if a candidate landing point has been used, the new candidate landing point can only be used as the new preferred result if the distance attenuation factor is better than the previous one by more than a certain threshold. th , update the candidate landing point G by the following formula n Distance decay factor:

[0147]

[0148] Where: α' n Represents the updated distance attenuation factor; α th Indicates the set threshold value.

[0149] The updated distance attenuation factor α' n Sort the candidate landing points and select the landing point with the smallest distance attenuation factor as the landing location, as shown in Table 4 below.

[0150] Table 4

[0151]

[0152] 5. Overall Process

[0153] Among the above three stages, based on stage 1 (initial positioning point), the normal process is to alternate between stage 2 (air positioning point) and stage 3 (landing positioning point), that is, from the air positioning point to the landing positioning point and from the landing positioning point to the air positioning point. It can also support stage 2 to stage 2 (from one air positioning point to another air positioning point) and stage 3 to stage 3 (from one landing positioning point to another landing positioning point).

[0154] 1. From one aerial positioning point to another

[0155] The current ground landing position P of the UAV node in stage 2 G Replace it with the current drone node aerial positioning point position, and then proceed according to the method of stage 2.

[0156] 2. From one landing point to another

[0157] Set the position of the aerial positioning point P in stage 3 air Replace it with the current drone landing location, and then proceed according to the method of stage three.

[0158] 3. Alternate between air positioning points and landing positioning points

[0159] This includes from an aerial positioning point to a landing positioning point and from a landing positioning point to an aerial positioning point, which is the main deployment form of sustainable networking.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the technical solutions. Those skilled in the art should understand that modifications or equivalent replacements of the technical solutions of the present invention that do not depart from the purpose and scope of the technical solutions of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A communication relay UAV dynamic positioning method based on multi-node collaborative labeling, characterized by: include: S1: Build a self-organizing network consisting of a drone node and several network nodes; S2: Each network node moves as needed and marks candidate landing points on the movement route. Each network node obtains the ID of the one-hop node whose distance to the candidate landing point exceeds the threshold and the corresponding link propagation loss, and generates annotation information. S3: The drone node receives the annotation information of all network nodes, calculates the distance from each candidate landing point to each one-hop node, combines the link propagation loss to obtain the distance-loss pair, and constructs the distance-loss pair information table of the candidate landing points; S4: Determine whether to perform lift-off deployment or landing deployment based on the network connectivity and service requirements of the self-organizing network: if lift-off deployment is performed, execute step S5; if landing deployment is performed, execute step S6; S5: Aerial deployment: Select an aerial positioning point that can cover all the network nodes that need to be covered and meet the air-to-ground communication distance requirements, and control the drone node to move to the aerial positioning point to communicate with the network nodes that need to be covered; S6: Landing deployment: Filter all candidate landing points to meet the search distance requirements and select the landing positioning point with the best distance-loss pair based on the distance-loss pair information table, control the UAV node to move to the landing positioning point and communicate with the network node; S7: Repeat steps S4 to S6 to alternately implement the launch deployment and landing deployment of the drone node.

2. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 1, characterized in that: In step S3, the UAV node modifies the distance-loss pair information table according to the current connected network topology and the location of the connected node. The specific steps are as follows: S301: Obtain the maximum distance D from the distance-loss pair information table of the candidate landing points max ; The formula is: D max =max{D 1,1 ,D 1,2 ,…,D 2,1 ,D 2,2 ,D 2,3 ,…,D 3,1 ,…}; S302: Traverse all candidate landing points and determine whether there is a network node P among the non-one-hop nodes of candidate landing point i. j Satisfied: P j The distance to candidate landing point i is D i,j And d1≤D i,j ≤D max If so, then for candidate landing point i, (D i,j ,L th ), where L th is the maximum loss allowed for communication between nodes; S303: Complete the update of the distance-loss pair information table.

3. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 1, characterized in that: In step S4, if the network connectivity does not meet the standard, the lift-off deployment is performed; if the service flow weakens or the node connectivity meets the standard during a specific period, the landing deployment is performed.

4. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 1, characterized in that: In step S5, when deployed in the air, the network nodes that the drone node needs to cover are P1, P2, ..., P k , then the aerial positioning point is obtained by solving the following first model: The formula of the first model is expressed as: my|P air -P G |; s.t.|P air -P i |≤R0,i=1,2,…,k; Where: P air Indicates an aerial positioning point; P G Indicates the current position of the drone node; P i Indicates the network nodes that the drone node needs to cover; R0 indicates the reference value of the air-to-ground communication distance.

5. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 4, characterized in that: In step S5, the air-to-ground communication distance reference value is determined by the following steps: S501: Given an initial value r0 of the air-to-ground communication distance reference value R0, set the distance reference weight μ; S502: When implementing the zth aerial deployment, if the number of one-hop nodes of the drone node is m, and the distance from the drone node to each one-hop node is Then calculate the distance mean r z ; The formula is: S503: After the zth aerial deployment is completed, update the air-to-ground communication distance reference value R0; The formula is:

6. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 4, characterized in that: In step S5, if the distance between the aerial positioning point and the current position of the drone node is so large that the drone node cannot travel back and forth, the deployment is abandoned.

7. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 1, characterized in that: In step S6, the landing deployment processing steps include: S601: Taking the current aerial positioning point of the UAV node as the origin, obtain a set A of candidate landing points within the search distance S; The formula is: Where: G n Indicates the search for the nth candidate landing point within the distance S; S602: If the number of elements in the candidate landing point set A is 1, the corresponding candidate landing point is the landing positioning point; if the number of elements in the candidate landing point set A is greater than 1, execute step S603; if the number of elements in the candidate landing point set A is 0, execute step S604; S603: Calculate the distance attenuation factor of each candidate landing point based on the distance-loss pair information table of the candidate landing points, and select the candidate landing point with the smallest distance attenuation factor as the landing positioning point; S604: Extend the search distance S=S+Δs, and return to step S601; where Δs represents the exploration step length.

8. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 7, characterized in that: In step S603, the distance attenuation factor of the candidate landing point is calculated by the following steps: S6031: For candidate landing point G n ∈A, according to the distance-loss information table (D n,1 ,L n,1 ),(D n,2 ,L n,2 ),…,(D n,p ,L n,p ) ; Convert the distance into logarithmic form and record it as lgD n,1 =g n,1 , then we get (g n,1 ,L n,1 ),(g n,2 ,L n,2 ),…,(g n,p ,L n,p ); S6032: Assume that the distance attenuation factor of the distance-loss pair is α n , then the candidate landing point G n The corresponding α n The following second model is satisfied; The formula of the second model is expressed as: min∑ i＝1,2,…,p (g n,i a n -L n,i ) 2 ; S6033: Solve the second model to obtain the candidate landing point G n The distance attenuation factor is α n ; The formula is:

9. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 8, characterized in that: In step S603, the candidate landing point G is updated by the following formula: n Distance decay factor: Where: α ‘ n Represents the updated distance attenuation factor; α th Indicates the set threshold value.

10. The method for dynamic positioning of a communication relay UAV based on multi-node collaborative labeling according to claim 9, characterized in that: The updated distance attenuation factor α ‘ n Sort them and use the candidate landing point corresponding to the smallest distance attenuation factor as the landing positioning point.

Images