A regional coverage resonant communication method for multi-unmanned system collaboration

Abstract

A regional coverage resonant communication method for multi-unmanned system collaboration. The unmanned systems are synchronized and move to the initialized deployment positions using the positioning system; starting from the mission center, the partitions, convergence regions of each spatial cell are determined in sequence, and the cell activation strategy is planned; according to the cell activation strategy, the corresponding spatial cell is activated; the UAV nodes belonging to the activated cell move towards the convergence region until the safe distance; check whether the data transmission is successful, if the transmission is successful, execute the next step; if the transmission is not successful, re-execute the previous step; end the communication. The relay nodes of the present invention move towards or away from each other at a specific rhythm, deliver data when moving towards each other to a very close distance, and the nodes moving away from each other will not affect the nodes that are communicating, thereby improving the end-to-end data forwarding efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV system relay communication, and particularly to the technical field of area coverage resonant communication method for multi-UAV system collaboration. Background Art

[0002] The effective aggregation and distribution of data is one of the eternal themes of communication networks, especially for sensor networks or the distribution of broadcast announcements in the network, which is of great significance. In such networks, information needs to be timely aggregated to a point or sent to the whole network through a point. In such networks, the location of communication relays and the selection of transfer points have always been one of the important issues in wireless relays. In conventional base stations or radio communication relays, in order to select a suitable communication point, various methods such as theoretical calculation, pure actual measurement, and the combination of theoretical calculation and actual measurement are generally used. In pure theoretical calculation, the designer can calculate the approximate signal loss at a specific regional distance through the relative distance between maps, the relative height of the transceiver, the transmission power of the radio, the antenna gain, etc., and set a forwarding point at the point where the signal loss may cause incorrect data reception. Pure actual measurement is that the road test personnel use signal detection tools to move along the communication relay route in the direction away from the signal source. After the signal drops to a specific threshold, this point is selected as the signal forwarding point. The method of combining theory and practice is to first roughly estimate the theoretical attenuation distance, then measure the signal around the point selected by theoretical calculation with a signal measuring instrument, and then select a suitable threshold to determine the forwarding point. In the communication relay of unmanned systems, some existing patents also have some methods that use theoretical calculation to calculate the theoretical path loss between any two points and select a relay at a suitable point of the theoretical path loss to ensure the relay transceiver of data.

[0003] In terms of theoretical research, the existing technical implementation methods are as follows: The invention patent "UAV swarm cooperative control method with intertwined tasks, communication and topology" (patent application number: CN201310170260.9) applied by Dai Qionghai et al. from Tsinghua University proposes a UAV swarm cooperative control method with intertwined tasks, communication and topology, including the following steps: establishing the correlation function of tasks, communication and topology of UAVs; establishing the strategy set of the number of interactive communications of UAVs, the strategy set of task information matrix, and the strategy set of the relative distance between interactive communication UAVs, and determining the winning matrix and related constraints; obtaining the number of UAV interactive communications, the task information transmission volume, and the relative distance between UAVs that meet the preset requirements in the strategy set of the number of interactive communications of UAVs, the strategy set of task information matrix, and the strategy set of the relative distance between interactive communication UAVs; and controlling the UAV swarm according to the number of UAV interactive communications, the task information transmission volume, and the relative distance between UAVs that meet the preset requirements. This patent application constructs the communication ability between UAVs through theoretical calculations; the patent "Method and system for obtaining UAV formation communication topology based on minimum spanning tree" (patent application number CN201610384144.0) applied by Luo He et al. from Hefei University of Technology provides a method and system for obtaining UAV formation communication topology based on minimum spanning tree. The method includes: constructing a formation communication graph according to the formation of a preset formation; calculating the minimum spanning tree of the formation communication graph; judging whether the UAV to which the root node of the minimum spanning tree belongs can be used as the formation leader, and obtaining the optimal communication topology according to the judgment result. This method constructs a formation communication graph according to the formation of a preset formation, calculates the minimum spanning tree of the formation communication graph, and then judges whether the UAV to which the root node of the minimum spanning tree belongs can be used as the formation leader. According to the judgment result, the optimal communication topology is obtained, ensuring that the overall communication cost is minimized during the formation maintenance process. This method generates a spanning tree based on the formation. The formation is known and not specifically designed for communication relay topology. UAVs provide a new degree of freedom for network performance optimization at the deployment level with their agile mobility and flexibility. However, the above two documents focus on the design and optimization of network topology, which is essentially similar to the establishment and data forwarding of traditional Ad hoc network topology, and do not consider the impact of UAV node deployment and controlled motion state on the network.

[0004] In fact, in traditional wireless relay networks, if the communication effect is not ideal after the relay point is determined according to the theoretical model, the position of the relay point can be adjusted. Since the relay points are all on the ground, this adjustment may not be troublesome. However, in the aerial drone relay network, especially in the case of multiple relays, the adjustment of a relay point may affect the relay topology of the entire network. For example, after a relay point closest to the source point is deployed according to the theoretical calculation method, there is environmental interference around it, resulting in poor communication effect. At this time, the position of the relay point needs to be moved closer to the source point. However, after the point moves, the distance between it and the next relay point will be lengthened, which will cause the second hop relay to deteriorate. If the position of the second hop is adjusted further, it will affect the communication quality between the second hop and the third hop, and so on.

[0005] The academic paper "Path Planning and Communication Optimization in the Process of Cooperative Relay of UAVs" (System Engineering and Electronic Technology) by Fu Xiaowei et al. focuses on analyzing the trajectory control and routing forwarding of UAVs, aiming to minimize the average delay of relay packets within the network under the constraints of load and hop count. However, this article is more inclined to the traditional D2D communication mode and is suitable for networks with small communication traffic. The author did not consider the cooperative motion control in the UAV network, nor did he consider the network-level packet distribution and aggregation application requirements in the scenario, such as the announcement and broadcast of control information. The academic paper "UAV Relay Layout Optimization Software Based on Google Earth" (Modern Electronic Technology) by Li Yanwen et al. deduced the maximum coverage of UAVs in the horizontal area based on the path loss of the signal, and deployed UAVs at the weighted centroid of the access user to achieve data access. At the same time, the author also designed and implemented relevant visualization software. However, the author focused on the data access of the UAV network and did not build relay links between UAV nodes. Therefore, this article is more inclined to data collection / distribution rather than building an effective data relay network. The above studies all adopt theoretical model deployment, and the actual communication effect of the deployed drones is difficult to determine, and there is no specific method for how multiple drones can cooperate with each other to achieve relay. In the process of drone cluster communication relay, what kind of relationship should exist between multiple drones is not mentioned in the existing solutions. Summary of the invention

[0006] The present invention proposes a regional coverage resonant communication method for the coordination of multiple unmanned systems. Relay nodes move toward or away from each other at a specific beat, and deliver data when they move toward each other very close, and nodes moving away from each other will not affect nodes in communication, thereby improving the end-to-end data forwarding efficiency.

[0007] A method for regional coverage resonant communication for multi-unmanned system collaboration, comprising the following steps:

[0008] S1: The unmanned system synchronizes and moves to the initialized deployment position using the positioning system;

[0009] S2: Starting from the mission center, sequentially determine the partitions and convergence regions of each spatial cell, and plan the cell activation strategy;

[0010] S3: According to the cell activation strategy in step S2, activate the corresponding spatial cells; the UAV nodes belonging to the activated cells move towards the convergence region until the safe distance;

[0011] S4: Check whether the data transmission is successful. If successful, proceed to the next step; if not, re - execute step S3;

[0012] S5: End the communication.

[0013] Preferably, the present invention performs a three - dimensional space rasterization process Each grid is assigned a specific label according to its position and regarded as a spatial cell;

[0014] Assume that the mission area is a cube with side length K, and the set of UAVs performing the mission is Deploy N UAVs evenly in the three - dimensional mission area with the same distance between adjacent UAVs; therefore, the layout of the unmanned system is related to the size of the mission area and the number of the unmanned system, and the approximate distance between adjacent UAVs is The UAVs move cooperatively to adjacent cells and use the ferry method in the delay - tolerant network for data transfer.

[0015] Preferably, the present invention divides the controlled movement of UAV nodes into three stages: spatial convergence, data transmission, and spatial dispersion.

[0016] Preferably, in the spatial convergence stage of the present invention, the unmanned cluster activates specific spatial cells according to the cell activation strategy; then, several UAV nodes belonging to the activated cells move towards the convergence region, and the flight distance is The spatial convergence stage is regarded as completing a "contraction" movement.

[0017] Preferably, in the data transmission stage of the present invention, the UAV nodes belonging to the activated cells converge at the convergence point and exchange all the collected information; when the data transmission is completed, the convergence point returns the corresponding ACK message; the data transmission stage is regarded as completing a "contraction" movement.

[0018] Preferably, in the spatial dispersion stage of the present invention, the UAVs that have completed data interaction fly back to their original deployment positions along a straight line and wait for the next neighboring cell to be activated; the movement in this stage can be regarded as completing a "dilation" movement.

[0019] Preferably, the present invention divides each cell into one or more levels according to the distance from the cell to the regional center, where the first level is the center of the mission area, a cube with side length d, the second level is the spatial area at a distance of d from the first-level cell, the third level is the spatial area at a distance of d from the second-level cell, and so on; the spatial movement of the unmanned system in one period is divided into two sub-periods, and each sub-period includes three sub-beats: spatial convergence, data transmission, and spatial dispersion;

[0020] At the start of the mission, all unmanned systems are powered on successively and remain synchronized, and move to the corresponding positions for initial deployment; in the first sub-period, the cells in the first-level partition and several cells in the third-level partition are activated, and the unmanned aerial vehicles (UAVs) belonging to each cell are controlled to execute a unit of the movement cycle for the first round of data transmission; in the second sub-period, several cells in the second-level partition are activated, and the UAVs belonging to each cell execute a unit of the movement cycle;

[0021] The above two sub-periods constitute a large period. After the unmanned system experiences a large period, the information at any position in the mission area can be quickly scaled up or down to the entire area. The calculation time for one period is set to

[0022]

[0023] The method involved in the present invention refers to the convergence and distribution methods, aiming to execute the spatial area covering specific tasks and backhaul / broadcast the corresponding data information. The invention is applicable to data transmission scenarios with a large communication guarantee area, a limited number of relay nodes, and low sensitivity to communication latency.

[0024] The resonance communication method for realizing information aggregation and distribution in an unmanned system proposed by the present invention can, without the need for theoretical calculation of node placement and without manual intervention, enable multiple unmanned systems (such as unmanned aerial vehicles, unmanned vehicles, unmanned boats, unmanned submersibles, space flight devices, etc.) to cooperate with each other according to a pre-set program and rules to complete periodic information aggregation and / or distribution. This method has the following advantages: First, its relay nodes do not need to be communicable with each other, so data can be periodically delivered in the covered area even when there are few relay unmanned system nodes; Second, compared with conventional opportunistic communication, its movement is controlled, and both communication delay and communication reliability are greatly improved; Third, the communication distance of the communication equipment it uses can be shortened to a very short distance, so as not to interfere with the communication between other nodes; Fourth, compared with other data transmission means for information aggregation and distribution, its continuous data transmission ability is stronger, and the data transmission delay for aggregation and distribution is less; In addition, since the additional movement and energy consumption overhead are less, the overall working duration of the system is longer; Fifth, through resonant information transfer, the movement range of each node (or device) does not need to be too long, and effective information transfer over ultra-long distances can be achieved through the relay of multiple nodes; Sixth, for a network with multiple packets to be transmitted end-to-end, "resonant transmission" results in less end-to-end delay than "relay transmission", which is especially suitable for end-to-end streaming information transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 FIG. is a schematic diagram of node deployment based on the mission area in the present invention.

[0026] Figure 2 FIG. is a schematic diagram of the controlled movement of an unmanned aerial vehicle node within one period of the present invention. Among them Figure 2 (a) in FIG. is a schematic diagram of the spatial aggregation (contraction) phase; Figure 2 (b) in FIG. is a schematic diagram of the data transmission (hovering) phase; Figure 2 (c) in FIG. is a schematic diagram of the spatial dispersion (expansion) phase.

[0027] Figure 3 FIG. is a three-dimensional spatial schematic diagram of the partitioning of the unmanned system in the present invention. Among them Figure 3 (a) in FIG. is a schematic diagram of the activated cell in the first sub-period; Figure 3 (b) in FIG. is a schematic diagram of the activated cell in the second sub-period.

[0028] Figure 4 FIG. is a planar projection schematic diagram of the partitioning of the unmanned system in the present invention.

[0029] Figure 5 FIG. is a schematic flow diagram of the area coverage communication method for the unmanned system in the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0030] Performing communication relay for multiple unmanned systems is one of the important application scenarios of current unmanned system clusters. Unmanned system communication mainly includes several methods such as multi-hop routing forwarding and opportunistic routing. Multi-hop routing forwarding requires reachability between adjacent nodes, so the communication distance between adjacent points is limited by the transmission distance of wireless devices; Opportunistic routing uses encounter probability, etc. as the decision basis to select relay nodes to forward packets until they reach the destination. During the selection and forwarding process, there is a risk that the packets cannot reach the destination. The resonant communication method for cooperation of multiple unmanned systems draws on the idea of charge propagation of electrons in conductors, relying on devices such as "Beidou" with short message and time synchronization functions. On a "body" with a resource aggregation point (SINK), it uses the synchronous "ferry" of unmanned systems to complete the novel data transmission method of centralized collection (aggregation) of regional data or four-way diffusion (distribution) of important messages. Its movement is controlled, and the nodes move towards or away from each other at a specific rhythm, thereby shortening the communication distance between communication nodes, improving the data communication quality between unmanned system nodes, and reducing the mutual interference of signals between nodes while the number of unmanned nodes does not need to be fully covered and without consuming a large amount of energy of the unmanned system. The method for discovering infringement by others is to observe the order and method of forming a communication relay link by the unmanned systems for convergent distribution collaborative communication, and whether there are movement characteristics with a specific rhythm.

[0031] As Figure 5 shown, a method for regional coverage resonant communication of multiple unmanned systems in cooperation includes the following steps:

[0032] S1: Synchronize the unmanned systems and use the positioning system to move to the initialized deployment positions;

[0033] S2: Starting from the mission center, sequentially determine the partitions and aggregation areas of each spatial cell, and plan the cell activation strategy;

[0034] S3: According to the cell activation strategy in step S2, activate the corresponding spatial cells; The unmanned aerial vehicle nodes belonging to the activated cells move towards the aggregation area until the safe distance;

[0035] S4: Check whether the data transmission is successful. If the transmission is successful, proceed to the next step; If the transmission is not successful, re-execute step S3;

[0036] S5: End the communication.

[0037] For the convenience of description, we perform rasterization processing on the three-dimensional space Each grid is assigned a specific label according to its position and regarded as a spatial cell. The scenario structure is as Figure 1 shown: Assume that the mission area is a cube with a side length of K cubic meters, and the set of unmanned aerial vehicles performing the mission is and represented by gray spheres. In the described scenario, N UAVs are evenly deployed within a three-dimensional mission area with the same spacing between adjacent UAVs. Therefore, the distribution points of the unmanned system are related to the size of the mission area and the number of the unmanned system, and the spacing between adjacent UAVs is approximately Due to excessive signal loss caused by the large range of the mission area, the traditional communication forwarding strategy with fixed relay positions can no longer undertake the data forwarding task. Therefore, the UAVs need to move collaboratively to adjacent cells and use the ferry method in the delay-tolerant network for data transmission.

[0038] Figure 2 Introduce the collaborative motion mechanism of UAVs. The controlled motion of UAV nodes can be divided into three stages: spatial convergence, data transmission, and spatial divergence. In the first stage, the unmanned cluster activates specific spatial cells according to the cell activation strategy. Then, 8 UAV nodes belonging to the activated cells move towards the convergence area, and the flight distance is The motion in this stage can be regarded as completing a "contraction" motion. In the second stage, the UAV nodes belonging to the activated cells will converge at the convergence point and exchange all the information collected. When the data transmission is completed, the convergence point replies with the corresponding ACK message (confirming the receipt of the packet message). Due to the short communication distance, the channel capacity of the communication in this stage is large and the transmission rate is fast. In addition, the wireless channel has a broadcast effect, and multiple UAVs converge in the convergence area, which can further improve the data transmission efficiency. In the third stage, the UAVs that have completed the data interaction fly back to their original deployment positions along a straight line and wait for the next neighboring cell to be activated. The motion in this stage can be regarded as completing a "dilation" motion. Therefore, the above-mentioned convergence, communication transmission, and divergence of the unmanned cluster can be regarded as a unit motion cycle, which contains three sub-beats (contraction-hover-dilation).

[0039] To effectively improve the data transmission efficiency, it will be divided into one level or multiple levels according to the distance between each cell and the regional center. Figure 3 and Figure 4 Taking the three-level partition of the unmanned system as an example, the first level is a cube with side length d at the center of the mission area, the second level is the spatial area at a distance of d from the first-level cell, and the third level is the spatial area at a distance of d from the second-level cell. The present invention divides the spatial motion of the unmanned system in one cycle into two sub-cycles, and each sub-cycle contains three sub-beats: spatial convergence, data transmission, and spatial divergence. At the beginning of the mission, all the unmanned systems are powered on successively and remain synchronized, and move to Figure 1 the corresponding positions initialized and deployed in Figure 3 As shown in (a) of Figure 3As shown in (b), in the second sub-cycle, 8 cells in the second-level partition are activated. The drones belonging to the cells execute one unit of the motion cycle (convergence-hovering-dilation). The above two sub-cycles constitute a large cycle. As Figure 4 shown, after the unmanned system experiences a large cycle, the information at any position within the mission area can be quickly scaled up or down to the entire area. Specifically, the calculation time for one cycle can be set to Therefore, the proposed strategy can quickly perform data aggregation / distribution and efficiently execute the area coverage task.

[0040] The present invention focuses on the data interaction strategy in three-dimensional space, aiming at a regional coverage resonance communication method for multi-drone collaboration. The core of the patent lies in optimizing the cell activation strategy and planning the controlled motion of drones. Since the optimization content does not involve the relevant variables of the upper layer protocol, the proposed strategy is independent of the upper layer protocol. For example, situations such as packet loss and out-of-order are handled by the upper layer protocol and will not be elaborated here.

[0041] This embodiment provides a schematic for constructing the spatial area coverage of a drone system. Without loss of generality, the unmanned system in this schematic is represented by drones. Please refer to Figures 3 - 4 Assume that both the first-level nodes and the third-level connections need to notify the detected information to the entire network to achieve effective area coverage. Assume that the obstacle height in the mission area does not exceed M meters (assume M = 100 meters). At this time, the minimum takeoff height of the drone can be set to 100 meters. This can avoid the influence of interference. The schematic of this case distributes 125 drones in a grid pattern. Without loss of generality, assume that the side length of the spatial cell is R meters (assume R = 50 meters), the farthest communication distance of the drone is D meters (assume D = 20 meters), and the safety distance is Q meters (assume Q = 1 meter). The spatial cell grading is based on the grading in the figure. Assume that the flight speed of the drone is V meters per second (assume V = 5m / s). In the contraction beat of the first sub-cycle, the first-level (red) and third-level cells (yellow) are activated, and the 8 drone nodes belonging to each cell "contract" and move towards the convergence area of each spatial cell at a speed of 5 meters per second. When the 8 drones move within the farthest communication distance D of the convergence area, any two drones can communicate with each other, and then approach the safety distance. To prevent collisions between drones and between drones and point S, they stop flying when they reach the safety distance. When the data transmission ends, the 8 drones enter the "dilation" beat and return to their initial positions. Among them, the total motion time is At this time, the first sub-cycle ends, and the second sub-cycle starts and is activated. Since the spatial cells all perform regular controlled movements, the second sub-cycle takes the same time as the first sub-cycle, except that the activated hierarchical cells are different. Then, first, the second-level cells (purple) are activated, and the 8 drones belonging to each cell take after that to "contract" to the specified convergence area and stop before the safe distance. After the data transmission is completed, the 8 drones enter the "dilation" rhythm and return to the initial position, and the total movement time is The whole process can be automatically completed by the drones according to the pre-set procedures and processes without manual participation.

[0042] The topology of the unmanned system for data convergence can be a triangular prism, a pentahedron, or other topologies that can cover the area. According to a similar multiple-beat or further refinement of the beat described above, the final result is that the data is periodically distributed or converged. Or multiple points achieve periodic data convergence or data distribution according to regional partitions. In addition, the data transmission points within the spatial cells can be related areas that can ensure communication connectivity.

[0043] The movement synchronization between multiple drones can be achieved through the short messages of Beidou, or through a time-sharing agreement mechanism under a unified agreement or with the cooperation of other time-unified devices (such as built-in high-stability clocks such as rubidium clocks).

[0044] In addition to drones (rotary-wing, fixed-wing), other information transfer devices with relatively longer communication distances, such as unmanned boats, unmanned submersibles, and aircraft in space, can adopt a similar resonant communication forwarding mechanism. While ensuring that other nodes do not interfere with the communication nodes, periodic information convergence and distribution are achieved through rhythmic repeated data interaction, and the communication interference to other nodes is reduced.

[0045] The present invention utilizes the controlled movement of relay drones. During data transmission, the drone network activates one or more cells, and the drones belonging to the activated cells perform regular convergence and divergence. Their movement pattern is similar to the blood circulation caused by the contraction and relaxation of the heart, so this transmission method is called "resonant communication". In the proposed communication method, each unmanned system node does not need to move a long distance, as long as it can reach the next hop. When there are fewer nodes, the resonant movement distance of the unmanned system is large, and when there are more nodes, the left and right resonant distances of the unmanned system are small. Therefore, the number of unmanned system nodes required for this data transmission method can be more or less, and it has a strong adaptability to scenarios. In "resonant communication", data continuously flows through the network of the unmanned system, ensuring the freshness of the data. Since the energy consumption of the unmanned system mainly depends on the acceleration during flight, when the acceleration changes little, the additional energy consumption of the unmanned system can be ignored; on the other hand, since adjacent nodes can move very close to each other before communication, "resonant communication" reduces the communication duration and energy consumption on the one hand, and reduces the interference to other non-adjacent nodes on the other hand. Compared with the traditional strategy of equidistant deployment and fixed-position forwarding of multiple relay drones, the "resonant communication scheme" utilizes the controlled movement characteristics of nodes to improve the spectral efficiency of data transmission and reduce the end-to-end delay of streaming media.

Claims

1. A regional coverage resonant communication method for multi-unmanned system collaboration, characterized in that It includes the following steps: Step S1: The unmanned system synchronizes and moves to the initialized deployment position using the positioning system; Step S2: Starting from the task center, sequentially determine the partitions and convergence areas of each spatial cell, and plan the cell activation strategy; The specific process is as follows: rasterize the three-dimensional space Each grid is assigned a specific label according to its position and regarded as a spatial cell; Assume that the task area is a cube with side length K, and the set of drones performing the task is N drones are evenly deployed within the three-dimensional task area with the same spacing between adjacent drones; therefore, the distribution points of the unmanned system are related to the size of the task area and the number of the unmanned system, and the spacing between adjacent drones is approximately The drones move collaboratively to adjacent cells and use the ferry method in the delay-tolerant network for data transfer; Step S3: According to the cell activation strategy in Step S2, activate the corresponding spatial cell; the unmanned aerial vehicle (UAV) nodes belonging to the activated cell move towards the convergence area until the safe distance; The specific process is as follows: The controlled movement of the UAV nodes is divided into three stages: spatial convergence, data transmission, and spatial dispersion; In the spatial convergence stage, the unmanned cluster activates specific spatial cells according to the cell activation strategy; then, several UAV nodes belonging to the activated cells move towards the convergence area, and the flight distance is The spatial convergence stage is regarded as completing a "contraction" movement; In the data transmission stage, the UAV nodes belonging to the activated cell will converge at the convergence point and exchange all the collected information; when the data transmission is completed, the convergence point returns the corresponding ACK message; The data transmission stage is regarded as completing one "contraction" movement; In the spatial dispersion stage, the UAVs that have completed data interaction fly back to the original deployment position along a straight line and wait for the next neighboring cell to be activated; the movement in this stage can be regarded as completing one "dilation" movement; It will be divided into one level or multiple levels according to the distance between each cell and the regional center. Among them, the first level is a cube with a side length of d at the center of the task area, the second level is the spatial area at a distance of d from the first-level cell, the third level is the spatial area at a distance of d from the second-level cell, and so on; the spatial movement of the unmanned system in one cycle is divided into two sub-cycles, and each sub-cycle includes three sub-beats: spatial convergence, data transmission, and spatial dispersion; At the beginning of the task, all unmanned systems are powered on successively and remain synchronized, and move to the corresponding initialized deployment positions; in the first sub-cycle, the cells in the first-level partition and several cells in the third-level partition are activated, and the UAVs belonging to each cell are controlled to execute one unit of the movement cycle for the first round of data transmission; In the second sub-cycle, several cells in the second-level partition are activated, and the UAVs belonging to each cell execute one unit of the movement cycle; The above two sub-cycles form a large cycle. After the unmanned system experiences one large cycle, the information at any position within the task area can be quickly scaled up and down to the entire area. The calculation time for one cycle is set to Step S4: Check whether the data transmission is successful. If the transmission is successful, proceed to the next step; if the transmission is not successful, re-execute Step S3; Step S5: End the communication.

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