Unmanned aerial vehicle dynamic network intelligent routing method and system based on star-guided beam enabling

Abstract

The invention relates to a star-guided beam-enabled unmanned aerial vehicle dynamic network intelligent routing method and system. The method comprises the following steps: receiving a cluster routing table generated by a satellite network based on link state data of an unmanned aerial vehicle cluster; receiving a data routing request sent by a data sending node; querying the cluster routing table based on the data routing request to obtain a routing path node and a data receiving node; sending a routing message to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node, so that a flooding routing request and response interaction do not need to be initiated when data is sent between the nodes, and routing path query can be directly completed through the cluster routing table; and the routing message is only sent to the routing path node and the data receiving node, so that the accurate sending of the routing instruction is realized, and the problems of low routing convergence speed and large bandwidth occupied by broadcast storm in the existing unmanned aerial vehicle dynamic ad hoc network can be solved.

Description

Technical Field

[0001] This application relates to the field of wireless communication network technology, and in particular to a starguide beam-enabled intelligent routing method and system for UAV dynamic networks. Background Technology

[0002] UAV Dynamic Ad Hoc Network (UAV-DANET) is a type of distributed network system that uses unmanned aerial vehicles (UAVs) as core communication nodes, does not rely on fixed infrastructure, and achieves dynamic discovery, autonomous networking, and collaborative communication between nodes through wireless communication technology. This network has core characteristics such as flexible deployment, wide coverage, and rapid reconfiguration. However, existing UAV dynamic ad hoc networks suffer from slow routing convergence speed and large bandwidth consumption caused by broadcast storms. Summary of the Invention

[0003] This application provides a starguide beam-enabled intelligent routing method and system for UAV dynamic networks, which can solve the problems of slow routing convergence speed and large bandwidth consumption by broadcast storms in existing UAV dynamic self-organizing networks.

[0004] In a first aspect, this application provides a starguide beam-enabled intelligent routing method for UAV dynamic networks, including: Receive cluster routing tables generated by the satellite network based on link state data of UAV clusters; Receive data routing requests sent by data sending nodes; Based on the data routing request, the cluster routing table is queried to obtain the routing path nodes and data receiving nodes; A routing message is sent to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node.

[0005] In some embodiments, before receiving the cluster routing table generated by the satellite network based on the link state data of the UAV cluster, the method further includes: The link status data of the UAV cluster is obtained through the satellite network; Based on the link status data, the path score between adjacent nodes in the UAV cluster is calculated using a path scoring model. The cluster routing table is generated based on the path scores of the adjacent nodes.

[0006] In some embodiments, the link status data includes link stability and load balancing. The calculation of neighboring node path scores between adjacent nodes in the UAV cluster based on the link state data using a path scoring model is specifically as follows: Based on the link stability and the load balance, the path score between adjacent nodes in the UAV cluster is calculated using the path scoring model R = 0.6 × link stability + 0.4 × load balance. Among them, link stability = 1 - (number of historical disconnections / total communication duration) and load balancing = 1 - (cluster head traffic / maximum capacity threshold).

[0007] In some embodiments, the cluster routing table includes a primary routing table and a backup routing table; The process of generating the cluster routing table based on the path scores of the adjacent nodes includes: Calculate the interval node path score between any two interval nodes in the UAV cluster based on the adjacent node path score; The primary routing table and the backup routing table are obtained based on the path scores of adjacent nodes and the path scores of interval nodes, according to the principle of prioritizing higher scores. The primary routing table is sent to the cluster head node of the UAV cluster, and the backup routing table is sent to the backup cluster head node of the UAV cluster.

[0008] In some embodiments, sending the primary routing table to the cluster head node of the UAV cluster and sending the backup routing table to the backup cluster head node of the UAV cluster further includes: A shadow channel is established between nodes in the UAV cluster based on the backup cluster head node and the backup routing table.

[0009] In some embodiments, the starguide beam-enabled intelligent routing method for UAV dynamic networks further includes: Monitor the packet loss rate between adjacent nodes in the drone cluster; If the packet loss rate of the adjacent nodes is greater than the packet loss rate threshold, a cluster head switching command is sent to the backup cluster head through the satellite network, so that the backup cluster head can take over the data stream in the UAV cluster through the shadow channel.

[0010] In some embodiments, receiving a data routing request sent by a data sending node includes: A narrow antenna beam is formed at the transmitting end by a smart beamforming antenna on the data transmission node. The narrow antenna beam of the transmitting end is pointed at the cluster head node to send the data routing request to the cluster head node through the narrow antenna beam of the transmitting end.

[0011] In some embodiments, sending routing messages to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node includes: Multiple cluster head antenna beams are formed by intelligent beamforming antennas on the cluster head nodes; The multiple cluster head antenna beams are respectively pointed to the routing path node and the data receiving node, so as to send the routing message through the multiple cluster head antenna beams; A data routing path is established between the data sending node and the data receiving node based on the routing path node and the confirmation message of the routing message in response to the data receiving node.

[0012] In some embodiments, sending routing messages to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node further includes: Data is sent from the data sending node to the data receiving node through the data routing path.

[0013] Secondly, embodiments of this application provide a starguide beam-enabled intelligent routing system for UAV dynamic networks, applied to the starguide beam-enabled intelligent routing method for UAV dynamic networks as described in any one of the first aspects, comprising: A satellite network is used to acquire link status data of the UAV cluster; based on the link status data, a path scoring model is used to calculate the path score between adjacent nodes in the UAV cluster; and a cluster routing table is generated based on the path score between adjacent nodes. A smart beamforming antenna, mounted on a UAV node, is used to form a directional beam to establish communication links between the UAV node and the satellite network, and between the UAV nodes themselves. A multi-channel communication terminal, installed on the UAV node, is used to receive data routing requests sent by the data sending node; query the cluster routing table based on the data routing requests to obtain routing path nodes and data receiving nodes; and send routing messages to the routing path nodes and the data receiving nodes to establish a data routing path between the data sending node and the data receiving node.

[0014] The technical solutions provided in this application have the following advantages compared with the prior art: The intelligent routing method and system for UAV dynamic networks empowered by starguide beams provided in this application embodiment receives a cluster routing table generated by a satellite network based on link state data of UAV clusters; receives data routing requests sent by data sending nodes; queries the cluster routing table based on the data routing requests to obtain routing path nodes and data receiving nodes; and sends routing messages to the routing path nodes and the data receiving nodes to establish a data routing path between the data sending nodes and the data receiving nodes. This eliminates the need for flooding routing request and response interactions when sending data between nodes, as routing path queries can be directly completed through the cluster routing table, significantly shortening the convergence time. Furthermore, by sending routing messages only to the routing path nodes and the data receiving nodes, precise routing instructions are achieved, avoiding invalid reception and forwarding by irrelevant nodes, alleviating link congestion, and solving the problems of slow routing convergence speed and large bandwidth consumption by broadcast storms in existing UAV dynamic self-organizing networks. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0018] Figure 1 Flowchart of a starguide beam-enabled intelligent routing method for UAV dynamic networks provided in an embodiment of this application; Figure 2 This is a schematic diagram of a routing implementation scheme provided in one embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] The following disclosure provides numerous different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of the invention. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0021] The UAV Dynamic Ad Hoc Network uses UAVs as communication nodes. It does not rely on fixed infrastructure such as base stations and routers. It uses wireless communication technologies (such as 5G, millimeter wave, and WiFi-6) to achieve dynamic discovery, connection and networking between nodes, forming a distributed and collaborative network system. It has shown irreplaceable application value in key areas such as military communication, emergency rescue, Internet of Things data collection and intelligent transportation collaboration, and has become one of the core development directions of the next generation of communication technology systems.

[0022] However, the traditional routing protocols commonly used in existing UAV ad hoc networks (such as AODV and OLSR) exhibit significant technical shortcomings when facing scenarios involving high-speed UAV movement, dynamic changes in node topology, and time-varying communication links: 1) Slow route convergence speed: The AODV protocol, based on an on-demand route discovery mechanism, requires re-initiating route request (RREQ) and route response (RREP) interactions when the topology changes abruptly, resulting in a route reconstruction delay typically exceeding 1 second; although the OLSR protocol maintains topology information in a proactive manner, its link state update cycle is relatively long, making it difficult to match the high-speed movement characteristics of UAV nodes, and it also suffers from route convergence lag, leading to packet loss, communication interruption, and other phenomena; 2) Prominent broadcast storm problem: Traditional routing protocols often use a flooding broadcast mechanism for route discovery, where nodes indiscriminately forward route request packets to all neighboring nodes. In this mode, as the network node density increases, a large number of redundant broadcast packets will occupy more than 40% of the wireless channel bandwidth, not only causing serious waste of channel resources but also causing packet collisions, communication link congestion, and other problems, significantly reducing network transmission efficiency and communication reliability.

[0023] Firstly, such as Figure 1 , 2 As shown, to address the aforementioned technical problems, this application provides a starguide beam-enabled intelligent routing method for UAV dynamic networks, comprising: S101: Receive the cluster routing table generated by the satellite network based on the link state data of the UAV cluster; S102: Receive a data routing request sent by the data sending node; S103: Based on the data routing request, query the cluster routing table to obtain the routing path nodes and data receiving nodes; S104: Send routing messages to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node.

[0024] It should be noted that by directly receiving the cluster routing table pre-generated by the satellite network, there is no need to re-initiate flooding routing requests and responses when the topology changes dynamically. This solves the problem of routing reconstruction delays greater than 1 second in protocols such as AODV. Furthermore, routing path queries can be completed directly through the cluster routing table, significantly reducing convergence time (millisecond level) and effectively reducing the risk of data packet loss and communication interruption. In particular, the satellite network has wide-area coverage and global link status monitoring capabilities. The generated cluster routing table integrates key information such as node connection relationships and link quality of each UAV cluster, so that the data sending node does not need to obtain routing information through local interactions, further shortening the route establishment time and meeting the high real-time requirements of scenarios such as military communications and emergency rescue.

[0025] It should be noted that the routing path is determined by querying the cluster routing table, eliminating the need for the indiscriminate flooding and forwarding mechanism of traditional protocols. This fundamentally reduces the generation of redundant broadcast packets and avoids the waste of bandwidth resources. Furthermore, by sending routing messages only to the routing path nodes and the data receiving nodes, precise routing instructions are achieved, avoiding invalid reception and forwarding by irrelevant nodes, reducing the probability of packet collisions, further alleviating link congestion, and improving network throughput. The satellite network can continuously update the cluster routing table based on real-time link status data, ensuring that the routing path query is always based on the latest network topology information, guaranteeing the effectiveness and stability of the data routing path, reducing routing failures caused by link interruptions, and improving network resilience and communication reliability.

[0026] It should be noted that by querying the pre-generated cluster routing table to determine the routing path, the drone nodes do not need to execute complex route discovery and link state maintenance algorithms, which can significantly reduce the computational resource consumption of the nodes and extend the drone's endurance.

[0027] In some embodiments, before receiving the cluster routing table generated by the satellite network based on the link state data of the UAV cluster, the method further includes: The link status data of the UAV cluster is obtained through the satellite network; Based on the link status data, the path score between adjacent nodes in the UAV cluster is calculated using a path scoring model. The cluster routing table is generated based on the path scores of the adjacent nodes.

[0028] It should be noted that acquiring link status data of the UAV cluster via satellite network has advantages over local interactive acquisition between UAV nodes, including global coverage, unobstructed access, and stable transmission. It can accurately obtain core parameters such as node connection relationships, link bandwidth, signal strength, latency, and packet loss rate, avoiding the loss or distortion of link status information caused by local perception, and providing high-quality data support for routing table generation. The path scoring model quantifies the scores of paths between adjacent nodes (i.e., the adjacent node path scores), transforming abstract link status parameters (such as bandwidth, latency, and stability) into intuitive scoring indicators, allowing direct comparison of the merits of different paths, and ensuring that the paths selected in the cluster routing table are the optimal or second-best choices under the current link status.

[0029] It should be noted that by sorting and filtering the path scores of the adjacent nodes, the cluster routing table can retain only the high-quality paths whose scores meet the threshold, and eliminate the inferior links with insufficient bandwidth, excessive latency or poor stability. This ensures the communication reliability of the routing path from the source, reduces packet loss, transmission lag and other phenomena, and improves the overall network transmission quality.

[0030] In some embodiments, the link status data includes link stability and load balancing. The calculation of neighboring node path scores between adjacent nodes in the UAV cluster based on the link state data using a path scoring model is specifically as follows: Based on the link stability and the load balance, the path score between adjacent nodes in the UAV cluster is calculated using the path scoring model R = 0.6 × link stability + 0.4 × load balance. Among them, link stability = 1 - (number of historical disconnections / total communication duration) and load balancing = 1 - (cluster head traffic / maximum capacity threshold).

[0031] It should be noted that the weighted ratio of 0.6 (link stability) + 0.4 (load balancing) highlights the core role of link stability in ensuring communication continuity (such as in military and emergency scenarios, where a stable link is a prerequisite for data transmission), while also taking into account the optimization of overall network performance by load balancing. Link stability transforms the abstract concept of "stability" into a quantifiable value in the 0-1 range through "1 - (number of historical disconnections / total communication duration)," and is directly linked to historical link operation data, avoiding subjective assessment errors. Load balancing accurately reflects the resource occupancy status of cluster head nodes through "1 - (cluster head traffic / maximum capacity threshold)," ensuring that the assessment results are objective and verifiable, providing solid data support for path selection.

[0032] It should be noted that the link failure probability is quantified by "historical number of disconnections / total communication duration". A higher score indicates a lower risk of link disconnection and a longer lifespan. This calculation method can effectively reduce the frequency of route switching and reduce data packet loss and communication interruptions caused by link interruptions, thus solving the problem that traditional routing protocols are difficult to adapt to dynamic topology changes. Furthermore, the weighting coefficient of 0.6 makes link stability the dominant factor in path scoring, ensuring that the cluster routing table prioritizes links with "low probability of disconnection and long lifespan". This is particularly suitable for scenarios with stringent requirements for communication continuity, such as military tactical communication and emergency rescue, thereby improving network resilience and data transmission success rate.

[0033] It should be noted that the load saturation of cluster head nodes is calculated by "cluster head traffic / maximum capacity threshold". The higher the score, the stronger the remaining capacity of the cluster head node. This formula links the node's hardware performance (maximum capacity threshold) with its actual operating status (cluster head traffic), which can avoid local congestion caused by ignoring node load. Furthermore, by filtering paths through load balancing indicators, the situation of "high-load cluster head nodes being frequently selected" can be effectively avoided. Data traffic is reasonably distributed to nodes with strong remaining capacity, which not only prevents link paralysis due to overload of a single node, but also makes full use of idle network resources. This solves the problem of low bandwidth utilization in traditional flooding routing and improves the overall network throughput.

[0034] In some embodiments, the cluster routing table includes a primary routing table and a backup routing table; The process of generating the cluster routing table based on the path scores of the adjacent nodes includes: Calculate the interval node path score between any two interval nodes in the UAV cluster based on the adjacent node path score; The primary routing table and the backup routing table are obtained based on the path scores of adjacent nodes and the path scores of interval nodes, according to the principle of prioritizing higher scores. The primary routing table is sent to the cluster head node of the UAV cluster, and the backup routing table is sent to the backup cluster head node of the UAV cluster.

[0035] It should be noted that by selecting the optimal path among adjacent node paths and interval node paths based on the "higher score priority principle" and generating the main routing table, the data transmission can be guaranteed to use high-quality paths with "high stability and high load balancing" by default, fundamentally ensuring low latency, low packet loss rate, and high throughput. By pre-generating the backup routing table, there is no need to re-initiate route discovery and calculation when the main routing link is interrupted. The backup path can be directly used to continue data transmission. Compared with the "fault reconstruction" mode of traditional routing protocols, the switching latency is greatly shortened, which can effectively avoid data packet loss and communication interruption. It is especially suitable for scenarios with high requirements for communication continuity, such as military communication and emergency rescue.

[0036] It should be noted that by calculating the "adjacent node path score" (direct link) and the "interval node path score" (multi-hop link), the primary and backup routing tables can cover high-quality links with different hop counts and path characteristics. This avoids the adaptation limitations caused by traditional routing relying on only a single path type. For example, the primary route (i.e., cluster head node, primary routing table) uses low-hop-count direct links to ensure low latency, while the backup route (i.e., backup cluster head node, backup routing table) uses multi-hop links to avoid the risk of drastic changes in local topology and improves the network's adaptability to complex topologies. Moreover, both the primary and backup routing tables are based on quantitative score screening. Although the backup route is a "second-best choice," it still meets the preset quality threshold, avoiding a significant drop in communication performance after switching due to poor backup path quality. At the same time, the score sorting mechanism can dynamically update path priorities to ensure that the primary and backup routing tables always reflect the optimal and second-best choices under the current network conditions, adapting to the dynamic changes in link status caused by the high-speed movement of drone nodes.

[0037] It should be noted that the primary routing table is stored in the cluster head node and the backup routing table is stored in the backup cluster head node, which can form a "dual-node backup" mechanism. If the cluster head node fails due to a fault or the link is interrupted, the backup cluster head can directly use the backup routing table to take over the routing scheduling without regenerating the global routing table. This greatly improves the network's resilience and fault tolerance, and can solve the problem of cluster network paralysis caused by a single point of failure of the cluster head in traditional routing protocols.

[0038] In some embodiments, sending the primary routing table to the cluster head node of the UAV cluster and sending the backup routing table to the backup cluster head node of the UAV cluster further includes: A shadow channel is established between nodes in the UAV cluster based on the backup cluster head node and the backup routing table.

[0039] It should be noted that the shadow channel is a "standby communication link" pre-established between nodes based on the backup routing table. This eliminates the need to renegotiate link parameters and establish physical connections when the main route (i.e., the cluster head node) fails. When the main route link fails due to node movement, link breakage, or congestion, the shadow channel can be directly activated to continue data transmission. This solves the switching delay caused by the traditional "failure-based link establishment" method and achieves seamless switching with near-zero communication interruption time. For high-priority services that are sensitive to interruption time, such as military tactical communications and emergency rescue command transmission, the pre-establishment mechanism of the shadow channel can ensure that data transmission is not interrupted or lost, avoids task failure due to routing switching delays, and improves the communication reliability of critical services.

[0040] It should be noted that when the topology is dynamically reconstructed due to the high-speed movement of drone nodes, the shadow channel is updated in real time based on the backup routing table (adjusted synchronously with the satellite network link status data). It can quickly adapt to scenarios such as changes in node location, the addition or removal of new nodes, etc., ensuring that the backup link is always effective and avoiding the problem of the backup route being "useless" due to topology changes.

[0041] It should be noted that the shadow channel is not an independent link that occupies additional physical bandwidth, but rather a "logical link" pre-allocated based on existing wireless channel resources. It only maintains a low-power listening state when the main router is functioning normally and does not transmit redundant data. When the main router link becomes congested (such as when the load balancing score drops), some data traffic can be diverted in advance through the shadow channel to avoid overloading a single link. At the same time, the backup cluster head node can monitor the link status of each node in real time through the shadow channel, dynamically adjust the traffic allocation strategy, achieve fine-grained management of intra-cluster load balancing, and further improve the overall network throughput.

[0042] In some embodiments, the starguide beam-enabled intelligent routing method for UAV dynamic networks further includes: Monitor the packet loss rate between adjacent nodes in the drone cluster; If the packet loss rate of the adjacent nodes is greater than the packet loss rate threshold, a cluster head switching command is sent to the backup cluster head through the satellite network, so that the backup cluster head can take over the data stream in the UAV cluster through the shadow channel.

[0043] It should be noted that packet loss rate is a direct quantitative indicator reflecting the quality of link communication. It is directly related to the success rate and reliability of data transmission. By monitoring the packet loss rate between adjacent nodes in real time, communication degradation of the main routing link caused by node movement, electromagnetic interference, overload, etc. can be accurately captured, enabling early prediction and proactive response to faults and avoiding large-scale data loss due to complete link failure. By setting packet loss rate thresholds (such as 5%, 10%, 40%, etc.), the switching trigger conditions can be clearly defined, avoiding false switching caused by instantaneous fluctuations in the link. At the same time, it ensures that emergency plans are activated in time before the communication quality drops to a critical value. This not only solves the problem of "lagging fault detection" in traditional routing, but also avoids network oscillations caused by frequent switching, achieving a balance between the accuracy and stability of fault response.

[0044] It should be noted that sending the cluster head switching command via satellite network has advantages over distributed negotiation between nodes within a UAV cluster, including lower transmission latency, wider coverage, and stronger anti-interference capabilities. This avoids response delays caused by blocked switching command transmission when intra-cluster communication deteriorates. Furthermore, the backup cluster head has already completed link parameter negotiation and resource reservation based on a pre-established shadow channel. Upon receiving the switching command, it can directly take over the data stream through the shadow channel without re-establishing links, negotiating routes, or synchronizing states. Compared to the traditional routing model of "reconstructing the routing table and establishing a new link after switching cluster heads," this eliminates communication interruptions during the switching process, achieves seamless data stream continuity, and ensures the transmission continuity of high-priority services (such as military commands and emergency data).

[0045] In some embodiments, receiving a data routing request sent by a data sending node includes: A narrow antenna beam is formed at the transmitting end by a smart beamforming antenna on the data transmission node. The narrow antenna beam of the transmitting end is pointed at the cluster head node to send the data routing request to the cluster head node through the narrow antenna beam of the transmitting end.

[0046] It should be noted that the intelligent beamforming antenna forms a narrow antenna beam through signal phase modulation, concentrating the wireless signal energy in a specific direction (the location of the cluster head node). Compared with the signal energy diffusion mode of traditional omnidirectional antennas, it can improve the link signal strength between the transmitter and the cluster head node, effectively overcome the path loss in high-altitude operations and long-distance communication of UAVs, reduce the risk of packet loss caused by signal attenuation of routing request data packets (i.e., the data routing request), and ensure that the routing request is delivered to the cluster head node quickly and accurately. Moreover, the directional transmission of the narrow antenna beam avoids the diffusion of the signal to irrelevant nodes, reducing signal fading and distortion caused by multipath propagation.

[0047] It should be noted that traditional routing protocols flood routing requests through omnidirectional antennas, causing all nodes within the signal coverage area to receive redundant requests, leading to bandwidth consumption and signal collisions. This embodiment uses a narrow beam directed towards the cluster head node, transmitting routing requests only to the target node, thus eliminating interference to irrelevant nodes at the source, avoiding bandwidth waste caused by flooding, improving the effective utilization of the wireless channel, and reserving more bandwidth resources for data transmission. Furthermore, in dynamic UAV networks where multiple nodes communicate simultaneously, omnidirectional antennas are prone to co-channel interference, leading to signal conflicts and reduced transmission efficiency. The directional transmission characteristics of the narrow antenna beam can reduce the overlapping coverage of routing request signals from different nodes, lowering the probability of co-channel interference. Especially in large-scale UAV networking scenarios, this can effectively improve the success rate of multiple nodes sending routing requests in parallel, avoiding network congestion.

[0048] In some embodiments, sending routing messages to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node includes: Multiple cluster head antenna beams are formed by intelligent beamforming antennas on the cluster head nodes; The multiple cluster head antenna beams are respectively pointed to the routing path node and the data receiving node, so as to send the routing message through the multiple cluster head antenna beams; A data routing path is established between the data sending node and the data receiving node based on the routing path node and the confirmation message of the routing message in response to the data receiving node.

[0049] It should be noted that the cluster head node generates multiple independent narrow beams simultaneously through a smart beamforming antenna, pointing to the routing path nodes and the data receiving nodes respectively. This enables parallel transmission of routing messages. Compared with the serial transmission mode of traditional omnidirectional antennas that "forward one by one" or "flood broadcast," this can shorten the time for routing messages to reach all target nodes and significantly improve the efficiency of routing message distribution. Furthermore, by sending routing messages directly to the routing path nodes through the cluster head node, without the need for forwarding through intermediate nodes, the latency accumulation and message distortion caused by multi-hop forwarding are avoided. At the same time, the number of hops in the transmission of routing messages is reduced, further shortening the overall latency of routing path establishment, thus meeting the requirement of UAV dynamic networks for fast routing convergence.

[0050] It should be noted that establishing a routing path (i.e., the data routing path) based on the acknowledgment message (ACK) of the target node can verify the reception status of the routing message and the reachability of the node in real time, avoid "false routing paths" caused by node offline or link interruption, and ensure that the established routing path has actual communication capability.

[0051] In some embodiments, sending routing messages to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node further includes: Data is sent from the data sending node to the data receiving node through the data routing path.

[0052] It should be noted that the data routing path is established based on the cluster routing table (primary / backup) generated by satellite. The path is filtered by quantitative scoring of "link stability + load balancing" and node reachability is verified through the routing message confirmation mechanism. This ensures that the path has the characteristics of "low packet loss, low latency, and high stability", which fundamentally solves the problems of data loss and transmission delays caused by uncontrollable path quality in traditional routing. If the primary routing path triggers cluster head switching due to problems such as excessive packet loss rate, the backup cluster head can seamlessly take over data transmission through the pre-established shadow channel without re-establishing the routing path, achieving "zero interruption" continuity of data transmission. This is especially suitable for business scenarios with strict continuity requirements, such as military commands and emergency rescue data.

[0053] It should be noted that the data is transmitted in a directed manner through the established routing path (i.e., the data routing path) and is forwarded only between nodes on the routing path. There is no need to use traditional flooding transmission, which reduces the bandwidth resources occupied by redundant data from the source and concentrates channel resources for effective data transmission, thereby improving the overall network throughput.

[0054] It should be noted that, for example, the routing implementation process is as follows: First, the route establishment phase: Member UAV7 needs to send images to UAV12, and the directional beam sends routing messages to the cluster head node; the cluster head node calls the satellite pre-calculated path: UAV7 → cluster head → UAV3 → UAV12, and synchronously establishes the path through the beam antenna; Second, the sabotage handover phase: the satellite detects that the frame loss rate (packet loss rate) of the UAV3 link has increased significantly, and the calculated probability of failure reaches 92%; the satellite issues a handover command; silent handover is initiated: the backup cluster head enables the new path UAV7 → backup cluster head → UAV5 → UAV12 through the shadow channel; seamlessly taking over the data stream.

[0055] Secondly, embodiments of this application provide a starguide beam-enabled intelligent routing system for UAV dynamic networks, applied to the starguide beam-enabled intelligent routing method for UAV dynamic networks as described in any one of the first aspects, comprising: A satellite network is used to acquire link status data of the UAV cluster; based on the link status data, a path scoring model is used to calculate the path score between adjacent nodes in the UAV cluster; and a cluster routing table is generated based on the path score between adjacent nodes. A smart beamforming antenna, mounted on a UAV node, is used to form a directional beam to establish communication links between the UAV node and the satellite network, and between the UAV nodes themselves. A multi-channel communication terminal, installed on the UAV node, is used to receive data routing requests sent by the data sending node; query the cluster routing table based on the data routing requests to obtain routing path nodes and data receiving nodes; and send routing messages to the routing path nodes and the data receiving nodes to establish a data routing path between the data sending node and the data receiving node.

[0056] The device / system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0057] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0058] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also mean including the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a specific order described or illustrated unless the order of execution is explicitly indicated. It should also be understood that additional or alternative steps may be used. The above description is merely a specific embodiment of the invention to enable those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A starguide beam-enabled intelligent routing method for UAV dynamic networks, characterized in that, include: Receive cluster routing tables generated by the satellite network based on link state data of UAV clusters; Receive data routing requests sent by data sending nodes; Based on the data routing request, the cluster routing table is queried to obtain the routing path nodes and data receiving nodes; A routing message is sent to the routing path node and the data receiving node to establish a data routing path between the data sending node and the data receiving node.

2. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to claim 1, characterized in that, Before receiving the cluster routing table generated by the satellite network based on the link state data of the UAV cluster, the following are also included: The link status data of the UAV cluster is obtained through the satellite network; Based on the link status data, the path score between adjacent nodes in the UAV cluster is calculated using a path scoring model. The cluster routing table is generated based on the path scores of the adjacent nodes.

3. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to claim 2, characterized in that, The link status data includes link stability and load balancing; The calculation of neighboring node path scores between adjacent nodes in the UAV cluster based on the link state data using a path scoring model is specifically as follows: Based on the link stability and the load balance, the path score between adjacent nodes in the UAV cluster is calculated using the path scoring model R = 0.6 × link stability + 0.4 × load balance. Among them, link stability = 1 - (number of historical disconnections / total communication duration) and load balancing = 1 - (cluster head traffic / maximum capacity threshold).

4. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to claim 2, characterized in that, The cluster routing table includes a primary routing table and a backup routing table; The process of generating the cluster routing table based on the path scores of the adjacent nodes includes: Calculate the interval node path score between any two interval nodes in the UAV cluster based on the adjacent node path score; The primary routing table and the backup routing table are obtained based on the path scores of adjacent nodes and the path scores of interval nodes, according to the principle of prioritizing higher scores. The primary routing table is sent to the cluster head node of the UAV cluster, and the backup routing table is sent to the backup cluster head node of the UAV cluster.

5. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to claim 4, characterized in that, The step of sending the primary routing table to the cluster head node of the UAV cluster and the backup routing table to the backup cluster head node of the UAV cluster further includes: A shadow channel is established between nodes in the UAV cluster based on the backup cluster head node and the backup routing table.

6. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to claim 5, characterized in that, Also includes: Monitor the packet loss rate between adjacent nodes in the drone cluster; If the packet loss rate of the adjacent nodes is greater than the packet loss rate threshold, a cluster head switching command is sent to the backup cluster head through the satellite network, so that the backup cluster head can take over the data stream in the UAV cluster through the shadow channel.

7. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to claim 1, characterized in that, The data routing request sent by the receiving data sending node includes: A narrow antenna beam is formed at the transmitting end by a smart beamforming antenna on the data transmission node. The narrow antenna beam of the transmitting end is pointed at the cluster head node to send the data routing request to the cluster head node through the narrow antenna beam of the transmitting end.

8. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to claim 1, characterized in that, Sending routing messages to the routing path nodes and the data receiving nodes to establish a data routing path between the data sending node and the data receiving node includes: Multiple cluster head antenna beams are formed by intelligent beamforming antennas on the cluster head nodes; The multiple cluster head antenna beams are respectively pointed to the routing path node and the data receiving node, so as to send the routing message through the multiple cluster head antenna beams; A data routing path is established between the data sending node and the data receiving node based on the routing path node and the confirmation message of the routing message in response to the data receiving node.

9. The intelligent routing method for UAV dynamic networks empowered by starguide beams according to any one of claims 1-8, characterized in that, The step of sending routing messages to the routing path nodes and the data receiving nodes to establish a data routing path between the data sending node and the data receiving node further includes: Data is sent from the data sending node to the data receiving node through the data routing path.

10. A starguide beam-enabled intelligent routing system for UAV dynamic networks, characterized in that, The intelligent routing method for UAV dynamic networks empowered by starguide beams as described in any one of claims 1-9 includes: A satellite network is used to acquire link status data of the UAV cluster; based on the link status data, a path scoring model is used to calculate the path score between adjacent nodes in the UAV cluster; and a cluster routing table is generated based on the path score between adjacent nodes. A smart beamforming antenna, mounted on a UAV node, is used to form a directional beam to establish communication links between the UAV node and the satellite network, and between the UAV nodes themselves. A multi-channel communication terminal, installed on the UAV node, is used to receive data routing requests sent by the data sending node; query the cluster routing table based on the data routing requests to obtain routing path nodes and data receiving nodes; and send routing messages to the routing path nodes and the data receiving nodes to establish a data routing path between the data sending node and the data receiving node.

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