A survivable communication system and communication method for a drone swarm

Abstract

This invention relates to the field of unmanned aerial vehicle (UAV) technology and discloses a robust communication system and method for UAV swarms. The system includes a multimodal heterogeneous communication subsystem and a dynamic network topology subsystem. The multimodal heterogeneous communication subsystem selects multimodal heterogeneous communication modules based on the communication environment and determines the communication mode, including 4G / 5G communication, broadband self-organizing network, long-distance narrowband communication, opportunistic relay, and radio frequency-free communication. The dynamic network topology subsystem includes an adaptive network topology construction module and a communication mode decision module. It determines the communication mode and network topology based on the communication environment quality and the UAV mission communication requirements, and performs topology reconstruction. This invention integrates multimodal heterogeneous communication modules, selects communication modes according to the communication environment, eliminates dependence on a single communication link, avoids swarm communication paralysis due to single link failure, achieves link-level robustness, and ensures high reliability and damage resistance of UAV swarm communication.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) technology, and more specifically to a survivable communication system and method for UAV swarms. Background Technology

[0002] Currently, drone technology is rapidly evolving from single-unit operations to swarming and collaborative systems, with drone swarms being widely used in urban patrols, emergency search and rescue, and other fields. However, current drone swarms heavily rely on continuous and stable communication data links, resulting in communication bottlenecks in highly dynamic, highly interference-prone, or large-scale scenarios. Therefore, achieving reliable and robust communication for drone swarms has become a critical issue. Summary of the Invention

[0003] This invention provides a sabotage-resistant communication system and method for unmanned aerial vehicle (UAV) swarms, in order to solve the problem of how to achieve reliable and sabotage-resistant communication for UAV swarms.

[0004] In a first aspect, the present invention provides a robust communication system for unmanned aerial vehicle (UAV) swarms, comprising: a multimodal heterogeneous communication subsystem and a dynamic network topology subsystem, wherein... The multimodal heterogeneous communication subsystem includes a multimodal heterogeneous communication module and a unified communication management layer. The multimodal heterogeneous communication subsystem is used to select the multimodal heterogeneous communication module according to the communication environment, determine the communication mode, and monitor the link quality, switch the communication mode, and adaptively adjust the transmission protocol parameters through the unified communication management layer. The communication modes include 4G / 5G communication, broadband self-organizing network, long-distance narrowband communication, opportunistic relay, and radio frequency-free communication. The dynamic network topology subsystem includes an adaptive network topology construction module and a communication mode decision module. The adaptive network topology construction module is used to determine the connection strength between the current drone and other drones in the drone cluster based on the current link quality, drone mission role, and drone location. The connection strength includes strong connection, weak connection, and disconnection. The communication mode decision module is used to determine the communication mode and network topology based on the communication environment quality and drone mission communication requirements, and inputs the decision results into the adaptive network topology construction module for topology reconstruction.

[0005] This invention integrates multimodal heterogeneous communication modules to select communication modes according to the communication environment, eliminating dependence on a single communication link and avoiding paralysis of cluster communication due to single link failure, thus achieving link-level resilience. It ensures continuous and stable communication through a unified communication management layer, and autonomously optimizes the network topology by adaptively constructing the network topology, intelligently deciding on the communication mode, and reconstructing the topology based on the decision results. This enables dynamic optimization of UAV cluster communication, ensuring high reliability, resilience, and sustainability of UAV cluster communication.

[0006] In one optional implementation, the unified communications management layer is used to receive link quality reports from multimodal heterogeneous communication modules, predict link quality using an exponentially weighted moving average algorithm, switch communication modes using a soft handover mechanism, and dynamically adjust transmission protocol parameters according to the current communication mode.

[0007] This invention uses a unified communication management layer to predict link quality based on the link quality using an exponentially weighted moving average algorithm, thereby anticipating communication degradation in advance and improving the predictability and robustness of communication. It employs a soft handover mechanism to switch communication modes, ensuring continuous and reliable communication. Furthermore, it dynamically adjusts transmission protocol parameters based on the current communication mode to maximize the utilization of link resources and improve transmission stability.

[0008] In one optional implementation, the dynamic network topology subsystem uses a neighbor discovery and link maintenance protocol for topology reconstruction. The neighbor discovery and link maintenance protocol involves the UAV periodically broadcasting beacon frames, the receiver calculating the link quality index based on the beacon frames, and performing topology reconstruction if the link quality index is lower than a preset link quality threshold.

[0009] This invention employs a neighbor discovery and link maintenance protocol for topology reconstruction. It ensures real-time network awareness by periodically broadcasting beacon frames from drones and automatically triggers topology reconstruction based on the link quality index to respond quickly in the early stages of link degradation, prevent the fault from escalating, and improve the resilience and adaptability of the drone swarm network.

[0010] In one alternative implementation, the dynamic network topology subsystem employs a link active optimization mechanism, which uses the potential field method to determine the direction of movement by treating the communication quality gradient as a virtual force, thereby driving the UAV to move in the direction of movement while avoiding obstacles.

[0011] This invention employs a link active optimization mechanism, which uses the communication quality gradient as a virtual force to guide the movement of the UAV, thereby actively improving the communication link quality and causing the UAV to move towards areas with stronger signals. While optimizing communication, it also takes into account obstacle avoidance constraints, ensuring the flight safety of the UAV.

[0012] In a second aspect, the present invention provides a survivable communication method for unmanned aerial vehicle (UAV) swarms, applied to a survivable communication system for UAV swarms as described in the first aspect or any corresponding embodiment thereof, the method comprising: The communication mode is determined based on the communication environment. The communication modes include 4G / 5G communication, broadband self-organizing network, long-distance narrowband communication, opportunistic relay, and radio frequency-free communication. Based on the link quality monitoring results, switch communication modes and adaptively adjust transmission protocol parameters; The connection strength between the current drone and other drones in the drone cluster is determined based on the current link quality, drone mission role, and drone location. The connection strength includes strong connection, weak connection, and disconnection. The communication mode and network topology are determined based on the quality of the communication environment and the communication requirements of the UAV mission, and the topology is reconstructed based on the decision results.

[0013] This invention achieves link-level resilience and ensures continuous and stable communication by selecting communication modes according to the communication environment, eliminating dependence on a single communication link, avoiding paralysis of cluster communication due to single link failure, and adaptively constructing network topology, intelligently deciding on communication modes, and reconstructing the topology based on the decision results to autonomously optimize the network topology, thereby achieving dynamic optimization of UAV cluster communication and ensuring high reliability, resilience, and sustainability of UAV cluster communication.

[0014] In one optional implementation, determining the communication mode based on the communication environment includes: If the communication environment is within a drone swarm that requires high-bandwidth data exchange and is covered by 4G / 5G base stations, then the communication mode should be 4G / 5G communication. If the communication environment is a drone cluster that requires high-bandwidth data exchange, and the drones are within line of sight and unobstructed, then the communication mode should be broadband self-organizing network. If the communication environment is a drone swarm that needs to send critical commands and status information, and the communication distance between drones is within the long-distance communication range, there is interference, or the high-bandwidth link fails, then the communication mode should be long-distance narrowband communication. If available drones or ground equipment exist in the communication environment as relay nodes, then the communication mode is selected as opportunistic relay; If the communication environment is such that the drone is within visual range, then select the communication mode as non-radio frequency communication.

[0015] This invention achieves optimal allocation and on-demand use of communication resources by matching corresponding communication modes according to different communication environments and business needs, thereby eliminating the dependence on a single, continuous, stable, and high-bandwidth communication link and improving the anti-interference, survivability, and environmental adaptability of UAV swarm communication.

[0016] In one alternative implementation, the method further includes: Calculate the link quality index based on the beacon frames broadcast by the drone; If the link quality index is lower than the preset link quality threshold, network topology reconstruction will be triggered.

[0017] This invention automatically triggers network topology reconstruction based on the link quality index, enabling rapid response in the early stages of link degradation, preventing the escalation of faults, and improving the resilience and adaptability of UAV swarm networks.

[0018] Thirdly, the present invention provides an electronic device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the survivability communication method for unmanned aerial vehicle swarms described in the second aspect or any corresponding embodiment thereof.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the survivable communication method for unmanned aerial vehicle swarms described in the second aspect or any corresponding embodiment thereof.

[0020] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the survivable communication method for unmanned aerial vehicle swarms described in the second aspect or any corresponding embodiment thereof. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of a survivable communication system for unmanned aerial vehicle (UAV) swarms according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of a survivable communication method for unmanned aerial vehicle (UAV) swarms according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0025] In related technologies, drone swarm communication relies on reliable communication such as high bandwidth, low latency, Wi-Fi, or self-organizing networks. To reduce the dependence of drone swarms on ideal communication and enhance the resilience of drone communication, this invention provides a resilience communication system for drone swarms. This system abandons the dependence on a single, continuous, stable, high-bandwidth communication link and switches to heterogeneous communication. It maintains necessary group information interaction in dynamic, harsh, and even adversarial environments, ensuring that drone missions can continue, reducing the dependence of drone swarms on ideal communication, and enhancing the resilience of drone communication.

[0026] This invention provides an embodiment of a survivable communication system for unmanned aerial vehicle (UAV) swarms, such as... Figure 1 As shown, the system includes a multimodal heterogeneous communication subsystem and a dynamic network topology subsystem. The UAV swarm is equipped with multiple complementary communication models, forming a multimodal communication toolkit. Specifically, the multimodal heterogeneous communication subsystem includes multimodal heterogeneous communication modules. These modules are autonomously selected based on the specific communication environment of the scenario to determine the communication mode. Communication modes include 4G / 5G communication, broadband self-organizing network, long-distance narrowband communication, opportunistic relay, and radio frequency-free communication.

[0027] The multimodal heterogeneous communication subsystem also includes a unified communication layer (UCL). Multimodal communication collaboration in this system is achieved through the unified communication layer, which sits above the multimodal heterogeneous communication modules and provides the following functions: real-time monitoring and prediction of link quality, seamless switching of communication modes, and adaptive adjustment of transmission protocol parameters.

[0028] By using an exponentially weighted moving average algorithm to predict link quality based on the unified communication management layer, communication degradation can be anticipated in advance to improve the predictability and robustness of communication. A soft handover mechanism is adopted to switch communication modes to ensure the continuity and reliability of the communication process. Transmission protocol parameters are dynamically adjusted according to the current communication mode to maximize the utilization of link resources and improve transmission stability.

[0029] The network structure is no longer a preset fixed star or mesh structure, but is dynamically reconstructed in real time based on link quality and UAV mission communication requirements. The dynamic network topology subsystem includes an adaptive network topology construction module and a communication mode decision module. The adaptive network topology construction module is used to dynamically determine the connection strength between the current UAV and other UAVs in the UAV cluster based on the current link quality, UAV mission role, and UAV location. The connection strength includes strong connection, weak connection, and disconnection.

[0030] The dynamic network topology subsystem also includes a communication mode decision module. This module determines the communication mode and network topology based on the quality of the communication environment and the communication requirements of the UAV mission. The decision results are then input into the adaptive network topology construction module for topology reconstruction. Through intelligent decision-making, the module maintains necessary group information interaction in dynamic, harsh, and even adversarial environments, ensuring that the UAV mission can continue.

[0031] When drone swarms perform flight missions in open airspace (such as the sea or desert), they are unobstructed and have minimal interference. They use 4G / 5G or broadband self-organizing networks by default to maintain full interconnection. The drone swarms share high-definition video streams and real-time locations at high speeds for dense collaborative searches.

[0032] When a drone swarm enters an area with many tall buildings, the communication signal deteriorates sharply due to multipath effects and blockages, causing a surge in data packet loss. At this point, the drone's intelligent onboard system makes a decision based on preset rules or reinforcement learning strategies: it degrades from a fully meshed topology to using the drone with the best current signal as a temporary central communication node, responsible for information aggregation and forwarding. Other drones then use this central node for information aggregation and forwarding. Critical formation control commands (such as formation turning) are switched to a more interference-resistant narrowband data transmission channel to ensure basic coordination remains intact.

[0033] Specifically, the multimodal heterogeneous communication module periodically monitors link quality and reports it to the unified communications management layer. The unified communications management layer receives the link quality reports from the multimodal heterogeneous communication modules and uses an Exponential Weighted Moving Average (EWMA) algorithm to predict link quality trends, preparing for handover in advance. A soft handover mechanism is employed to switch communication modes, avoiding disconnecting the old link first. Instead, the new link is established and stabilized before gradually migrating the data stream, rather than abruptly cutting it off. This ensures a smooth handover process and avoids interruptions. During handover, critical data is transmitted simultaneously on multiple links, including the old and new links, using redundant encoding (such as fountain codes). Non-critical data is temporarily stored in a local buffer queue and retransmitted after the new link is fully established and stable. This approach ensures reliable transmission of critical data while preventing non-critical data from interfering with the handover process.

[0034] The unified communications management layer dynamically adjusts transmission protocol parameters based on the current communication mode. In narrowband mode, it adopts simplified header compression and aggregated transmission, while in broadband mode, it enables multiplexing and traffic shaping.

[0035] It should be noted that the trigger condition for communication mode switching is set to forced switching. If the current link is interrupted for more than 200ms, the switch will be made immediately to ensure communication continuity.

[0036] Specifically, the dynamic network topology subsystem uses a neighbor discovery and link maintenance protocol for topology reconstruction. The neighbor discovery and link maintenance protocol is as follows: the UAV periodically broadcasts beacon frames, the receiver calculates the link quality index based on the beacon frames, and if the link quality index is lower than a preset link quality threshold, topology reconstruction is performed.

[0037] The topology reconstruction is performed using a neighbor discovery and link maintenance protocol. The UAV periodically broadcasts beacon frames to ensure real-time network awareness. The topology reconstruction is automatically triggered based on the link quality index to respond quickly in the early stages of link degradation, prevent the fault from escalating, and improve the resilience and adaptability of the UAV swarm network.

[0038] Specifically, the dynamic network topology subsystem employs a link active optimization mechanism, which uses the potential field method to treat the communication quality gradient as a virtual force to determine the direction of movement of the drone, driving it to move in that direction while avoiding obstacles. During formation flight, non-critical drones are allowed to deviate from their predetermined paths to act as relays, thereby improving the overall connectivity of the drone swarm.

[0039] By adopting a link active optimization mechanism, the communication quality gradient is used as a virtual force to guide the movement of the UAV, thereby actively improving the communication link quality and causing the UAV to move towards areas with stronger signals. While optimizing communication, obstacle avoidance constraints are taken into account, ensuring the flight safety of the UAV.

[0040] The robust communication system for UAV swarms provided in this embodiment integrates multimodal heterogeneous communication modules to select communication modes according to the communication environment, eliminating dependence on a single communication link and avoiding swarm communication paralysis due to single link failure, thus achieving link-level robustness. It ensures continuous and stable communication through a unified communication management layer, and autonomously optimizes the network topology by adaptively constructing network topology, intelligently deciding on communication modes, and reconstructing the topology based on the decision results. This achieves dynamic optimization of UAV swarm communication, ensuring high reliability, robustness, and sustainability of UAV swarm communication.

[0041] This invention provides an embodiment of a sabotage-resistant communication method for unmanned aerial vehicle (UAV) swarms. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0042] This embodiment provides a robust communication method for drone swarms, applied to the aforementioned robust communication system for drone swarms. Figure 2 This is a flowchart of a survivable communication method for unmanned aerial vehicle (UAV) swarms according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: Determine the communication mode based on the communication environment.

[0043] In this embodiment of the invention, the drone swarm no longer relies on a single communication mode, but rather autonomously decides which communication mode to use based on the specific communication environment of the scenario. The communication modes include 4G / 5G communication, broadband self-organizing network, long-distance narrowband communication, opportunistic relay, and radio frequency-free communication.

[0044] Step S202: Based on the link quality monitoring results, switch the communication mode and adaptively adjust the transmission protocol parameters.

[0045] In this embodiment of the invention, in order to achieve multimodal communication coordination, the link quality is periodically monitored, the communication mode is switched according to the link quality monitoring results, and the transmission protocol parameters are adaptively and dynamically adjusted according to the currently used communication mode.

[0046] For example, in narrowband mode, to avoid excessive bandwidth consumption from redundant information such as protocol headers, simplified header compression is used to significantly reduce data packet overhead. Simultaneously, aggregation transmission is enabled to combine multiple small data packets into a single large packet for transmission, significantly improving channel utilization and payload ratio. In broadband mode, to fully utilize high bandwidth and prevent network congestion, multiplexing technology is employed to merge multiple data streams for transmission, filling bandwidth resources. At the same time, traffic shaping is used to smooth the data transmission rate and suppress sudden traffic attacks, ensuring transmission stability.

[0047] Step S203: Determine the connection strength between the current drone and other drones in the drone cluster based on the current link quality, drone mission role, and drone location.

[0048] In this embodiment of the invention, the drone node is no longer a fixed node. Instead, the connection strength between the current drone and other drones in the drone cluster is dynamically determined based on the current link quality, the drone's mission role, and the drone's location. The connection strength includes strong connection, weak connection, and disconnection, i.e., which neighbors the drone establishes strong connections with, which neighbors it establishes weak connections with, and which neighbors it disconnects from. For example, for nodes requiring highly reliable collaboration or neighbors with good link quality, strong connections are established for high-speed data exchange; for non-critical nodes or neighbors with poor link quality, weak connections are maintained or the connection is directly disconnected.

[0049] It should be noted that network connections are mobile and paths are self-organizing. When the communication environment deteriorates, drones can proactively improve the communication environment by moving their own positions.

[0050] Step S204: Decision on communication mode and network topology based on communication environment quality and UAV mission communication requirements, and topology reconstruction based on the decision results.

[0051] In this embodiment of the invention, communication environment quality includes base station signal strength, link packet loss rate, and interference level, while UAV mission communication requirements include whether high-definition video transmission is needed or only formation commands need to be sent. Based on the current communication environment quality and UAV mission communication requirements, the optimal communication mode and suitable network topology are determined. According to the decision result, topology reconstruction is triggered, dynamically adjusting the connection strength between each UAV, and moving their positions if necessary, to form a network structure that best matches the communication environment quality and UAV mission communication requirements. In this way, reliable communication is ensured for the UAV swarm in complex and dynamic environments.

[0052] The robust communication method for UAV swarms provided in this embodiment selects a communication mode based on the communication environment, abandons dependence on a single communication link, avoids paralysis of swarm communication due to single link failure, achieves link-level robustness, ensures continuous and stable communication, and autonomously optimizes the network topology by adaptively constructing the network topology, intelligently deciding the communication mode, and reconstructing the topology based on the decision results, thereby achieving dynamic optimization of UAV swarm communication and ensuring high reliability, robustness, and sustainability of UAV swarm communication.

[0053] This embodiment provides a survivable communication method for unmanned aerial vehicle (UAV) swarms, the process of which includes the following steps: Step S301: Determine the communication mode based on the communication environment.

[0054] Specifically, step S301 includes: Step S3011: If the communication environment is within the drone cluster and requires high-bandwidth data exchange, and there is 4G / 5G base station coverage, then select 4G / 5G communication as the communication mode. Step S3012: If the communication environment is a drone cluster that needs to exchange high-bandwidth data, and the drones are within line of sight and unobstructed, then select the broadband self-organizing network as the communication mode. Step S3013: If the communication environment is a drone cluster that needs to send key instructions and status information, and the communication distance between drones is within the long-distance communication range, there is interference, and the high-bandwidth link fails, then the communication mode is selected as long-distance narrowband communication. Step S3014: If there are available drones or ground equipment in the communication environment as relay nodes, then select opportunistic relay as the communication mode. Step S3015: If the communication environment is such that the drone is within visual range, then select the communication mode as no radio frequency communication.

[0055] In this embodiment of the invention, if the communication environment involves high-bandwidth data exchange such as high-definition video streams, large-scale remote sensing images, and real-time location information within a drone swarm, selecting a 4G / 5G network can provide a high-speed, low-latency transmission channel to meet the communication bandwidth requirements. However, this communication method is limited by the communication base stations in the specific environment; therefore, 4G / 5G communication must be selected in environments covered by 4G / 5G base stations.

[0056] If the communication environment requires high-bandwidth data exchange within a drone swarm, such as high-definition video streams, large-scale remote sensing images, and real-time location information, and does not rely on infrastructure such as base stations, the drones can self-organize into a communication network. When high-bandwidth data exchange is needed within a drone swarm, a broadband self-organizing network can provide a high-speed, low-latency transmission channel. However, this communication method has a limited effective communication distance, typically only suitable for drone interconnection within line-of-sight or short distances, and the signal is susceptible to obstruction and interference. Therefore, a broadband self-organizing network should be selected in an environment where drones are within line-of-sight and unobstructed.

[0057] When the communication environment involves a drone swarm that needs to send critical commands such as formation control instructions, as well as basic status information such as position, battery level, and speed, long-range narrowband communication offers advantages in terms of long communication distance and strong anti-interference capabilities. However, this communication method has extremely low bandwidth, typically supporting only tens to hundreds of bits of data transmission per second, making it unsuitable for transmitting large amounts of information such as video and images. Therefore, long-range narrowband communication is preferred when drones are within a long-range communication range, when interference exists, or when high-bandwidth links fail.

[0058] If other available drones or ground equipment in the drone swarm exist in the communication environment and can serve as temporary data relay nodes, then opportunistic relays are selected based on the site conditions to dynamically establish a link between the source node, relay node, and target node, in order to extend the communication coverage and bypass obstacles.

[0059] If the communication environment is such that the drone is within visual range, the drone's onboard sensors, such as onboard cameras and lidar, are used to observe the movement and light signals of other drones, indirectly obtaining commands. When other radio frequency communication methods are unavailable, radio frequency-free communication is selected to ensure that basic coordination does not fail.

[0060] By matching the corresponding communication mode according to different communication environments and business needs, the optimal allocation and on-demand use of communication resources can be achieved, eliminating the dependence on a single, continuous, stable, and high-bandwidth communication link, thereby improving the anti-interference, survivability, and environmental adaptability of UAV swarm communication.

[0061] Step S302: Based on the link quality monitoring results, switch the communication mode and adaptively adjust the transmission protocol parameters.

[0062] Please see details Figure 2 Step S202 of the illustrated embodiment will not be described again here.

[0063] Step S303: Determine the connection strength between the current drone and other drones in the drone cluster based on the current link quality, drone mission role, and drone location.

[0064] Please see details Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0065] Step S304: Decision on communication mode and network topology based on communication environment quality and UAV mission communication requirements, and topology reconstruction based on the decision results.

[0066] In some alternative implementations, the method further includes: Step S3041: Calculate the link quality index based on the beacon frames broadcast by the UAV; In step S3042, if the link quality index is lower than the preset link quality threshold, network topology reconstruction is triggered.

[0067] In this embodiment of the invention, the UAV periodically broadcasts beacon frames on a common control channel (such as narrowband), containing its own ID, location, communication capabilities, current load, etc. A Link Quality Indicator (LQI) is calculated based on the beacon frames, and a neighbor table is maintained accordingly, marking the link status of each neighbor as strongly connected, weakly connected, or disconnected. A pre-set link quality threshold, for example, 0.5, is used; if the calculated link quality index is lower than the pre-set threshold, network topology reconfiguration is triggered.

[0068] At this point, the Minimum Spanning Tree (MST) optimization algorithm is adopted to select the topology that can guarantee the connectivity of all drones and has the highest total link quality from all possible connection methods while ensuring network connectivity. Finally, the reconstruction is confirmed through a distributed consensus protocol (such as a simplified version of Raft).

[0069] The robust communication method for UAV swarms provided in this embodiment automatically triggers network topology reconstruction based on the link quality index, enabling rapid response in the early stages of link degradation, preventing the escalation of faults, and improving the robustness and adaptability of the UAV swarm network.

[0070] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0071] The following is a detailed reference. Figure 3 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from memory 308 into random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0072] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0073] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from memory 308, or installed from ROM 302. When the computer program is executed by processor 301, it performs the functions defined in the survivability communication method for unmanned aerial vehicle swarms according to embodiments of the present invention.

[0074] Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0075] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the survivable communication method for UAV swarms shown in the above embodiments is implemented.

[0076] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0077] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and all such modifications and variations fall within the scope defined by the appended invention.

Claims

1. A survivable communication system for unmanned aerial vehicle (UAV) swarms, characterized in that, The system includes: a multimodal heterogeneous communication subsystem and a dynamic network topology subsystem, wherein... The multimodal heterogeneous communication subsystem includes a multimodal heterogeneous communication module and a unified communication management layer. The multimodal heterogeneous communication subsystem is used to select the multimodal heterogeneous communication module according to the communication environment, determine the communication mode, and monitor link quality, switch communication modes, and adaptively adjust transmission protocol parameters through the unified communication management layer. The communication modes include 4G / 5G communication, broadband self-organizing network, long-distance narrowband communication, opportunistic relay, and radio frequency-free communication. The dynamic network topology subsystem includes an adaptive network topology construction module and a communication mode decision module. The adaptive network topology construction module is used to determine the connection strength between the current UAV and other UAVs in the UAV cluster based on the current link quality, UAV mission role, and UAV location. The connection strength includes strong connection, weak connection, and disconnection. The communication mode decision module is used to determine the communication mode and network topology based on the communication environment quality and UAV mission communication requirements, and input the decision results into the adaptive network topology construction module for topology reconstruction.

2. The system according to claim 1, characterized in that, The unified communication management layer is used to receive link quality reports from multimodal heterogeneous communication modules, predict link quality using an exponentially weighted moving average algorithm, switch communication modes using a soft handover mechanism, and dynamically adjust transmission protocol parameters according to the current communication mode.

3. The system according to claim 1, characterized in that, The dynamic network topology subsystem uses a neighbor discovery and link maintenance protocol for topology reconstruction. The neighbor discovery and link maintenance protocol involves the UAV periodically broadcasting beacon frames, the receiver calculating the link quality index based on the beacon frames, and performing topology reconstruction if the link quality index is lower than a preset link quality threshold.

4. The system according to claim 1, characterized in that, The dynamic network topology subsystem adopts a link active optimization mechanism, which uses the potential field method to treat the communication quality gradient as a virtual force to determine the direction of movement and drive the UAV to move in the direction of movement while avoiding obstacles.

5. A sabotage-resistant communication method for unmanned aerial vehicle (UAV) swarms, characterized in that, The method, applied to a survivable communication system for unmanned aerial vehicle (UAV) swarms as described in any one of claims 1 to 4, comprises: The communication mode is determined based on the communication environment, and the communication mode includes 4G / 5G communication, broadband self-organizing network, long-distance narrowband communication, opportunistic relay, and radio frequency-free communication; Based on the link quality monitoring results, switch communication modes and adaptively adjust transmission protocol parameters; The connection strength between the current drone and other drones in the drone cluster is determined based on the current link quality, drone mission role, and drone location. The connection strength includes strong connection, weak connection, and disconnection. The communication mode and network topology are determined based on the quality of the communication environment and the communication requirements of the UAV mission, and the topology is reconstructed based on the decision results.

6. The method according to claim 5, characterized in that, The step of determining the communication mode based on the communication environment includes: If the communication environment is within a drone swarm that requires high-bandwidth data exchange and is covered by 4G / 5G base stations, then the communication mode should be 4G / 5G communication. If the communication environment is a drone cluster that requires high-bandwidth data exchange, and the drones are within line of sight and unobstructed, then the communication mode should be broadband self-organizing network. If the communication environment is a drone swarm that needs to send critical commands and status information, and the communication distance between drones is within the long-distance communication range, there is interference, or the high-bandwidth link fails, then the communication mode should be long-distance narrowband communication. If available drones or ground equipment exist in the communication environment as relay nodes, then the communication mode is selected as opportunistic relay; If the communication environment is such that the drone is within visual range, then select the communication mode as non-radio frequency communication.

7. The method according to claim 5, characterized in that, The method further includes: Calculate the link quality index based on the beacon frames broadcast by the drone; If the link quality index is lower than the preset link quality threshold, network topology reconstruction will be triggered.

8. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the sabotage-resistant communication method for unmanned aerial vehicle swarms as described in any one of claims 5 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the survivable communication method for unmanned aerial vehicle swarms as described in any one of claims 5 to 7.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the sabotage-resistant communication method for unmanned aerial vehicle swarms as described in any one of claims 5 to 7.

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