A secure, efficient and dynamic UANATS data transmission method

Abstract

The present invention discloses a secure, efficient and dynamic UANATS data transmission method, which relates to the technical field of data transmission. First, obtain and analyze the status information of each communication node of the unmanned aerial vehicles (UAVs) in the UANATS network to evaluate its stability; then, cluster the UAVs based on the status stability evaluation value and select the cluster heads, and further allocate the broadcast frequencies; finally, monitor and analyze the data transmission process of each UAV cluster, dynamically adjust the clustering according to the evaluation results, and by realizing the flexible adjustment of clustering and the optimal selection of cluster heads, the efficiency and security of data transmission are effectively improved. The continuous monitoring and analysis of the data transmission process contribute to enhancing the stability and reliability of the UANATS network, thereby improving the efficiency and quality of data transmission, and also providing strong support for the autonomous management and intelligent optimization of the UAV network.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and specifically provides a secure, efficient and dynamic UANATS data transmission method. Background Art

[0002] In the context of the increasing popularity of distributed systems and microservices architectures, by combining data collection from untrusted endpoints with the efficiency and reliability of the NATS messaging system, and through the implementation of strict encryption technologies, authentication and authorization mechanisms, as well as dynamic configuration and expansion capabilities, secure, efficient and dynamic transmission of data in complex network environments is achieved to meet the high requirements for data transmission performance and security in different application scenarios.

[0003] For example, the invention patent with publication number CN108307448B discloses a data transmission method and device. The method includes: when the air interface supports multiple connections, establishing a mapping relationship between the uplink and downlink PDU flows and one or more air interface RB bearers. In the downlink direction, the master base station can dynamically select the transmission path of the data packets of the downlink PDU flow; in the uplink direction, the UE can dynamically select the air interface RB bearer for transmitting the data packets of the uplink PDU flow, and the master base station can control that some PDU flows can only be transmitted through the air interface RB bearers of specific master base stations or secondary base stations, so as to solve the QoS and user plane data transmission in the case of 5G multiple connections.

[0004] For example, the invention patent with publication number CN102316516B discloses a method for constructing an LTE uplink data transmission structure. A PDCP SDU cache is added at the packet data convergence protocol layer to store the PDCP SDU IP packet pointers that have not been converted into PDCP PDUs and are transmitted from the upper layer; at the radio link control layer, the RLC SDU cache is deleted, and only the RLC PDU cache is retained. The RLC PDU cache stores the RLC PDUs to be confirmed, and the data assembled into the RLC PDUs is obtained from the PDCP PDU cache.

[0005] Based on the above findings, in the existing technical solutions, there may be problems with the unstable states of each communication node of the unmanned aerial vehicle, which may lead to the leakage of private data, the destruction of data, communication interference, and the failure of the unmanned aerial vehicle to execute tasks. Summary of the Invention

[0006] Aiming at the deficiencies of the prior art, the present invention provides a secure, efficient and dynamic UANATS data transmission method, which solves the problems described in the above background art.

[0007] To achieve the above object, the present invention is implemented through the following technical solutions: A safe, efficient and dynamic UANATS data transmission method, including obtaining the status information of each communication node of the unmanned aerial vehicle (UAV) in the UANATS network, and analyzing the status information of each communication node of the UAV to obtain the status stability evaluation value of each communication node of the UAV.

[0008] According to the status stability evaluation value of each communication node of the UAV, cluster each communication node of the UAV in the UANATS network to obtain each UAV cluster of the UANATS network, screen the cluster heads of each UAV cluster of the UANATS network, and adjust the broadcast frequency of the UAVs in the UANATS network.

[0009] Monitor and analyze the data transmission process of the cluster heads of each UAV cluster of the UANATS network and each communication node of the UAV to obtain the data transmission evaluation value of each UAV cluster of the UANATS network, and adjust the clustering of each communication node of the UAV in the UANATS network according to the data transmission evaluation value of each UAV cluster of the UANATS network.

[0010] Further, the status information of each communication node of the UAV includes: the signal strength of each communication node, the number of times of role change of each communication node, the packet loss rate of each communication node, and the interference power of each communication node.

[0011] Further, extract the interference power, signal strength, number of times of role change, and packet loss rate of each communication node of the UAV, and process to obtain the status stability evaluation value of each communication node of the UAV. The status stability evaluation value of each communication node of the UAV is used to evaluate the communication stability of the UAV.

[0012] Extract the status stability evaluation value of each communication node of the UAV and compare it with the status stability evaluation value threshold of the communication node in the database. If the status stability evaluation value of a certain communication node of the UAV is higher than or equal to the status stability evaluation value threshold of the communication node in the database, continuously monitor the status information of each communication node of the UAV; if the status stability evaluation value of a certain communication node of the UAV is lower than the status stability evaluation value threshold of the communication node in the database, adjust the communication frequency of the communication node of the UAV.

[0013] Further, extract the status stability evaluation value of each communication node of the UAV and compare it with the status stability evaluation threshold of each communication node of the UAV stored in the database. If the status stability evaluation value of a certain communication node of the UAV is higher than or equal to the status stability evaluation threshold of each communication node of the UAV, mark the communication node of the UAV as a candidate cluster head, thereby obtaining each candidate cluster head, and divide each UAV cluster according to the preset number limit of UAVs within the cluster.

[0014] Further, broadcast the cluster head information of each candidate cluster head to each neighbor node. Each neighbor node receives and analyzes the cluster head information of each candidate cluster head. The cluster head information of each candidate cluster head includes the remaining total energy, communication delay, and bandwidth. Combining with the status stability evaluation value of each candidate cluster head of the UAV, the status evaluation value of each candidate cluster head of each neighbor node is processed. Sort the status evaluation values of each candidate cluster head of each neighbor node, and select the candidate cluster head node ranked first within each UAV cluster of each neighbor node as the cluster head of each neighbor node, thereby obtaining the cluster heads of each UAV cluster in the UANATS network.

[0015] Further, preset each monitoring time period. During each monitoring time period, count the number of UAVs in each UAV cluster and monitor the energy efficiency and moving distance of each UAV. Take the average value of the moving distance and energy efficiency of each UAV in each UAV cluster respectively to obtain the average moving distance and average energy efficiency of the UAVs in each UAV cluster. Combining with the number of UAVs in each UAV cluster, the broadcast stability value of each UAV cluster in the UANATS network during each monitoring time period is processed.

[0016] Compare the broadcast stability value of each UAV cluster in the UANATS network during each monitoring time period with the broadcast stability threshold stored in the database. If the broadcast stability value of a certain UAV cluster during a certain monitoring time period is higher than or equal to the broadcast stability threshold stored in the database, it means that the broadcast frequency of this UAV cluster does not need to be adjusted. If the broadcast stability value of a certain UAV cluster during a certain monitoring time period is lower than the broadcast stability threshold stored in the database, the broadcast frequency of this UAV cluster is adjusted and allocated.

[0017] Further, during each monitoring time period, monitor and analyze the data transmission process of each communication node in each UAV cluster of the UANATS network to obtain the communication data of each communication node in each UAV cluster of the UANATS network. The communication data of each communication node in each UAV cluster of the UANATS network includes: data transmission rate, retransmission rate.

[0018] Further, extract the data transmission rate and retransmission rate of each communication node in each UAV cluster of the UANATS network, and combine the broadcast stability value of each UAV cluster in the UANATS network during each monitoring time period and the status evaluation value of each communication node in each UAV cluster to process the data transmission evaluation value of each UAV cluster in the UANATS network. The data transmission evaluation value of each UAV cluster in the UANATS network is used to evaluate the network stability of each UAV cluster.

[0019] Further, the data transmission evaluation values of each UAV cluster in the UANATS network are extracted and matched with the network stability of the UAV clusters corresponding to each interval of the data transmission evaluation values stored in the database, and the network stability of each UAV cluster is obtained. The network stability of the UAV cluster includes: highly stable, moderately stable, and generally stable.

[0020] Extract the network stability of each UAV cluster in the UANATS network. When the network stability of a certain UAV cluster is highly stable, continuously monitor and analyze the data transmission process of the communication nodes in the UAV cluster.

[0021] When the network stability of a certain UAV cluster is moderately stable and generally stable, adjust the number of communication nodes in the UAV cluster and re-elect the cluster head.

[0022] Further, the data transmission evaluation values of each UAV cluster in the UANATS network, the specific analysis process is as follows:

[0023] ;

[0024] In the formula, represents the data transmission evaluation value of the i-th UAV cluster in the UANATS network, represents the broadcast stability value of the i-th UAV cluster in the q-th monitoring time period, represents the evaluation value of the x-th candidate cluster head status of the s-th neighbor node represents the data transmission rate of the j-th communication node in the i-th UAV cluster represents the retransmission rate of the j-th communication node in the i-th UAV cluster, represents the reference value of the data transmission rate of the set communication node, represents the maximum allowable value of the retransmission rate of the set communication node, e is the natural constant, represents the weight factor corresponding to the broadcast stability value of the set UAV cluster, represents the weight factor corresponding to the set data transmission rate represents the weight factor corresponding to the set retransmission rate, represents the weight factor corresponding to the evaluation value of the set candidate cluster head status, i represents the number of each UAV cluster , m represents the total number of UAV clusters, j represents the number of each communication node, , n represents the total number of communication nodes, q represents the number of each monitoring time period, , r represents the total number of monitoring time periods, s represents the number of each neighbor node, , p represents the total number of neighbor nodes, x represents the number of each candidate cluster head, , y represents the total number of candidate cluster heads.

[0025] The present invention has the following beneficial effects:

[0026] (1) The present invention obtains and analyzes the status information of each communication node of the unmanned aerial vehicles (UAVs) in the UANATS network to evaluate its stability; then, based on the status stability evaluation value, the UAVs are clustered and cluster heads are selected, and then the broadcast frequencies are allocated; finally, the data transmission processes of each UAV cluster are monitored and analyzed, and the clustering is dynamically adjusted according to the evaluation results. By realizing the flexible adjustment of clustering and the optimal selection of cluster heads, the efficiency and security of data transmission are effectively improved. The continuous monitoring and analysis of the data transmission process contribute to enhancing the stability and reliability of the UANATS network, thereby improving the efficiency and quality of data transmission, and also providing strong support for the autonomous management and intelligent optimization of the UAV network;

[0027] (2) The present invention processes the interference power, signal strength, number of role changes, and packet loss rate of each communication node of the UAVs to obtain the status stability evaluation value of each communication node of the UAVs, evaluates its status stability, compares it with the threshold value in the database, and adjusts the communication frequency of the unstable nodes; at the same time, according to the status stability evaluation value, candidate cluster heads are selected, and the UAV nodes are organized to form a cluster network;

[0028] (3) The present invention receives and analyzes the remaining total energy, communication delay, and bandwidth of the candidate cluster heads by each neighbor node, combines the status stability evaluation value, evaluates and sorts the candidate cluster heads, selects the optimal one as the cluster head, and forms the UAV cluster structure of the UANATS network. By dynamically selecting the optimal node as the cluster head, the reliability and efficiency of data transmission are significantly improved, and at the same time, the resource allocation is optimized, ensuring the security, efficiency, and dynamic adaptability of the UANATS data transmission network;

[0029] (4) The present invention presets each monitoring time period, counts the number of UAVs in the UAV cluster, monitors the energy efficiency and moving distance in each cluster, calculates the average moving distance, combines the number of UAVs and the energy efficiency to obtain the broadcast stability value of each UAV cluster of the UANATS network in each monitoring time period, compares it with the broadcast stability threshold value, and adjusts the broadcast frequency allocation of the UAV cluster according to the result;

[0030] (5) The present invention monitors the data transmission processes of the communication nodes of each UAV cluster of the UANATS network, combines the data transmission rate and retransmission rate of each communication node, and combines the broadcast stability value of each UAV cluster of the UANATS network and the status evaluation value of each communication node in each UAV cluster to obtain the data transmission evaluation value of each UAV cluster of the UANATS network to evaluate the network stability, and takes corresponding monitoring or adjustment measures according to the network stability.

[0031] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic flowchart of the method of the present invention.

[0033] Figure 2 It is a curve showing the change of the average moving distance of the unmanned aerial vehicle of the present invention - the broadcast stability value of the unmanned aerial vehicle cluster of the UANATS network. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inner", "perimeter", etc. indicating the orientation or positional relationship are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0036] Please refer to Figure 1 , the embodiments of the present invention provide a technical solution: a secure, efficient and dynamic UANATS data transmission method, including obtaining the status information of each communication node of the unmanned aerial vehicle in the UANATS network, and analyzing the status information of each communication node of the unmanned aerial vehicle to obtain the status stability evaluation value of each communication node of the unmanned aerial vehicle.

[0037] According to the status stability evaluation value of each communication node of the unmanned aerial vehicle, cluster each communication node of the unmanned aerial vehicle in the UANATS network to obtain each unmanned aerial vehicle cluster of the UANATS network, and screen the cluster heads of each unmanned aerial vehicle cluster of the UANATS network to adjust the broadcast frequency of the unmanned aerial vehicle in the UANATS network.

[0038] Monitor and analyze the data transmission process of the cluster heads of each unmanned aerial vehicle cluster of the UANATS network and each communication node of the unmanned aerial vehicle to obtain the data transmission evaluation value of each unmanned aerial vehicle cluster of the UANATS network, and adjust the clustering of each communication node of the unmanned aerial vehicle in the UANATS network according to the data transmission evaluation value of each unmanned aerial vehicle cluster of the UANATS network.

[0039] It should be noted that the state information of each communication node of the unmanned aircraft in the UANATS (Unmanned Aircraft Networked and Autonomous Tactical System) network is obtained and analyzed to evaluate its stability; then, the unmanned aircraft is clustered and cluster heads are selected based on the state stability evaluation value, and then the broadcast frequency is allocated; finally, the data transmission process of each unmanned aircraft cluster is monitored and analyzed, and the clustering is dynamically adjusted according to the evaluation results. By realizing the flexible adjustment of clustering and the optimal selection of cluster heads, the efficiency and security of data transmission are effectively improved, providing strong support for the autonomous management and intelligent optimization of the unmanned aircraft network.

[0040] Specifically, the state information of each communication node of the unmanned aircraft includes: the signal strength of each communication node, the number of times the role of each communication node changes, the packet loss rate of each communication node, and the interference power of each communication node.

[0041] It should be noted that a wireless signal detector is used to detect the signal strength of each communication node of the unmanned aircraft; the number of times the role of each communication node changes refers to the number of times the role of each communication node changes during the execution of tasks in the UANATS network. The state log of the unmanned aircraft communication node records the number of times the role state changes; network testing tools (such as ping, traceroute, etc.) can be used to detect the loss of data packets during transmission, so as to obtain the packet loss rate; a power meter is used to measure the power of the received interference signal.

[0042] Specifically, the interference power, signal strength, number of times the role of each communication node changes, and packet loss rate of each communication node of the unmanned aircraft are extracted, and the state stability evaluation value of each communication node of the unmanned aircraft is processed to evaluate the communication stability of the unmanned aircraft.

[0043] The state stability evaluation value of each communication node of the unmanned aircraft is extracted and compared with the state stability evaluation value threshold of the communication node in the database. If the state stability evaluation value of a certain communication node of the unmanned aircraft is higher than or equal to the state stability evaluation value threshold of the communication node in the database, the state information of each communication node of the unmanned aircraft is continuously monitored; if the state stability evaluation value of a certain communication node of the unmanned aircraft is lower than the state stability evaluation value threshold of the communication node in the database, the communication frequency of the communication node of the unmanned aircraft is adjusted.

[0044] It should be noted that the specific analysis process of the state stability evaluation value of each communication node of the unmanned aircraft is as follows:

[0045] ;

[0046] In the formula, represents the stable evaluation value of the j-th communication node of the UAV, represents the interference power of the j-th communication node of the UAV, represents the signal strength of the j-th communication node of the UAV, represents the number of role changes of the j-th communication node of the UAV, represents the packet loss rate of the j-th communication node of the UAV, represents the reference value of the interference power of the set communication node, represents the reference value of the signal strength of the set communication node, represents the reference value of the number of role changes of the set communication node, represents the reference value of the packet loss rate of the set communication node, represents the correction factor corresponding to the interference power of the set communication node, represents the correction factor corresponding to the signal strength of the set communication node, represents the correction factor corresponding to the number of role changes of the set communication node, represents the correction factor corresponding to the packet loss rate of the set communication node, where j represents the number of each communication node, , and n represents the total number of communication nodes.

[0047] It should be noted that there is a correlation among the interference power of each communication node of the UAV, the signal strength of each communication node, the number of role changes of each communication node, and the packet loss rate of each communication node. The greater the interference power, the stronger the signal interference to the communication node of the UAV, resulting in a decrease in signal strength; frequent role changes will cause a burden on the communication node, thereby affecting the stability of its signal strength; a large interference power may cause the communication link between communication nodes to be unstable, resulting in the need for the node to change its role frequently, leading to an increase in the number of role changes of the node; an increase in interference power will cause the communication link to be unstable, thereby increasing the packet loss rate. It can be seen that the stable evaluation value of each communication node of the UAV is jointly processed by the interference power of each communication node of the UAV, the signal strength of each communication node, the number of role changes of each communication node, and the packet loss rate of each communication node;

[0048] It is the correction factor corresponding to the interference power of the communication node preset in the database, which represents the numerical value of the influence degree of the interference power of the communication node on the state stability evaluation value of each communication node of the UAV. When in use, the correction factor corresponding to the interference power of the communication node can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the interference power of the communication node and the correction factor corresponding to the interference power of the communication node preset in the database form a mapping set. Input the real-time interference power of the communication node into the mapping set to obtain the correction factor corresponding to the interference power of the communication node, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0049] It is the correction factor corresponding to the signal strength of the communication node preset in the database, which represents the numerical value of the influence degree of the signal strength of the communication node on the state stability evaluation value of each communication node of the UAV. When in use, the correction factor corresponding to the signal strength of the communication node can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the signal strength of the communication node and the correction factor corresponding to the signal strength of the communication node preset in the database form a mapping set. Input the real-time signal strength of the communication node into the mapping set to obtain the correction factor corresponding to the signal strength of the communication node, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0050] It is the correction factor corresponding to the number of times of communication node role change preset in the database, which represents the numerical value of the influence degree of the number of times of communication node role change on the state stability evaluation value of each communication node of the UAV. When in use, the correction factor corresponding to the number of times of communication node role change can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the number of times of communication node role change and the correction factor corresponding to the number of times of communication node role change preset in the database form a mapping set. Input the real-time number of times of communication node role change into the mapping set to obtain the correction factor corresponding to the number of times of communication node role change, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0051] It represents the correction factor corresponding to the packet loss rate of the preset communication nodes in the database, which is a numerical value indicating the influence degree of the packet loss rate of the communication nodes on the state stability evaluation value of each communication node of the UAV. When in use, the correction factor corresponding to the packet loss rate of the communication nodes can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the packet loss rate of the communication nodes and the correction factor corresponding to the packet loss rate of the preset communication nodes in the database form a mapping set. The real-time packet loss rate of the communication nodes is input into the mapping set to obtain the correction factor corresponding to the packet loss rate of the communication nodes, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1].

[0052] It should be noted that by extracting the interference power, signal strength, number of role changes and packet loss rate of each communication node of the UAV, the state stability evaluation value of each communication node of the UAV is processed. If the state stability evaluation value of a certain communication node of the UAV is higher than or equal to the state stability evaluation value threshold of the communication node in the database, the state information of each communication node of the UAV is continuously monitored, and there is no need to adjust the communication frequency; if the state stability evaluation value of a certain communication node of the UAV is lower than the state stability evaluation value threshold of the communication node in the database, the adjustment of the communication frequency of this communication node of the UAV includes extracting the current communication frequency of this node and reducing it according to the set communication frequency adjustment amplitude. After each reduction, the state stability evaluation value of this communication node of the UAV is recalculated until the state stability evaluation value of this communication node of the UAV is higher than or equal to the state stability evaluation value threshold of the communication node in the database. For example: assuming that the set communication frequency adjustment amplitude is 10%, when the state stability evaluation value of a certain communication node of the UAV is lower than the state stability evaluation value threshold of the communication node in the database, the communication frequency of this communication node is reduced by 10%. After the adjustment, the state stability evaluation value of this communication node of the UAV is recalculated. If it is higher than or equal to the state stability evaluation value threshold of the communication node, the adjustment ends. If it is lower than the state stability evaluation value threshold of the communication node, the adjustment continues until the state stability evaluation value of this communication node of the UAV is higher than or equal to the state stability evaluation value threshold of the communication node in the database.

[0053] It should be noted that evaluating the state stability of the UAV communication nodes and dynamically adjusting the communication frequency to cope with unstable situations ensure the security and efficiency of data transmission. At the same time, this method can continuously monitor the state information of the communication nodes, provide a strong guarantee for the stable operation of the UAV, and effectively improve the overall performance and reliability of the UAV communication network system.

[0054] Specifically, extract the state stability evaluation values of each communication node of the UAV, and compare them with the state stability evaluation thresholds of each communication node of the UAV stored in the database. If the state stability evaluation value of a certain communication node of the UAV is higher than or equal to the state stability evaluation threshold of each communication node of the UAV, then mark this communication node of the UAV as a candidate cluster head, and thus obtain each candidate cluster head. According to the preset limit on the number of UAVs within a cluster, divide each UAV cluster.

[0055] Broadcast the cluster head information of each candidate cluster head to each neighbor node. Each neighbor node receives and analyzes the cluster head information of each candidate cluster head. The cluster head information of each candidate cluster head includes the remaining total energy, communication delay, and bandwidth. Combining with the state stability evaluation value of each candidate cluster head of the UAV, process to obtain the state evaluation value of each candidate cluster head of each neighbor node. Sort the state evaluation values of each candidate cluster head of each neighbor node, and select the candidate cluster head node ranked first within each UAV cluster as the cluster head of each neighbor node. Thus, obtain the cluster heads of each UAV cluster in the UANATS network.

[0056] It should be noted that the specific steps for dividing each UAV cluster are to extract the state stability evaluation values of each communication node of the UAV, compare them with the state stability evaluation thresholds of each communication node of the UAV stored, mark the UAV communication nodes whose state stability evaluation values are higher than or equal to the state stability evaluation thresholds of each communication node of the UAV as candidate cluster heads. Each candidate cluster head broadcasts its signal strength and position coordinates to other ordinary nodes around. Each ordinary node selects the cluster head with the strongest signal and the shortest distance as the cluster head of the cluster to be joined. If the cluster heads with the strongest signal and the shortest distance point to different candidate cluster heads respectively, select the candidate cluster head with the strongest signal as the cluster head of the cluster to be joined. If the signal strengths are the same, select the cluster head with the shortest distance as the cluster head of the cluster to be joined, and send a join request. After each cluster head receives the join request from an ordinary node, check whether the number of UAVs in its cluster has reached the preset limit on the number of UAVs within a cluster. If not, the cluster head confirms the join request of this ordinary node, adds this node to its cluster member list, and sends a confirmation message to this ordinary node, notifying it that it has successfully joined the cluster; if the number of UAVs in the cluster has reached the preset limit, then reject the join request of this ordinary node. After this ordinary node receives the rejection command sent by the cluster head, mark this cluster head, and re-send a join request to other cluster heads until it is rejected by all cluster heads or successfully joins a cluster.

[0057] It should be noted that each neighbor node refers to other nodes that can directly communicate within the communication range of the candidate cluster head. During the cluster head selection process, the neighbor node decides whether to join a certain cluster according to the information broadcast by the candidate cluster head.

[0058] It should be noted that the total remaining energy refers to the total energy that the battery can still release in the current state, which can be obtained by monitoring the remaining battery charge. UAVs are usually equipped with a battery management system (BMS), which can monitor the current state of the battery in real time. The remaining battery charge of each candidate cluster head obtained is the total remaining energy of the candidate cluster head. By using a network performance monitoring tool (such as PingPlotter), the communication delay of communication nodes can be monitored. By using a bandwidth measurement tool (such as iperf, Speedtest), the bandwidth of communication nodes can be measured.

[0059] It should be noted that the state evaluation values of each candidate cluster head of each neighbor node are specifically analyzed as follows:

[0060] ;

[0061] In the formula, represents the state evaluation value of the x-th candidate cluster head of the s-th neighbor node, represents the state stability evaluation value of the x-th candidate cluster head of the UAV, represents the total remaining energy of the x-th candidate cluster head of the s-th neighbor node, represents the communication delay of the x-th candidate cluster head of the s-th neighbor node, the bandwidth of the x-th candidate cluster head of the s-th neighbor node, represents the reference value of the energy of the set candidate cluster head, represents the maximum allowable value of the communication delay of the set communication node, represents the reference value of the bandwidth of the set communication node, e is the natural constant, represents the weight factor corresponding to the state stability evaluation value of the set communication node, represents the weight factor corresponding to the total remaining energy of the set candidate cluster head, represents the weight factor corresponding to the communication delay of the set communication node, represents the weight factor corresponding to the bandwidth of the set communication node, s represents the number of each neighbor node, , p represents the total number of neighbor nodes, x represents the number of each candidate cluster head, , y represents the total number of candidate cluster heads;

[0062] It is the weight factor corresponding to the state stability evaluation value of the preset communication node in the database, which represents the numerical value of the influence degree of the state stability evaluation value of the communication node on the state evaluation values of each candidate cluster head of each neighbor node. When in use, the weight factor corresponding to the state stability evaluation value of the communication node can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the state stability evaluation value of the communication node and the weight factor corresponding to the state stability evaluation value of the preset communication node in the database form a mapping set. Inputting the real-time state stability evaluation value of the communication node into the mapping set to obtain the weight factor corresponding to the state stability evaluation value of the communication node, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0063] It is the weight factor corresponding to the remaining total energy of the preset candidate cluster head in the database, which represents the numerical value of the influence degree of the remaining total energy of the candidate cluster head on the state evaluation values of each candidate cluster head of each neighbor node. When in use, the weight factor corresponding to the remaining total energy of the candidate cluster head can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the remaining total energy of the candidate cluster head and the weight factor corresponding to the remaining total energy of the preset candidate cluster head in the database form a mapping set. Inputting the real-time remaining total energy of the candidate cluster head into the mapping set to obtain the weight factor corresponding to the remaining total energy of the candidate cluster head, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0064] It is the weight factor corresponding to the communication delay of the preset communication node in the database, which represents the numerical value of the influence degree of the communication delay of the communication node on the state evaluation values of each candidate cluster head of each neighbor node. When in use, the weight factor corresponding to the communication delay of the communication node can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the communication delay of the communication node and the weight factor corresponding to the communication delay of the preset communication node in the database form a mapping set. Inputting the real-time communication delay of the communication node into the mapping set to obtain the weight factor corresponding to the communication delay of the communication node, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0065] The weight factor corresponding to the bandwidth of the preset communication node in the database, which represents the degree of influence of the bandwidth of the communication node on the evaluation values of the candidate cluster head states of each neighbor node. When in use, the weight factor corresponding to the bandwidth of the communication node can be directly obtained from the database, and its corresponding relationship can be a preset mapping relationship. For example, the bandwidth of the communication node and the weight factor corresponding to the bandwidth of the preset communication node in the database form a mapping set. Inputting the real-time bandwidth of the communication node into the mapping set to obtain the weight factor corresponding to the bandwidth of the communication node, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1].

[0066] It should be noted that by monitoring the cluster head information of each candidate cluster head, including the remaining total energy, communication delay, and bandwidth, and combining the state stability evaluation value of the candidate cluster head, the evaluation value of the candidate cluster head state of each neighbor node is obtained. Sorting the evaluation values of the candidate cluster head states of each neighbor node in descending order and selecting the candidate cluster head ranked first within each UAV cluster as the cluster head helps to ensure that the UAV cluster can maintain efficient and stable communication under various conditions.

[0067] Specifically, preset each monitoring time period. During each monitoring time period, count the number of UAVs within each UAV cluster and monitor the energy efficiency and moving distance of each UAV. Take the average value of the moving distance and energy efficiency of each UAV within each UAV cluster respectively to obtain the average moving distance of the UAVs within each UAV cluster and the average energy efficiency of the UAVs. Combine the number of UAVs within each UAV cluster and process to obtain the broadcast stability value of each UAV cluster of the UANATS network in each monitoring time period.

[0068] Compare the broadcast stability value of each UAV cluster of the UANATS network in each monitoring time period with the broadcast stability threshold stored in the database. If the broadcast stability value of a certain UAV cluster in a certain monitoring time period is higher than or equal to the broadcast stability threshold stored in the database, it means that the broadcast frequency of this UAV cluster does not need to be adjusted. If the broadcast stability value of a certain UAV cluster in a certain monitoring time period is lower than the broadcast stability threshold stored in the database, then adjust and allocate the broadcast frequency of this UAV cluster.

[0069] It should be noted that through the UAV cluster management system, the composition and changes of each UAV cluster are tracked and recorded in real time to obtain the number of UAVs in each UAV cluster; through the GPS positioning system, the flight trajectory and position information of the UAVs are recorded to obtain the moving distance of the UAVs in each monitoring time period; the energy efficiency is the ratio of the output power to the input power of the UAV. Use a power meter to directly measure the input power and output power of the UAV, and divide the output power by the input power to obtain the energy efficiency of the UAV.

[0070] It should be noted that the broadcast stability values of each UAV cluster in the UANATS network for each monitoring time period are analyzed as follows:

[0071] ;

[0072] In the formula, represents the broadcast stability value of the i-th UAV cluster in the UANATS network for the q-th monitoring time period, represents the number of UAVs in the i-th UAV cluster for the q-th monitoring time period, represents the number of UAVs in the i-th UAV cluster for the (q - 1)-th monitoring time period, represents the energy efficiency of the i-th UAV cluster for the q-th monitoring time period, represents the average moving distance of the UAVs in the i-th UAV cluster for the q-th monitoring time period, represents the allowable value of the change in the number of UAVs in the set UAV cluster, represents the reference value of the energy efficiency of the set UAV cluster, represents the maximum allowable value of the average moving distance of the UAVs in the set UAV cluster, represents the correction factor corresponding to the set number of UAVs, represents the correction factor corresponding to the energy efficiency of the set UAV cluster, represents the correction factor corresponding to the average moving distance of the UAVs in the set UAV cluster. i represents the number of each UAV cluster , m represents the total number of UAV clusters, q represents the number of each monitoring time period, , r represents the total number of monitoring time periods.

[0073] It should be noted that there is a correlation among the average moving distance of the UAVs in each UAV cluster, the number of UAVs in each UAV cluster, and the energy efficiency of each UAV within each monitoring time period. The shorter the moving distance of the UAV, the less energy it consumes, and the higher the energy efficiency. The average moving distance of the UAVs and the number of UAVs often affect each other. For example, when monitoring a large area, it may be necessary to increase the number of UAVs to improve the coverage rate. Thus, it can be seen that the broadcast stability value of each UAV cluster in the UANATS network for each monitoring time period is jointly determined by the average moving distance of the UAVs in each UAV cluster, the number of UAVs in each UAV cluster, and the energy efficiency of each UAV within each monitoring time period;

[0074] The correction factor corresponding to the preset number of UAVs in the database, which represents the degree of influence of the number of UAVs on the broadcast stability value of each UAV cluster in the UANATS network during each monitoring period. When in use, the correction factor corresponding to the number of UAVs can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the number of UAVs and the correction factor corresponding to the preset number of UAVs in the database form a mapping set. Inputting the real-time number of UAVs into the mapping set to obtain the correction factor corresponding to the number of UAVs, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0075] The correction factor corresponding to the energy efficiency of the UAV cluster preset in the database, which represents the degree of influence of the energy efficiency of the UAV cluster on the broadcast stability value of each UAV cluster in the UANATS network during each monitoring period. When in use, the correction factor corresponding to the energy efficiency of the UAV cluster can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the energy efficiency of the UAV cluster and the correction factor corresponding to the preset energy efficiency of the UAV cluster in the database form a mapping set. Inputting the real-time energy efficiency of the UAV cluster into the mapping set to obtain the correction factor corresponding to the energy efficiency of the UAV cluster, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1].

[0076] The correction factor corresponding to the average moving distance of the UAVs within the UAV cluster preset in the database, which represents the degree of influence of the average moving distance of the UAVs within the UAV cluster on the broadcast stability value of each UAV cluster in the UANATS network during each monitoring period. When in use, the correction factor corresponding to the average moving distance of the UAVs within the UAV cluster can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the average moving distance of the UAVs within the UAV cluster and the correction factor corresponding to the preset average moving distance of the UAVs within the UAV cluster in the database form a mapping set. Inputting the real-time average moving distance of the UAVs within the UAV cluster into the mapping set to obtain the correction factor corresponding to the average moving distance of the UAVs within the UAV cluster, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1].

[0077] As Figure 2 shown, Figure 2Represents the average moving distance of the UAV - the broadcast stability value curve of the UAV clusters in the UANATS network. The x - axis represents the average moving distance of the UAVs in the \(i\) - th UAV cluster during the \(q\) - th monitoring time period, and the y - axis represents the broadcast stability value of the \(i\) - th UAV cluster in the UANATS network during the \(q\) - th monitoring time period. Three groups of different example parameters are defined in the figure, corresponding to different situations of the three curves, represented by solid lines, dashed lines, and dotted lines respectively, and the corresponding curve labels are a, b, c. Assume the number of UAVs in the \(i\) - th UAV cluster during the \(q\) - th monitoring time period = 6 (units), and the number of UAVs in the \(i\) - th UAV cluster during the \((q - 1)\) - th monitoring time period = 3 (units), the allowable value of the change in the number of UAVs in the set UAV cluster = 2 (units), the reference value of the energy efficiency of the set UAV cluster = 1.0 (W), the maximum allowable value of the average moving distance of the UAVs in the set UAV cluster = 10 (meters), the correction factor corresponding to the set number of UAVs = 0.3, the correction factor corresponding to the energy efficiency of the set UAV cluster = 0.5, the correction factor corresponding to the average moving distance of the UAVs in the set UAV cluster = 0.2. When the energy efficiency of the \(i\) - th UAV cluster during the \(q\) - th monitoring time period is 0.6, the schematic diagram of the broadcast stability value of the \(i\) - th UAV cluster in the UANATS network during the \(q\) - th monitoring time period is shown as curve a. When the energy efficiency of the \(i\) - th UAV cluster during the \(q\) - th monitoring time period is 0.8, the schematic diagram of the broadcast stability value of the \(i\) - th UAV cluster in the UANATS network during the \(q\) - th monitoring time period is shown as curve b. When the energy efficiency of the \(i\) - th UAV cluster during the \(q\) - th monitoring time period is 1.0, the schematic diagram of the broadcast stability value of the \(i\) - th UAV cluster in the UANATS network during the \(q\) - th monitoring time period is shown as curve c.

[0078] As shown in Table 1, Table 1 shows the example data of the broadcast stability values of each UAV cluster in the UANATS network during each monitoring time period, where the broadcast stability values of each UAV cluster in the UANATS network and the average moving distance of the UAVs are listed.

[0079] Table 1 Example data of the broadcast stability values of each UAV cluster in the UANATS network

[0080] ;

[0081] As shown in Table 1, in a specific embodiment, assume the number of UAVs in the \(i\) - th UAV cluster during the \(q\) - th monitoring time period = 6 (units), and the number of UAVs in the \(i\) - th UAV cluster during the \((q - 1)\) - th monitoring time period = 3 (units), the allowable value of the number of drones in the set drone cluster = 2 (units), the reference value of the energy efficiency of the set drone cluster = 1.0 (W), the maximum allowable value of the average moving distance of the drones within the set drone cluster = 10 (meters), the correction factor corresponding to the set number of drones =  0.3, the correction factor corresponding to the energy efficiency of the set drone cluster = 0.5, the correction factor corresponding to the average moving distance of the drones within the set drone cluster = 0.2.

[0082] It should be noted that the adjustment and allocation of the broadcast frequency of the drone cluster include comparing the broadcast stability values of each drone cluster in the UANATS network during each monitoring time period with the preset broadcast stability threshold. When the broadcast stability value of a certain drone cluster in a certain monitoring time period is lower than the broadcast stability threshold stored in the database, a frequency band with less interference is identified through a spectrum analyzer, and the drone cluster is allocated to the frequency band with less frequency interference to reduce frequency interference.

[0083] Specifically, during each monitoring time period, the data transmission process of each communication node in each drone cluster of the UANATS network is monitored and analyzed to obtain the communication data of each communication node in each drone cluster of the UANATS network. The communication data of each communication node in each drone cluster of the UANATS network includes: data transmission rate, retransmission rate.

[0084] The data transmission rate and retransmission rate of each communication node in each drone cluster of the UANATS network are extracted, and combined with the broadcast stability value of each drone cluster in the UANATS network during each monitoring time period and the status evaluation value of each communication node in each drone cluster, to process and obtain the data transmission evaluation value of each drone cluster in the UANATS network. The data transmission evaluation value of each drone cluster in the UANATS network is used to evaluate the network stability of each drone cluster.

[0085] The data transmission evaluation value of each drone cluster in the UANATS network is extracted and matched with the network stability of the drone clusters corresponding to each interval of the data transmission evaluation value stored in the database to obtain the network stability of each drone cluster. The network stability of the drone cluster includes: highly stable, moderately stable, and generally stable.

[0086] The network stability of each drone cluster in the UANATS network is extracted. When the network stability of a certain drone cluster is highly stable, the data transmission process of the communication nodes within the drone cluster is continuously monitored and analyzed.

[0087] When the network stability of a certain UAV cluster is moderately stable or generally stable, adjust the number of communication nodes within the UAV cluster and re-elect the cluster head.

[0088] It should be noted that connect a network tester to the communication link of the UAV to monitor the data transmission rate in real time and obtain the data transmission rate of the communication nodes within the UAV cluster; use special test software (such as iperf, netperf) to record the number of sent data packets and retransmitted data packets, and divide the number of retransmitted data packets by the number of sent data packets to obtain the retransmission rate.

[0089] It should be noted that extract the data transmission evaluation values of each UAV cluster in the UANATS network and match them with the network stability of the UAV clusters corresponding to each interval of the data transmission evaluation values stored in the database. The network stability of each UAV cluster is preset in the database. When in use, the network stability of each UAV cluster can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the data transmission evaluation values of each UAV cluster and the network stability of the UAV clusters in the database form a mapping set. Input the real-time data transmission evaluation values of each UAV cluster into the mapping set to obtain the network stability of each UAV cluster, and the mapping relationship therein can be a one-to-one correspondence. The network stability of the UAV cluster includes: highly stable, moderately stable, generally stable. By evaluating the network stability of the UAV cluster, reliable data support is provided for subsequent adjustment and optimization.

[0090] It should be noted that adjusting the number of communication nodes within the UAV cluster and re-electing the cluster head includes: the communication nodes within each UAV cluster extract their own position parameters and the position parameters of the cluster head to obtain the distance between the communication node and the cluster head, compare the distance between the communication node and the cluster head with the distance threshold set in the database. If the distance between the communication node and the cluster head is greater than the distance threshold stored in the database, the communication node exits the UAV cluster, accepts the position information of each cluster head, joins the UAV cluster with the closest distance, re-monitor and collect the status information of the communication nodes within each adjusted UAV cluster, process to obtain the status stability evaluation value of each UAV communication node, and re-elect a new candidate cluster head, re-obtain the status evaluation values of each candidate cluster head of each neighbor node and sort them to elect a new cluster head.

[0091] Specifically, the data transmission evaluation value of each UAV cluster in the UANATS network, the specific analysis process is as follows:

[0092] ;

[0093] In the formula, represents the data transmission evaluation value of the i-th UAV cluster in the UANATS network, Denote the broadcast stability value of the $i$-th UAV cluster in the $q$-th monitoring time period. Denote the $x$-th candidate cluster head status evaluation value of the $s$-th neighbor node. Denote the data transmission rate of the $j$-th communication node in the $i$-th UAV cluster. Denote the retransmission rate of the $j$-th communication node in the $i$-th UAV cluster. Denote the reference value of the data transmission rate of the set communication node. Denote the maximum allowable value of the retransmission rate of the set communication node, where $e$ is the natural constant. Denote the weight factor corresponding to the broadcast stability value of the set UAV cluster. Denote the weight factor corresponding to the set data transmission rate. Denote the weight factor corresponding to the set retransmission rate. Denote the weight factor corresponding to the set candidate cluster head status evaluation value, where $i$ represents the number of each UAV cluster. , where $m$ represents the total number of UAV clusters, $j$ represents the number of each communication node. , where $n$ represents the total number of communication nodes, $q$ represents the number of each monitoring time period. , where $r$ represents the total number of monitoring time periods, $s$ represents the number of each neighbor node. , where $p$ represents the total number of neighbor nodes, $x$ represents the number of each candidate cluster head. , where $y$ represents the total number of candidate cluster heads.

[0094] [[ID=…]]It should be noted that there is a correlation between the data transmission rate and the retransmission rate. When the retransmission rate is higher, the retransmission of data packets will occupy the bandwidth originally used for transmitting new data, resulting in lower data transmission efficiency.

[0095] is the weight factor corresponding to the broadcast stability value of the UAV cluster set in the database, which represents the numerical value of the influence degree of the broadcast stability value of the UAV cluster on the data transmission evaluation value of each UAV cluster in the UANATS network. When in use, the weight factor corresponding to the broadcast stability value of the UAV cluster can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the broadcast stability value of the UAV cluster and the weight factor corresponding to the broadcast stability value of the UAV cluster preset in the database form a mapping set. Input the real-time broadcast stability value of the UAV cluster into the mapping set to obtain the weight factor corresponding to the broadcast stability value of the UAV cluster, where the mapping relationship can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1].

[0096] The weight factor corresponding to the data transmission rate set in the database, which represents the degree of influence of the data transmission rate on the data transmission evaluation value of each UAV cluster in the UANATS network. When used, the weight factor corresponding to the data transmission rate can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the data transmission rate and the weight factor corresponding to the pre-set data transmission rate in the database form a mapping set, and the real-time data transmission rate is input into the mapping set to obtain the weight factor corresponding to the data transmission rate. The mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0097] The weight factor corresponding to the retransmission rate set in the database, which represents the degree of influence of the retransmission rate on the data transmission evaluation value of each UAV cluster in the UANATS network. When used, the weight factor corresponding to the retransmission rate can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the retransmission rate and the weight factor corresponding to the pre-set retransmission rate in the database form a mapping set, and the real-time retransmission rate is input into the mapping set to obtain the weight factor corresponding to the retransmission rate. The mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1];

[0098] The weight factor corresponding to the candidate cluster head status evaluation value set in the database, which represents the degree of influence of the candidate cluster head status evaluation value on the data transmission evaluation value of each UAV cluster in the UANATS network. When used, the weight factor corresponding to the candidate cluster head status evaluation value can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the candidate cluster head status evaluation value and the weight factor corresponding to the pre-set candidate cluster head status evaluation value in the database form a mapping set, and the real-time candidate cluster head status evaluation value is input into the mapping set to obtain the weight factor corresponding to the candidate cluster head status evaluation value. The mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1].

[0099] It should be noted that a safe, efficient and dynamic UANATS data transmission method further includes a database for storing and managing the status information of each communication node of the unmanned aerial vehicle. In this embodiment, the database is used to store the reference value of the interference power of the set communication node, the reference value of the signal strength of the set communication node, the reference value of the number of times of role change of the set communication node, the reference value of the packet loss rate of the set communication node, the correction factor corresponding to the interference power of the set communication node, the correction factor corresponding to the signal strength of the set communication node, the correction factor corresponding to the number of times of role change of the set communication node, the correction factor corresponding to the packet loss rate of the set communication node, the threshold value of the status stability evaluation value of the communication node, the status stability evaluation threshold of each communication node of the unmanned aerial vehicle, the set adjustment range of the communication frequency, the reference value of the energy of the set candidate cluster head, the maximum allowable value of the communication delay of the set communication node, the reference value of the bandwidth of the set communication node, the weight factor corresponding to the status stability evaluation value of the set communication node, the weight factor corresponding to the remaining total energy of the set candidate cluster head, the weight factor corresponding to the communication delay of the set communication node, the weight factor corresponding to the bandwidth of the set communication node, the allowable value of the change in the number of unmanned aerial vehicles in the set unmanned aerial vehicle cluster, the reference value of the energy efficiency of the set unmanned aerial vehicle cluster, the maximum allowable value of the average moving distance of the unmanned aerial vehicles in the set unmanned aerial vehicle cluster, the correction factor corresponding to the number of unmanned aerial vehicles, the correction factor corresponding to the energy efficiency of the set unmanned aerial vehicle cluster, the correction factor corresponding to the average moving distance of the unmanned aerial vehicles in the set unmanned aerial vehicle cluster, the preset broadcast stability threshold, the network stability of the unmanned aerial vehicle cluster, the threshold value of the set distance, the reference value of the data transmission rate of the set communication node, the maximum allowable value of the retransmission rate of the set communication node, the weight factor corresponding to the broadcast stability value of the set unmanned aerial vehicle cluster, the weight factor corresponding to the set data transmission rate, the weight factor corresponding to the set retransmission rate, the preset limit on the number of unmanned aerial vehicles within the cluster, etc.

[0100] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0101] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A secure, efficient and dynamic UANATS data transmission method, characterized in that, Including: Obtain the status information of each communication node of the unmanned aircraft in the UANATS (Unmanned Aircraft Networked and Autonomous Tactical System) network, analyze the status information of each communication node of the unmanned aircraft, and obtain the status stability evaluation value of each communication node of the unmanned aircraft; According to the status stability evaluation value of each communication node of the unmanned aircraft, cluster each communication node of the unmanned aircraft in the UANATS network to obtain each unmanned aircraft cluster of the UANATS network, receive and analyze the cluster head information of each candidate cluster head to obtain the status evaluation value of each candidate cluster head of each neighbor node, and screen the cluster heads of each unmanned aircraft cluster of the UANATS network. Count the number of unmanned aircraft in each unmanned aircraft cluster within each monitoring time period and monitor the energy efficiency of each unmanned aircraft and the moving distance of each unmanned aircraft. Process to obtain the broadcast stability value of each unmanned aircraft cluster of the UANATS network in each monitoring time period, and adjust the broadcast frequency of the unmanned aircraft in the UANATS network; Monitor and analyze the data transmission process of the cluster heads of each unmanned aircraft cluster and each communication node of the unmanned aircraft in the UANATS network to obtain the data transmission evaluation value of each unmanned aircraft cluster of the UANATS network. Adjust the clustering of each communication node of the unmanned aircraft in the UANATS network according to the data transmission evaluation value of each unmanned aircraft cluster of the UANATS network.

2. The secure, efficient and dynamic UANATS data transmission method according to claim 1, characterized in that: The status information of each communication node of the unmanned aircraft includes: the signal strength of each communication node, the number of times of role change of each communication node, the packet loss rate of each communication node, and the interference power of each communication node.

3. The secure, efficient and dynamic UANATS data transmission method according to claim 2, characterized in that: The analysis of the status information of each communication node of the unmanned aircraft to obtain the status stability evaluation value of each communication node of the unmanned aircraft is specifically analyzed as follows: Extract the interference power, signal strength, number of times of role change, and packet loss rate of each communication node of the unmanned aircraft, and process to obtain the status stability evaluation value of each communication node of the unmanned aircraft. The status stability evaluation value of each communication node of the unmanned aircraft is used to evaluate the communication stability of the unmanned aircraft; Extract the status stability evaluation value of each communication node of the unmanned aircraft and compare it with the status stability evaluation value threshold of the communication node in the database. If the status stability evaluation value of a certain communication node of the unmanned aircraft is higher than or equal to the status stability evaluation value threshold of the communication node in the database, continuously monitor the status information of each communication node of the unmanned aircraft; if the status stability evaluation value of a certain communication node of the unmanned aircraft is lower than the status stability evaluation value threshold of the communication node in the database, adjust the communication frequency of the communication node of the unmanned aircraft.

4. The secure, efficient and dynamic UANATS data transmission method according to claim 1, characterized in that: The clustering of each communication node of the unmanned aircraft in the UANATS network according to the status stability evaluation value of each communication node of the unmanned aircraft is specifically analyzed as follows: Extract the state stability evaluation values of each communication node of the UAV, and compare them with the state stability evaluation thresholds of each communication node of the UAV stored in the database. If the state stability evaluation value of a certain communication node of the UAV is higher than or equal to the state stability evaluation threshold of each communication node of the UAV, then mark this communication node of the UAV as a candidate cluster head, and thus obtain each candidate cluster head. According to the preset limit on the number of UAVs within a cluster, divide each UAV cluster.

5. The secure, efficient and dynamic UANATS data transmission method according to claim 4, characterized in that: The specific analysis of screening the cluster heads of each UAV cluster in the UANATS network is as follows: Broadcast the cluster head information of each candidate cluster head to each neighbor node. Each neighbor node receives the cluster head information of each candidate cluster head and conducts analysis. The cluster head information of each candidate cluster head includes the remaining total energy, communication delay, and bandwidth. Combining with the state stability evaluation value of each candidate cluster head of the UAV, process to obtain the state evaluation value of each candidate cluster head of each neighbor node. Sort the state evaluation values of each candidate cluster head of each neighbor node, and select the candidate cluster head node ranked first within each UAV cluster as the cluster head of each neighbor node. Thus, obtain the cluster heads of each UAV cluster in the UANATS network.

6. The secure, efficient, and dynamic UANATS data transmission method according to claim 1, wherein: The specific analysis of adjusting the broadcast frequency of the UAVs in the UANATS network is as follows: Preset each monitoring time period. Within each monitoring time period, count the number of UAVs within each UAV cluster and monitor the energy efficiency of each UAV and the moving distance of each UAV. Take the average value of the moving distance of each UAV and the energy efficiency of each UAV within each UAV cluster respectively to obtain the average moving distance of the UAVs within each UAV cluster and the average energy efficiency of the UAVs. Combining with the number of UAVs within each UAV cluster, process to obtain the broadcast stability value of each UAV cluster in the UANATS network for each monitoring time period; Compare the broadcast stability value of each UAV cluster in the UANATS network for each monitoring time period with the broadcast stability threshold stored in the database. If the broadcast stability value of a certain UAV cluster in a certain monitoring time period is higher than or equal to the broadcast stability threshold stored in the database, it means that the broadcast frequency of this UAV cluster does not need to be adjusted. If the broadcast stability value of a certain UAV cluster in a certain monitoring time period is lower than the broadcast stability threshold stored in the database, then adjust and allocate the broadcast frequency of this UAV cluster.

7. The secure, efficient and dynamic UANATS data transmission method according to claim 1, characterized in that: The specific analysis of monitoring and analyzing the data transmission process of the cluster heads of each UAV cluster and each communication node of the UAV in the UANATS network is as follows: During each monitoring time period, monitor and analyze the data transmission process of each communication node within each UAV cluster in the UANATS network to obtain the communication data of each communication node within each UAV cluster in the UANATS network. The communication data of each communication node within each UAV cluster in the UANATS network includes: data transmission rate, retransmission rate.

8. The secure, efficient and dynamic UANATS data transmission method according to claim 7, characterized in that: The specific analysis of obtaining the data transmission evaluation value of each UAV cluster in the UANATS network is as follows: Extract the data transmission rate and retransmission rate of each communication node in each UAV cluster of the UANATS network, and combine the broadcast stability value of each UAV cluster in the UANATS network and the status evaluation value of each communication node in each UAV cluster during each monitoring time period to process and obtain the data transmission evaluation value of each UAV cluster in the UANATS network. The data transmission evaluation value of each UAV cluster in the UANATS network is used to evaluate the network stability of each UAV cluster.

9. A secure, efficient, and dynamic UANATS data transmission method according to claim 8, characterized in that: The adjustment of the clustering of each communication node of the UAVs in the UANATS network is specifically analyzed as follows: Extract the data transmission evaluation value of each UAV cluster in the UANATS network and match it with the network stability of the UAV clusters corresponding to each interval of the data transmission evaluation value stored in the database to obtain the network stability of each UAV cluster. The network stability of the UAV cluster includes: highly stable, moderately stable, and generally stable; Extract the network stability of each UAV cluster in the UANATS network. When the network stability of a certain UAV cluster is highly stable, continuously monitor and analyze the data transmission process of the communication nodes in this UAV cluster; When the network stability of a certain UAV cluster is moderately stable and generally stable, adjust the number of communication nodes in this UAV cluster and re-elect the cluster head.

10. A secure, efficient and dynamic UANATS data transmission method according to claim 8, characterized in that: The specific analysis process of the data transmission evaluation value of each UAV cluster in the UANATS network is as follows: ； Wherein, represents the data transmission evaluation value of the i-th UAV cluster in the UANATS network, represents the broadcast stability value of the i-th UAV cluster in the q-th monitoring time period, represents the evaluation value of the x-th candidate cluster head status of the s-th neighbor node represents the data transmission rate of the j-th communication node in the i-th UAV cluster represents the retransmission rate of the j-th communication node in the i-th UAV cluster, represents the reference value of the data transmission rate of the set communication node, represents the maximum allowable value of the retransmission rate of the set communication node, and e is the natural constant, represents the weight factor corresponding to the broadcast stability value of the set UAV cluster, represents the weight factor corresponding to the set data transmission rate represents the weight factor corresponding to the set retransmission rate, represents the weight factor corresponding to the evaluation value of the set candidate cluster head status, where i represents the number of each UAV cluster , m represents the total number of UAV clusters, j represents the number of each communication node, , n represents the total number of communication nodes, q represents the number of each monitoring time period, , r represents the total number of monitoring time periods, s represents the number of each neighbor node, , p represents the total number of neighbor nodes, x represents the number of each candidate cluster head, , y represents the total number of candidate cluster heads.

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